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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213

Biometrics Based Access Control System

Mujo Hadžimehanović1, Dino Kečo1, Demir Korać1
1
International Burch University, Sarajevo, Bosnia and Herzegovina
mujo.hadzimehanovic@stu.ibu.edu.ba
dino.keco@ibu.edu.ba
demir.korac@stu.ibu.edu.ba
Abstract – Access control includes attendance checking and intrusion prevention. It is used to protect
property, employees and other assets of a company or institution. Since attendance checking and
intrusion detection are important segments of many educational institutions and other businesses as well,
it is important to make these processes faster, easier and as convenient as possible. Lots of institutions
are suffering from unreliable attendance checking methods, so we have decided to use biometrics, more
precisely face recognition to automate and improve this overall process. As part of this study the full
system has been implemented for recognition of people. As an example of usage in an educational
institutions multiple photos will be recorded during the class session, so that in case of students leave
class after the first shot, they will be removed from the attendance sheet. All recognized people will be
stored in Mongo database as an array of features and later read from database and processed by using
Python script for face recognition. All educational institutions are going to have benefits from this study.
Benefits would be improving attendance management and security.
Keywords - attendance, face, images, recognition
1.

Introduction

Technology is rapidly improving nowadays and everyday activities are adopting these improvements. Point is
to automate these activities and not to lose time performing them. Attendance is a really important part in most
organizations such as schools, faculties, companies etc. Today, attendance is performed in various ways. Best
way to do it is biometrics. Biometrics is a bioengineering area which is an automated method for person
recognition based on its physiological or behavioural characteristics. There are many biometric templates such
as fingerprints, face, hand geometry, iris, voice or signature. System is going to use face biometric template
because it is the fastest approach and requires no human intervention. This method is better than other biometric
methods because these methods are time consuming. There are also lots of systems which are using RFID
cards, location based attendance tracking systems, signature based etc. Negative things about these methods
are that they can be faked. In RFID and location based systems employees are carrying RFID cards or GPS
locators. So, other people can check instead of other employees. There are two main stages of face recognition
process and they are face detection and face identification [1]. Recording employees' work hours and their
activities, attendance of students in schools are really important components of every company or school. This
process is maintained by using signature, fingerprint, iris, RFID or face recognition. System is going to use a
camera which captures images of people entering the company or school building. Detected faces will be
compared with pictures which are already in the database. If a person's picture is in the database attendance

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
will be checked automatically. Otherwise, the security system is going to be informed that an unrecognized
person entered the building. So, this system can also be used as an intrusion detection system.

2.

Literature Review

Following section contains a presentation of all related work and their methods.
Since they have large-scale data with massive noisy labels, X. Wu, R. He, Z. Sun, and T. Tan used a Light
CNN framework [2]. Their Light CNN architecture contains Max-Feature-Map to suppress low activation
neurons in all layers. Their model was trained on Celeb-1M dataset. In order to handle noisy labeled images,
they proposed a semantic bootstrapping method to automatically re-label training data via pre-trained deep
networks. For training purposes they used five types of databases. First type is commonly used Labeled Faces
in the Wild which consists of ~13,250 images of ~5,750 people. At VR@FAR=0 for Light CNN-29, they
achieved 97.50%, while results from all other methods were lower than 70%. Next type of the database are
collections of images extracted from Youtube videos which contain YouTube Celebrities (YTC) and
Celebrity1000 database. Precision achieved for these datasets is 94.18%. Third type are MegaFace, IJB-A and
IJB-B datasets which are challenging and they got 85.13% precision. Cross-domain databases are the fourth
type of database. It includes CACD - VS, Multi - PIE and the CASIA NIR - VIS 2.0 database. They achieved
98.55% on CACD, 95.0% on Multi-PIE and on CASIA VR@FAR=0.1% result is further improved from
94.03% to 94.77%.
M. Arsenovic, S. Sladojevic, A. Anderla, and D. Stefanovic use Convolutional Neural Networks (CNNs)
cascade to detect faces and CNN to generate embeddings of each face [3]. Fact is the best results for larger
datasets are achieved by using CNNs, but in their production environment that was not the case. CNN gave the
best results for smaller datasets. Accuracy of 95.02% was achieved on a dataset created by authors in the realtime environment. Five employees of the company took pictures of themselves and they used these pictures as
a dataset. Model was trained with these 5 pictures.
Active annotation and learning framework was used by H. Ye et al [4]. They are starting with face image
training set without labels and train a deep neural network iteratively model created was used to choose
examples for further manual annotation. After following active learning strategy, Value of Information
criterion is derived to actively select candidate annotation images. This model reaches the coverage of 70.7%
with a precision of 95%.
MSR Image Recognition Challenge by J. Li et al introduces a knowledge base which has an idea to assign each
face unique entity key and provide large dataset consisting of about 100,000 famous persons with around 100
images per person (MsCeleb) [5]. Method achieved coverage of 46.1% at 95% precision on the random dataset
and 33% at 95% precision on the hard set of their challenge. Authors proposed a method consisting of two
stages to learn robust human face representations for effective recognition of human faces. First stage in the
training set is cleaning the noisy data because dataset is taken from the internet so images without faces can
appear. In order to do so, a deep neural network was trained on existing dataset.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
S. Chintalapati and M. V. Raghunadh used SVM and Bayesian classifier for automated attendance system
based on face detection and recognition [6]. They proved that these classifiers are better when compared to
other distance classifiers. This system automatically detects the student which enters the classroom and marks
the attendance if recognizes him. One of the failures of the system is recognizing faces only up to 30 degrees
angle variations.

3.

Methods and Materials

Dataset to be used is Labeled Faces in the Wild [7] which is a database of face photographs designed for
studying the problem of unconstrained face recognition. It contains more than 13,000 pictures collected from
the web. Each image has been labeled with the name of the person on it. There are 1680 different persons in
images. Fig.1 shows samples from LFW dataset.

Fig.1. Samples from dataset
These images need to be processed in order to get numerical representation of faces which is called feature
vector. Feature vector consists of various numbers in a specific order which can be: height or width of face,
width of lips, nose height etc… Final output of processed image needs to be an array with features which is
shown in Fig.2. All features are stored in the mongo database for speed improvement. Python script iterates in
a folder which has dataset images and stores one by one in a database with image name and features. Face
Recognition library with deep learning is going to be used for this project. Deep learning model has an accuracy
of 99.38% on Labeled Faces in Wild dataset. Features of face recognition library are finding faces in pictures,
finding facial features in pictures and identifying faces in pictures. Once installed face recognition gives us two
command line programs:
●

face_recognition - recognize face on image

●

face_detection - detect face in image

Face recognition process consists of two stages. This includes taking and preparing training dataset and
integration into existing system. For testing purposes, data was collected at the university. These are images of
students which were taken in the first year. Images are preprocessed and inserted into the mongo database by

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
using python script for inserting images. After insertion, facebook images of the same people were taken and
tested by using python script for face recognition.

Fig.2. Array of features
3.1

Data preprocessing

Implemented system is going to use monitoring cameras at the entrance. It means that we could have some
kind of network or other problems and taken images could be blurry, so we have to include such images in
training dataset, Fig.3. Persons entering the building can be photographed from different angles, so these kind
of photos should be included also in training dataset, Fig 4.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213

Fig.3. Original and Blurred image
Fig.3 shows an example of original and blurred images. If we have perfect conditions we would have a picture
like the original one, but if the system experiences network issues we might have a blurry image like the one
represented. System has to be ready to respond accordingly to these kinds of issues. Python script was written
using OpenCV [8] interface to generate blurry images out of the original ones.

Fig.4. Image from front and side
In Fig.5 we can see facial features drawn on picture of Pep Guardiola. Most important features are shown: eyes,
nose, mouth and chin location. These features are used when recognizing people on images. Face recognition
library contains script face_landmarks for detecting facial landmarks and positioning the face based on them.

Fig.5. Facial features

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
3.2

Usage Workflow

Application usage workflow is represented on Fig.6. Images need to be collected into a single folder, so that
insertion helper scripts can be run. For multiple insertions we need to pass a folder of images to script, which
iterates through these images, creates encodings and inserts them into database. Single insertion script accepts
an image as a parameter, encodes it and inserts into a database. Last step is recognizing images, the script
accepts an image which needs to be recognized and iterates through mongoDB collection and looks for
matching images.

Fig.6. Usage workflow
3.3

Face Recognition Library

Face recognition library which we are using is built using dlib’s face recognition with deep learning. We can
install library by using a python package installer. Once installed we are provided with two command-line
programs : face_recognition and face_detection. Face recognition recognizes faces in a photograph or in a
folder of photos. There should be two folders, one containing known people and second which contains photos
of people which we want to recognize. Face recognition program is run with two parameters which are the
names of these folders. Face detection program finds pixel coordinates of faces. It takes a folder with images
as parameter and at the end prints one line for each face that was detected. There is also an option to speed up
the overall process by doing a recognition with multiple CPU cores. For example if we have 8 core CPU, we
can process 8 times as many images in the same amount of time.
Dlib is a toolkit written in C++ and contains ML algorithms and tools for solving real world problems. The
most important thing is that dlib is an open source library which enables anyone to use it anywhere, free of any
charge. Some of the dlib’s features are Deep Learning, Multiclass SVM, Image Processing etc.. Our library
uses Image Processing tool for face recognition built by using deep learning tools from dlib.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
3.4

Helper Scripts

There are multiple helper scripts which enable user to insert multiple or single image into database and
recognize faces. The most important parts of scripts are represented in the following lines.
insertMultiple.py
for image in images:
current_image = face_recognition.load_image_file("images/" + image)
encodings = face_recognition.face_encodings(current_image)
if len(encodings) &gt; 0:
current_image_encoded = encodings[0]
num_of_images+=1
else:
print("No faces found in the image " + image)
num_of_not_found+=1
continue
mydict = { "image": image, "encoding": current_image_encoded.tolist() }
x = mycol.insert_one(mydict)
print(image + " inserted")

Code snippet above loads images from the folder, encodes them and inserts them into mongoDB. We have to
provide the name of the folder which contains images and simply run the script.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
faceRecognition.py
unknown_image = face_recognition.load_image_file("image.jpg")
unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]
known_faces = []
names = []
for x in mycol.find():
known_faces.append(x['encoding'])
names.append(x['image'])
results = face_recognition.compare_faces(known_faces, unknown_face_encoding)
for x in range(len(known_faces)):
if results[x] == True:
print("Recognized: " + names[x])
else:
print("Failed: " + names[x])

Code represented above does face recognition. It takes an image of the person which we want to recognize,
encodes it, loops through face encodings from the database and checks if a person exists in the database.

4.

Results

By using a custom dataset which was collected from our university. Students' images were taken and tested on
created scripts. From these tests we have obtained accuracy of 90.9% when testing on images found on
Facebook. There were some problems when recognizing people from different angles, but this can be material
for further study. Images of people are not shown because they did not agree to publish their images.
Since face_recognition python library has a pre-trained model there is no need for additional training.
Improvement is that all images are inserted in mongoDB with image name and face encodings array. Fig.5
shows one part of mongoDB record. Python script for inserting images in mongoDB is written and it takes a
folder with images and inserts one by one in the database. In our testing environment LFW dataset is used and
all images are collected into a single folder. Number of images inserted in the database is 4014. There are also
images on which faces are not recognized. Unrecognized images number is 21. So, if we take into consideration
that 4014 images are inserted and 21 are unrecognized which means that more than 99% images were
recognized. Example of such an image is shown in Fig.6. Execution time of the script is about 35 minutes for
LFW Dataset.
Final result of this research would be access control application. Application can be installed on Raspberry Pi
which has a camera installed. All assets that are necessary for access control application to be fully functional
can be installed on Raspberry. These are mongoDB, python and python libraries. Overall process is not so
challenging, so that we do not need anything better than Raspberry Pi 3 B+ which is a model that we used
while testing the application.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020213
5.

Conclusion

The aim of this study was to make the attendance checking process a lot easier for companies and schools by
using biometrics. Every employee or student would be recorded by camera at the entrance and recorded in the
system. For educational institutions cameras will be installed in classrooms so that the system can make
multiple shots during lessons. This research was successful because it made the recognition process faster by
using a document based database which is really fast.

This study will bring benefits for multiple groups. Benefit for schools is easier attendance recording and
reducing waste of time at the beginning of the classes. Also students will not have a chance to avoid coming to
classes because this system will not allow them to cheat. Similar benefit is for companies to track their
employees coming and leaving time. Future research suggestions in this field are solving problems if a person
is recorded from the side and possibly getting blurry images because of internet connection issues.

REFERENCES
[1]

B. T. Liyew and P. Hazari, “A Survey on Face Recognition based Students Attendance System.”

[2]

X. Wu, R. He, Z. Sun, and T. Tan, “A Light CNN for Deep Face Representation With Noisy
Labels,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 11. pp. 2884–2896,
2018, doi: 10.1109/tifs.2018.2833032.

[3]

M. Arsenovic, S. Sladojevic, A. Anderla, and D. Stefanovic, “FaceTime — Deep learning based
face recognition attendance system,” 2017 IEEE 15th International Symposium on Intelligent Systems
and Informatics (SISY). 2017, doi: 10.1109/sisy.2017.8080587.

[4]

H. Ye et al., “Face Recognition via Active Annotation and Learning,” Proceedings of the 2016
ACM on Multimedia Conference - MM ’16. 2016, doi: 10.1145/2964284.2984059.

[5]

J. Li et al., “Robust Face Recognition with Deep Multi-View Representation Learning,”
Proceedings of the 2016 ACM on Multimedia Conference - MM ’16. 2016, doi:
10.1145/2964284.2984061.

[6]

S. Chintalapati and M. V. Raghunadh, “Automated attendance management system based on face
recognition algorithms,” 2013 IEEE International Conference on Computational Intelligence and
Computing Research. 2013, doi: 10.1109/iccic.2013.6724266.

[7]

“LFW Face Database : Main.” [Online]. Available: http://vis-www.cs.umass.edu/lfw/. [Accessed:
19-Jan-2019].

[8]

“OpenCV library.” [Online]. Available: https://opencv.org/. [Accessed: 09-Jan-2019].

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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214

Handwriting digit recognition using Decision Tree Classifiers

Demir Korać1, Samed Jukić1, Mujo Hadžimehanović1
1

International Burch University, Sarajevo, Bosnia and Herzegovina
demir.korac@stu.ibu.edu.ba
samed.jukic@ibu.edu.ba
mujo.hadzimehanovic@stu.ibu.edu.ba

Abstract – The usage of handwritten character recognition has been useful for usage from large to
common consumer usage. The transitional period of the handwritten to the digital age can be largely
improved by focusing on perfecting handwritten character recognition. This paper and work aims to
focus on handwritten digit recognition using the decision tree classifier machine learning method,
implemented, trained and tested on the data set gathered from the Modified National Institute of
Standards and Technology dataset. The data to be recognized is inputted from a pre-existing reliable
set, used both for training and testing, in order to give a fair result. The system is run through a
Python script and the data set is stored in CSV format, preprocessed and ready for further usage.
Taking into consideration the size of the dataset (42000 rows of data), the system’s overall performance
is satisfactory with an accuracy of 85% and outputs the results in an understandable manner.
Keywords – character, decision, handwritten, recognition

1.

Introduction

Optical character recognition is the process of mechanically or electronically converting typed, printed or
handwritten images of text into a machine-encoded text. The source can be taken from a photo of a
document, a scanned document or a scene photo (billboards in a landscape photo). Another possible source is
superimposed text on an image, such as subtitle text from a television broadcast. This process of recognition
and the technique used in it is called a handwriting recognition system. In literature this recognition is
classified into offline handwriting recognition and online handwriting recognition depending on the style of
recognition. If an image of handwriting is previously acquired and recognized after it will be classified as
offline recognition. However if the handwriting is inputted directly into the machine to be recognized this is
called online recognition. One way of doing this is writing on a touchpad or other device dedicated for
writing and having it recognized. Another classification exists regarding the recognition and it is based on the
process of recognition itself and the technique.

We can recognize two main categories: segmentation free and segmentation based recognition. Segmentation
free recognition is based on recognizing the character without segmentation into smaller units or characters,

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
i.e. words into characters. Segmentation based recognition is the opposite of this. In this approach each word
is segmented into smaller units/characters and each character is recognized separately.

Handwriting has been for the most part of our history, the primary means of communication and information
organization, but with the modernization of these fields handwriting is becoming slowly obsolete. However
the legacy of handwritten information cannot be overlooked, so a transitional period and process needs to
occur.
That’s where handwriting and optical character recognition comes into play. The importance of handwriting
recognition is reflected in many industries such as:
health care (7,000 people are killed per year by the poor handwriting of doctors)
automotive (digital handwriting solutions allow drivers to write characters or numerals, or simply
gesture with their fingertips on vehicles' onboard computer screens instead of typing on a standard
keyboard)
field services (field service technicians use HWR technology for digital data capture, decreasing
paperwork and information loss while also allowing technicians to see precise notes on customer
history)
education (using HWR technology, students can benefit from more than just the increased
comprehension linked to taking handwritten notes. For example, handwriting recognition tech can
take your sloppy algebra equation, convert it into neat, digital text, and then crunch the numbers in a
matter of seconds. )
consumer (with the rapid success of tablets and smartphones, the market is desperately in need of an
alternative to inaccurate, digital keyboards and HWR tech is the best remedy.)

2. Previous work

Perwej Y. and Chaturvedi A. have worked on recognizing the English alphabet handwriting using Artificial
Neural Networks using binary pixels of the alphabet to train the Neural Network and the accuracy of this
method is 82.5% [1]. The data set that they worked on are handwritten English alphabet characters which are
scanned from documents and then “cleaned” and “smoothed”. The characters are then split into 25 segment
grids, scaling and thinning the segments of the characters to obtain skeletal patterns. This is then transformed
into binary values representing the segments input. (Shown in Figure 1.)

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214

Input Alphabet

Figure 1. Process of recognition
Amrouch M. and Y. Es saady have worked on a method using sliding window based on the Hough transform
as a feature extraction technique [2]. An inputted image is divided into two windows and then a dominant
direction is determined based on the Hough transform and a directional feature vector sequence has been
formed. This method is based on continuous HMMs and directional features with an average accuracy of
90.4%.The data set that they worked on is a database of Amazigh printed characters, containing 240 isolated
characters. The images of characters are in Gray level of dimensions 96x96 pixels.

M. Hanmandlu and O.V. Ramana Murthy [3] have done a study on recognition of Hindi and English
numerals. The numerals are represented in the form of exponential membership functions which serve as a
fuzzy model. They have achieved an overall recognition rate of 95% for Hindi numerals and 98.4% for
English numerals. The data set that they worked on is a database of 5000 samples of numerals for
handwritten English numerals. For Hindi they used a database of totally unconstrained handwritten numerals
created using the services of a large number of writers, since there is no standard database available at the
moment for handwritten Hindi numerals.

Nafiz Arica at al. has proposed a method of recognition without pre-processing which he believed leads to
loss of necessary information [4]. This has been backed up with a powerful segmentation algorithm with
utilization of character boundaries, maxima and minima, slant angle, upper and lower baselines, stroke height
and width and ascenders and descenders which improved the search algorithm of the optimal segmentation
path, applied on a gray-scale image. The dataset used was the handwritten database of LancesterOslo/Bergen, which contains single author cursive handwriting. In this dataset, 1,000 words with lower-case
letters are segmented and used for HMM training and another disjoint set of 2,000 words are used for testing
performance of the proposed system.
Table 1. Results of recognition for the LOB Dataset
TEST DATA
SIZE
LOB Dataset

2000

LEXICON SIZE
50

1000

30000

40000

92.3

90.8

89.1

88.8

The overall recognition rate of the whole system on word basis for various lexicon sizes is shown in the table
above.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
3. Method and Materials

The dataset being used in the project is the famous Modified National Institute of Standards and Technology
database of handwritten digits [5], as it is the most reliable and largest database of this type. This dataset is
taken as a subset of another larger dataset by NIST. The MNIST database of handwritten digits consists of
42000 rows of data. It will be split into a 80/20 ratio for training and test data respectively, so the training
data will have 33600 rows and test data will have 8400 rows of data. The digits have been size-normalized
and centered in a fixed-size image. The database and the files such as the training set images and labels, and
the test set images and labels can be found at: http://yann.lecun.com/exdb/mnist/

The machine learning model used will be a Decision Tree Classifier implemented through the scikit-learn
machine learning library in Python [6]. Decision Trees are used in data mining, machine learning and
statistics as a predictive modeling approach. The structure of trees is as follows: Class labels are represented
as leaves and the conjunctions of features that lead the class labels are represented as branches. The process
of operation will be such that the dataset will be inputted as a matrix containing cell inputs from the database
as intensity values of pixels of 28x28 images.
Table 2. Sample from dataset
label

pixel0

pixel1

pixel2

pixel3

pixel4

pixel5

pixel6

pixel7

pixel8

pixel9

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An empty classifier will be created and using the fit method it will be filled with the training data. After the
classifier finishes with the training data, we will move on to the rest of the data set, the testing part. Using the
predict method we will output the classifier prediction of the handwritten digit from the test dataset along
with the actual image of the digit.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
4. Process
The process of recognition is as follows:
The dataset is imported and separated into two parts with a ratio of 80/20. The train set consists of 33600 and
the test set consists of 8400 rows of data.

Splitting the dataset:
traindata=data[1:33600,1:]
train_label=data[1:33600,0]

The data and its label are fitted to the model to learn from it. We do this by using the fit method and passing
our training set to it.

Fitting the training set:
clf.fit(traindata,train_label)

The user of the system gives an input of the order number he wants to test the system with, from the dataset.
That number is taken and a sample with that order number is chosen from the dataset, along with its actual
label.

Figure 2. Taking input from the user

Using the predict method the sample is predicted from the sample and the prediction is outputted. Using the
shape method we are taking the sample from a row vector and shaping it as a 28x28 matrix of pixel intensity
values. We are then creating a figure, which will be displayed after prediction.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
Using the shape method:
d.shape=(28,28)
When the figure is created, we are proceeding with the prediction. We will then be using the predict method
from the Decision Tree Classifier in the scikit-learn library [7].

Using the predict method along with output of the data:
print ("The predicted digit is =", clf.predict( [testdata[number]]))
print ("The actual digit is =", actnum)

Along with predicting the digit, we will also be outputting the actual label of the sample number that the user
chose. An extra feature added is the current certainty of prediction calculation.

Certainty of prediction:
p=clf.predict(testdata)
count=0
for i in range (0,8400):
count+=1 if p[i]==actual_label[i] else 0
print ("Certainty of prediction=", (count/8400)*100,"%")

For this feature we are taking all numbers in the range of the test data set and using the predict method, as to
calculate the success rate of our model on the current test data.

Figure 3. The systems’ process from the users’ perspective

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
5. Usage workflow
In Figure 4. We can see the workflow according to which the system will be operating.

Figure 4. Usage workflow

Since the system does not need dataset input from the user, we will just be importing the dataset. The system
needs user input, since the user will be choosing the digit that is to be recognized, so he needs to provide the
order number from the data. The system then outputs its prediction along with other data such as the actual
label and the prediction certainty. This allows the user to analyze the data given to him, and check if the
prediction was correct and is the prediction certainty satisfactory.

4. Decision Tree Classifier in scikit-learn

A decision tree is a flowchart-like tree structure where an internal node represents a feature (or attribute), the
branch represents a decision rule, and each leaf node represents the outcome. The topmost node in a decision
tree is known as the root node. It learns to partition on the basis of the attribute value. It partitions the tree in
a recursive manner called recursive partitioning. This flowchart-like structure helps you in decision making.
It's visualized like a flowchart diagram which easily mimics the human level thinking. That is why decision
trees are easy to understand and interpret.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214

Figure 5. Decision tree operation diagram
5. Results

After processing and thorough testing the model seems to have a success rate of ~85% on the test dataset
given to it. The system itself may have some confusion when analyzing similar digits. This occurs because
the digits themselves are handwritten and because the data has been gathered from over 250 different writers,
and some of them write different digits in a similar manner. An example is shown in Figure 6. where we can
see that the system is having trouble predicting number 9, but instead predicts 3. From the image we can see
that the digits themselves are quite similar.

Figure 6. Wrong prediction of digit 9 as digit 3

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020214
Different parts of the world write digits differently, so the algorithm would be much more accurate if it
would be implemented based on location, and also, if different Machine Learning methods or Ensemble
methods would be used, we would surely improve accuracy. Finally the thing that would take the recognition
to the next level is image quality, considering that this algorithm has been implemented on a dataset with
quite low quality of images.

5. Conclusion

It should be noted that this data set is not sufficient for a higher level model, to be used in production, but as
its using a small dataset, used for initial training, it has shown to be a pretty successful model and method.
If we would train the aforementioned algorithm on a larger dataset with higher image quality, it could be
used for real world projects. The confusion of the system may also be affected by the quality of the images in
the given dataset, as it is limited to only 28x28 matrices. Future training with a dataset with matrices of larger
magnitude may prove more successful.

REFERENCES
[1]

Perwej Y. &amp; Chaturvedi A. -Neural Networks for Handwritten English Alphabet Recognition.

2011 IJCA
[2]

M. Amrouch, A. Rachidi, M. El Yassa, D. Mammass - Printed amazigh character recognition by a

hybrid approach based on Hidden Markov Models and the Hough transform. 2009 IEEE https://scikitlearn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html
[3]

M. Hanmandlu, O.V. Ramana Murthy - Fuzzy model based recognition of handwritten numerals.

2007 Pattern Recognition
[4]

N. Arica, F.T. Yarman-Vural - Optical character recognition for cursive handwriting. 2002 IEEE

[5]

MNIST handwritten digit database - http://yann.lecun.com/exdb/mnist/

[6]

Decision Tree Classification in Python -

https://www.datacamp.com/community/tutorials/decision-tree-classification-python
[7]

sklearn.tree.DecisionTreeClassifier-

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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020215

Machine Learning in Autism Spectrum Disorder Diagnosis

Naida Nalo1, Jasmin Kevrić1
1

International Burch University, Sarajevo, Bosnia and Herzegovina
naida.nalo@stu.ibu.edu.ba
jasmin.kevric@ibu.edu.ba

Abstract— This paper represents an overview of Machine Learning techniques used in Autism
Spectrum Disorder - ASD diagnosis. ASD is detected based on behavioral screening which is time
consuming and can only be taken by a medical professional. The idea is to find a smaller number of
features that are still able to equally well provide satisfying results and not lose the accuracy, sensitivity
nor specificity. Some of the algorithms mostly used in recent studies were Artificial Neural Network ANN and Alternating Decision Trees - ADTrees. The researches usually use WEKA software package
for applying the algorithm and obtaining results.
Keywords—Machine Learning, Autism Spectrum Disorder, diagnosis, features, ANN, ADTree, WEKA.

1. Introduction

Autism Spectrum Disorder (ASD) is defined as a developmental disorder that reflects in difficulty to
communicate and interact with people, to have minimal interests and to generate pattern like behaviors. There
are three separate conditions that are combined into the Autism Spectrum Disorder and those are: Autistic
disorder, Asperger’s syndrome and Pervasive developmental disorder not otherwise specified (PDD-NOS).
Even though ASD can be a lifelong disorder, an early diagnosis and proper treatment can help improve
communications skills and overall ability to function. However, the diagnosis sometimes takes a lot of time,
which prolongs the appropriate treatment [1].

Two widely used clinical diagnosis tools for diagnosing autism are The Autism Diagnostic Interview-Revised
(ADI-R) [2] and Autism Diagnostic Observation Schedule (ADOS) [3]. ADI-R consists of ninety-three
questions that are to be answered by a clinician. This process can take up to two and a half hours to conduct.
The ADOS contains four modules, that can be used to test children and adults, according to behavioral and
language levels of the person to be tested. This tool uses an algorithm that results with a diagnosis based on
the scores of responses. Each module has its own scores [4]. It has become of great importance to find a faster
but reliable method of diagnosing ASD, since the earliest treatment gives a greater chance for improvement.

�This paper gives insight on the studies conducted in the past on the subject of Machine Learning in ASD
diagnosis. A brief review on differences between two versions of Diagnostics and Statistical Manual of
Mental Disorders (DSM-IV [5] and DSM-5 [6]) is made.

2. Literature review

The ADI-R is one of two most widely used instruments for behavioral diagnosis of ASD [7]. It is structured
in a form of an exam containing ninety-three questions and can be applied to individuals from the age of
eighteen months and above. The questions are answered by a trained professional but still take up to two and
a half hours to finish. And additionally, the gap between the initial screening and the resulting diagnosis can
be around thirteen months, depending on the socioeconomic status of the family [8]. This introduces an
additional delay in the early treatment crucial for proper development of the person, especially children. In
[9], it was proposed to create an exam that can be conducted in minutes, rather than hours and receive
satisfying results.

Machine learning was used to select the right amount of questions, out of initial ninety-three, that would be
able to classify the person in either autism or non-spectrum class. In total, fifteen algorithms were tested, and
the one that performed the best with the given data was found to be the Alternating Decision Tree (ADTree).
This classification algorithm managed to successfully classify all individuals diagnosed with ASD using only
eight questions, that were previously tested with a complete set of ninety-three questions of ADI-R and
misclassified only one.

However, this research was proved to be unreliable by [10]. This paper brought to attention the importance of
understanding both the computational and clinical area before giving any conclusions. The research conducted
in [9], was limited by the imbalance of data as well as excluding a big part of it due to missing values. This
resulted in only a two-class diagnosis, when originally it should have been three. The middle class, which is
the most difficult to identify, that was removed was the ASD Spectrum, leaving only the ASD and Nonspectrum cases. A recommendation from [10] is to use the Unweighted Average Recall – UAR, which is a
measure of performance that works better for such unbalanced data and that was used in this paper, when they
tried to replicate the work done in [9]. Their results were algorithm dependent and if another algorithm was to
be applied to the same data, the number of features would vary.

Another important issue that was discussed in [4] were the differences between results of DSM-IV and the
new DSM-5. From [4] we learn that although both of the screening methods abovementioned have shown
good sensitivity, specificity and high reliability in experiments, the majority of those studies were based on
the DSM-IV rather than the new criteria for diagnosing ASD, the DSM-5. Several studies that were mentioned
in [4] had conflicting results when using the two different versions of the manual. This introduces the need to
reevaluate the current tools for diagnosis, and to adjust them to the new criteria of diagnosing ASD.

�Combining all the research and experiments from the past, and critically analyzing the results, suggestions and
advices for the future projects are provided in [11]. The author highlights that none of the screening tools
currently in use, have incorporated the machine learning algorithm for diagnosing ASD from the recent
studies. Along with the problem of unbalanced data, the overlap of ASD, ADHD and Asperger Syndrome as
well as different forms of ASD, represents another obstacle in diagnosing, mentioned in [11]. Most studies
simplified the classification process by removing these classes and leaving just the ‘Severe Autism’ and ‘Nonspectrum’ as a possible outcome. This of course leads to unreliable classifiers with questionable sensitivity,
specificity and accuracy.

3. Problem formulation

For the purpose of this project, in total three datasets have been downloaded from UCI Machine Learning
Repository [12]. They deal with data related to ASD screening of three different sets of population: toddlers,
adolescents and adults. The data was collected through an application in a form of a quiz [13]. The data sets
consist of twenty questions, out of which ten are behavioral features, while the other ten are individual
characteristics. The application offers four modules representing the age category for individuals from the age:
12-36 months, 4-11 years, 12-16 years and 17 years and older. Ten questions, that differed depending on the
age of the individual, from the application are provided in Table 1, in Appendix 1. Description of the data set
is provided in Table 2.

Table 2. Data set characteristics
ASD Screening Data
MODULE

CHILDREN

ADOLESCENTS

ADULTS

Number of instances

292

104

704

Number of attributes

21

Missing values

Yes

The first module is based on current parent-assisted ASD screening tool, the Quantitative Checklist for Autism
Toddlers (Q-CHAT), while the remaining three are based on appropriate versions of Autism Spectrum
Quotient (AQ), which are considered to be good candidates of diagnosing and were somewhat referred to as
a ‘red flag’. These screening tools were discussed in [4], where it has been noted that the ten questions can
only be used for acknowledging if additional clinical testing is required and is not a definite diagnosis. An
analysis that studied these tools is [14]. Next step of this paper will be to investigate the dataset and determine
the best way to make the most of it.

�4. Machine learning methods

Seven algorithms that were chosen for the process of attribute selection with their brief description are
provided in this chapter. Bayes Net’s function is to learn the Bayesian networks. This algorithm assumes
nominal attributes and no missing values. Search process is done using K2 or TAN algorithm. More
sophisticated search methods, used for search, are built on genetic algorithm, hill-climbing, simulated
annealing, etc. Search speed can additionally be enhanced by ADTrees [15].

Simple Logistic is an algorithm that builds regression models and fits them with use of LogitBoost and simple
regression functions as base learners. Number of iterations are calculated using cross-validation, supporting
attribute selection [15].
Decision Stump’s function is to build one-level decision trees for sets with a categorical or numeric value.
Missing values in this algorithm are dealt with by seeing them as a separate value and creating a third branch
from the stump [15].

J48 is an algorithm that creates a pruned or unpruned C4.5 decision tree. C4.5 This algorithm produces a
classifier in a form of a decision tree, which can be either a leaf or a decision node. A leaf indicates a class, a
decision node specifies a test with one branch and a subtree for every possible outcome of the test [16].

Logistic Model Tree, or LMT, combines two most popular methods of classification: linear logistic regression
and tree induction. This algorithm results in not only classification but also in explicit probability estimates of
the class. Another advantage of LMT is that it results in a single tree which makes it easier to interpret [17].

Random Forest is an algorithm that combines tree predictors. Each tree is dependent on values of a random
vector, which is sampled independently and with same distribution for all trees of the forest. Generalization
error of this algorithm depends on strength of individual trees of thee forest and their correlation. As the
number of trees grows, the generalizatioon error converges to the limit [18].

REPTree algorithm represents a fast decision tree learner. This algorithm uses information regarding gain or
variance and prunes it with reduced-error pruning to build a ecision or regression tree. Values for numeric
attributes are only sorted once, which optimized its speed [15].

5. Results

Classification procedure of this research paper was split in two main parts. First part was applying a 10-fold
cross-validation to all attributes and all three datasets. Cross-validation of n-folds splits the original dataset
into n parts where n-1 parts are used as a train test, while the nth part is used as a test set [19]. Another method
used in this part was applying a percentage split of three different values: 50%, 70% and 90%. Percentage split
separates the original dataset into train and test according to the chosen percentage.

�Both methods were tested using sixteen algorithms, giving in total 64 results for each dataset. The second
part of classification involved attribute selection. Algorithms chosen for this part resulted from the first part,
since only those that gave 100% accuracy for all three datasets were again used in attribute selection part. A
more detailed 10-fold cross-validation results and algorithm performance are presented in Table 3, and the
results of percentage-split and algorithm performance is shown in Table 4.

Table 3. 10-fold cross-validation accuracy results
Method

Cross-validation 10

Algorithm

Dataset

Bayes

Child

Adolescent

Adult

BayesNet

100%

100%

100%

NaiveBayes

98.9726%

98.0769%

97.017%

MultinomialText

51.7123%

60.5769%

73.1534%

BayesUpdateable

98.9726%

98.0769%

97.017%

Logistic

95.2055%

95.1923%

97.017%

MultilayerPerceptron

99,6575%

89.4231%

100%

SimpleLogistic

100%

100%

100%

SMO

100%

89.4231%

100%

88.3562%

90.3846%

94.8864%

DecisionStump

100%

100%

100%

HoeffdingTree

100%

99.0385%

99.858%

J48

100%

100%

100%

LMT

100%

100%

100%

RandomForest

100%

100%

100%

RandomTree

93.1507%

80.7692%

96.1648%

REPTree

100%

100%

100%

Functions

Lazy
IBk
Trees

�Table 4. Percentage split accuracy
Method

Percentage Split (50%-50%, 70%-30%, 90%-10%)

Algorithm

Dataset

Bayes

Child

Adolescent

BayesNet

100%

100%

100%

NaiveBayes

98.6%

96.5%

96.5%

MultinomialText

51.36
%

55.68
%

41.37
%

BayesUpdateable

98.6%

96.5%

96.5%

Logistic

93.1%

89.7%

93.1%

MultilayerPerceptr
on

97.2%

97.7%

100%

SimpleLogistic

100%

100%

SMO

96.5%

100%
98.07
%
61.53
%
98.07
%

100%
100%

Adult
100
%
100
%

54.83
%

50%

100%

100
%

100%
98.01
%
74.14
%
98.01
%

100%

100%

98.5%

97%

74.88
%
98.57
%

97.14
%

80%

Functions
84.61
%
94.23
%

87.09
%
93.54
%

90%

96.59
%

94.78
%

95.71
%

80%

100%

100%

100%

100%

100%

100%

100
%

100%

100%

100%

95.4%

100%

92.3%

93.54
%

80%

100%

100%

100%

89.04
%

89.7%

86.2%

88.46
%

90.32
%

100
%

95.73
%

94.31
%

94.28
%

DecisionStump

100%

100%

100%

100%

100%

100%

100%

100%

HoeffdingTree

98.6%

100%

100%

98.07
%

100%

100%

100%

100%

J48

100%

100%

100%

100%

100%

100%

100%

100%

LMT

100%

100%

100%

100%

100%

100%

100%

100%

RandomForest

100%

100%

100%

100%

100%

100%

100%

100%

RandomTree

93.8%

94.3%

82.7%

67.3%

74.19
%

100%

90.99
%

100%

REPTree

100%

100%

100%

100%

100%

100%

100%

100%

Lazy
IBk
Trees
100
%
100
%
100
%
100
%
100
%
100
%
100
%

Algorithms used for the second part of classifying process of this research paper were chosen according to the
percentage of accuracy of Table 3. Out of four Bayes algorithms, only BayesNet gave 100%, SimpleLogistic
is the only one out of four Function algorithms that proved the best, and lastly, Tree algorithms shown good
results with DecisionStump, J48, LMT, RandomForest and REPTree performing in 100% accuracy for all
three datasets. These seven algorithms were used in attribute selection part of classification. All three datasets
originally had 21 attributes, and the previous two methods mentioned above included all attributes in the
process. Attribute selection method [20] is a process of selecting the most relevant attributes and by doing so,
reducing the processing time.

�In total, five attribute evaluators have been used in attribute selection process. Those were:
ClassifierAttributeEval,

CorrelationAttributeEval,

ReliefAttributeEval,

CfsSubsetEval

and

WrapperSubsetEval. In a combination of these evaluators, three search methods were used: BestFirst,
GreedyStepwise and Ranker [15]. ClassifierAttributeEval evaluates the worth of an attribute with use of a
user-specified classifier [21]. CorrelationAttributeEval evaluates the worth of an attribute by measuring the
correlation between the attribute and the class [21]. ReliefFAttributeEval sampling of instances happens
randomly, and the neighboring instances of the same or different class is checked on [15]. CfsSubsetEval
evaluates the worth of a subset of attributes by considering the individual predictive ability of each attribute
along with the degree of redundancy between them. Missing values can be seen as a separate value or, with
proportion to their frequency, its counts can be distributed among other values [15]. WrapperSubsetEval
evaluates attribute sets by using a learning scheme. Cross-validation estimates the accuracy of the learning
scheme for a set of attributes [15] .

ClassifierAttributeEval, CorrelationAttEval and ReliefAttributeEval required Ranker as a search method. In
all three datasets, number of attributes chosen for the Ranker was five. CfsSubsetEval and WrapperSubsetEval
work using either BestFirst or GreedySetpwise search method. Combining the evaluators with search methods,
we obtained 56 results for each dataset. After the attribute selection was performed on the complete set of 21
attributes, all evaluators resulted with 100% accuracy, regardless of the algorithm used. The attributes of all
three datasets are presented in Table 5.

Table 5. Attributes by number with description
Attribute

Description

1 - 10

Score of 10 questions

11

Age (number)

12

Gender (male or female)

13

Ethnicity (list provided)

14

Born with jaundice

15

Autism in family

16

Country of residence

17

Used app before

18

Result of app (automated calculation)

19

Age description (toddler, child, adolescent, adult)

20

Relation (who is completing the test)

21

Class ASD/NoASD

Attribute that was present in all three datasets and that showed extremely high correlation was the 18th
attribute. This attribute represents the score of ten questions of the application [13]. Therefore, a new approach
was used. The 18th attribute was removed completely, and the process of selection was repeated for all three
datasets. Results of selection are shown in Table 6, 7 and 8, in Appendix 2. Results of accuracy are shown in
Table 9, 10 and 11, in Appendix 3.

�The lowest performance for child, adolescent and adult dataset was achieved by DecisionStump, resulting in
78.082%, 70.192% and 82.822% respectively, as can be observed from the results. The lowest number of
attributes selected is 1, and the highest is 14. However, the best results required less than that. The algorithms
that showed best performance for child dataset were SimpleLogistic and LMT. These algorithms, with applied
CfsSubsetEvaluator, resulted in accuracy of 98.973%, and used 10 attributes. BayesNet showed best results,
with applied ClassifierAttributeEvaluator, it performed in 90.385% accuracy for adolescent dataset and used
only 5 attributes. Simple Logistic successfully classified the adult dataset, with impressive accuracy of
99.432% and used 11 attributes in the process.

6. Conclusion

The conclusion is split into two parts, one regarding actions taken to review already written papers and discuss
their results, and second which deals with actions taken to derive our own conclusion through processing
datasets. This research paper involved three datasets: child, adolescent and adult, with each having 21
attributes. Original datasets were processed using two methods for splitting the dataset into train and test and
used sixteen algorithms for both. The obtained results from the first test helped choose algorithms for the
second part of testing which involved attribute selection. According to the results, seven algorithms stood out.
Attribute selection was performed on all three datasets using seven evaluators. All results had 100% accuracy,
despite using different number of attributes. This leaded to another approach which included removing the
18th attribute and reapplying the selection process. Number of attributes for best performances were dependent
on the dataset and therefore are different. One should keep in mind that classification process using five
attributes can only be used as an indicator of whether further medical testing should be conducted.

The main lesson learned, reading papers written so far on this topic, is that integrating ML in ASD diagnosis
and its screening tools is a much harder process than it seems. Finding the appropriate number of features and
managing to reduce the time of diagnosis depends on many parameters. Many experiments, in an attempt to
reduce the time required for the diagnosis process, have discarded some important issues for the sake of
simplicity. Their initially admiring results could not be taken for granted, due to misbalanced data and
questionable reliability. The algorithm should not be dependent on data. The issue of distinguishing between
ASD and PDD related disorders (ADHD, Asperger Syndrome) represents a big obstacle for proper diagnosis
of ASD. The algorithm should be provided with a similar number of all possible outcomes in order to learn to
better distinguish between categories. The need to reevaluate the current diagnosis tools and adjust them to fit
the new criteria from DSM-5 arises.

�APPENDIX 1
Table 1. Questions from the ASDQuiz application [13]
13-36 months TODDLER

4-11 years – CHILD

12-16 years –
ADOLESCENT

17 &amp; older –
ADULT

1.

Does your child look
at you when you call
his/her name?

He/she often notices
small sounds when
other do not?

He/she notices patterns
in things all the time?

I often notice small
sounds when others
do not?

2.

How easy is it for
you to get eye
contact with your
child?

3.

4.

5.

6.

7.

Does your child
point to indicate that
he/she wants
something (e.g. toy
out of reach)?
Does your child
point to share
interest with you?
(e.g. pointing at an
interesting sight)
Does your child
pretend? (e.g. care
for dolls, talk on a
toy phone)
Does your child
follow where you are
looking?
If you or someone
else in the family is
visibly upset, does
your child show
signs of wanting to
comfort you/them?
(e.g. gives a hug)

He/she usually
concentrates more on
the whole picture
rather than the small
details?
In a social group,
he/she can easily
keep track of several
different people’s
conversation?
He/she finds it easy
to go back and forth
between different
activities?

He/she usually
concentrates more on
the whole picture
rather than the small
details?
In a social group,
he/she can easily keep
track of several
different people’s
conversation?
If there is an
interruption, he/she can
switch back to what
he/she was doing very
quickly?

I usually concentrate
more on the whole
picture, rather than
the small details?
I find it easy to do
more than one thing
at once?
If there is an
interruption, I can
switch back to what
I was doing easily?

He/she doesn’t know
how to keep a
conversation going
with his/her peers?

He/she frequently finds
that he/she doesn’t
know how to keep a
conversation going?

I find it easy to read
between the lines
when someone is
talking to me?

He/she is good at
social chit-chat?

He/she is good at
social chit-chat?

I know how to tell if
someone listening to
me is getting bored?

When he/she reads a
story, he/she finds it
hard to work out the
character’s intentions
or feelings?

When he/she was
younger, he/she used
to enjoy playing games
involving pretending
with other children?

When I’m reading
the story, I find it
difficult to work out
the character’s
intentions?

Would you describe
your child’s first
words as: typical,
unusual, the child
doesn’t speak?

When he/she was on
preschool, he/she
used to enjoy playing
games involving
pretending with other
children?

She/he finds it difficult
to imagine what it
would be like to be
someone else?

I like to collect
information about
categories of things
(e.g. types of car,
types of bird, types
of train, types of
plants, etc.)

9.

Does your child use
simple gestures (e.g.
waves goodbye)?

He/she finds it
difficult to work out
what someone is
thinking or feeling
just by looking at
their face?

He/she finds social
situations easy?

I find it easy to work
out what someone is
thinking just by
looking at their face

10.

Does your child stare
at nothing with no
apparent purpose?

He/she finds it hard
to make new friends?

He/she finds it hard to
make new friends?

I find it difficult to
work out people’s
intentions?

8.

�APPENDIX 2
Table 6. Attribute selection results - child dataset
Algorithm
s vs.
selected
attributes
BayesNet
SimpleLo
gistic
DecisionS
tump
J48

ClassifierAttrib
uteEval

CorrelationAttrib
uteEval

4,9,8,10,1

4,9,10,8,6

ReliefAttribu
teEval

4,1,10,8,9

CfsSubset
Eval (BF
&amp;
Greedy)

1-10

LMT
RandomF
orest
REPTree

WrapperSubs
etEval (BF

Wrappe
r,
Greedy

1-10,17
3,4,6,7,10,12,
16

4,10
4,6,10,1
2,16

4

4

1,3,4,5,7,8,10
4,10
,14
4,6,10,12,16
15,7,8,9,10,15,
4,10
17
1,4,8,10
4,10

Table 7. Attribute selection results - adolescent dataset
Algorithm
s vs.
selected
attributes

ClassifierAttrib
uteEval

CorrelationAttrib
uteEval

ReliefAttribu
teEval

CfsSubset
Eval (BF
&amp; Greedy)

BayesNet
SimpleLo
gistic
DecisionS
tump
J48
LMT
RandomF
orest
REPTree

5,4,3,10,6

WrapperSubs
etEval (BF

Greedy

1,2,3,4,5,7,10
,12

1,3,4,5,1
0,12

3,4,5,10,14

5,4,10,3,6

5,4,10,3,6

5,3,10,4,8

3,4,5,6,7,8,
10,17

5
2,5,9,14
3,4,5,10,14

5,4,3,10,6

15,7,8,10,17

5,4,10,3,6

2,3,5,8

4,5,7,10

Table 8 Attribute selection results - adult dataset
Algorithm
s vs.
selected
attributes
BayesNet
SimpleLog
istic
DecisionSt
ump
J48
LMT
RandomFo
rest
REPTree

ClassifierAttribu
teEval

CorrelationAttrib
uteEval

ReliefAttribut
eEval

CfsSubset
Eval (BF
&amp;
Greedy)

9,6,16,19,7

WrapperSubs
etEval (BF

Greed
y

1-10,15,16
1,3,5,6,9,12,1
1,3,5,
5
6,9
9

9,6,8,7,19

9,6,5,4,3

5,9,6,4,7

1-10,16

1-5,710,16,15
1,3,5,6,9,12,1
5

9
1,5,9
1,3,5,
6,9

1-10,12,15,18,19
1,2,3,5,6,7,9,15

�APPENDIX 3
Table 9. Attribute selection accuracy - child dataset
Attribute
evaluator
ClassifierAttribu
teEval
CorrelationAttE
val
ReliefAttributeE
val
CfsSubsetEval
WrapperSubsetE
val (BF)
WrapperSubsetE
val (Greedy)

Bayes
Net
86.644
%
84.932
%
85.616
%
95.206
%
91.438
%
82.192
%

SimpleLog
istic

DecisionSt
ump

J48

LMT

78.082%

85.95
9%
84.93
2%
83.90
4%
91.43
8%
85.27
4%
82.19
2%

85.95
9%
84.58
9%
87.32
9%
98.97
3%
95.89
0%
83.90
4%

86.301%
84.589%
88.014%
98.973%
95.890%
82.192%

RandomF
orest
85.274%
81.849%
85.274%
93.151%
89.384%
84.247%

REPT
ree
85.616
%
85.959
%
83.219
%
83.562
%
84.589
%
83.562
%

Table 10. Attribute selection accuracy - adolescent dataset
Attribute
evaluator
ClassifierAttribu
teEval
CorrelationAttE
val
ReliefAttributeE
val

Bayes
Net

CfsSubsetEval

87.5%

WrapperSubsetE
val (BF)
WrapperSubsetE
val (Greedy)

88.462
%
77.885
%

90.385
%
89.423
%
82.692
%

SimpleLog
istic

DecisionSt
ump

89.423%
70.192%

J48

80.76
9%

81.731%
89.423%
86.539%
68.269%
78.846%

84.61
5%
72.11
5%
71.15
4%

LMT
89.42
3%
81.73
1%
88.46
2%
85.57
7%
78.84
6%

RandomF
orest

REPT
ree

86.539%
75%
85.577%
83.654%
86.539%

78.846%

76.923
%
68.269
%
72.115
%
71.154
%

Table 11. Attribute selection accuracy - adult dataset
Attribute
evaluator
ClassifierAttribu
teEval
CorrelationAttE
val
ReliefAttributeE
val
CfsSubsetEval
WrapperSubsetE
val (BF)
WrapperSubsetE
val (Greedy)

Bayes
Net
90.341
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90.767
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95.313
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89.347%
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89.06
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94.46%
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90.199
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89.205
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86.364
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89.063
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89.921
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�7. References

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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020216

Distribution of inherited thrombophilia markers in Bosnian-Herzegovinian
population: a review of previous studies
Nermin Đuzić1, Adna Ašić1
1

International Burch University, Sarajevo, Bosnia and Herzegovina
nermin.djuzic@stu.ibu.edu.ba
adna.asic@ibu.edu.ba

Abstract – Thrombophilia is a condition that is associated with an individual’s risk for venous or
arterial thrombosis, as well as a risk of adverse pregnancy outcomes. Gene variants that are the most
commonly associated with inherited thrombophilia are F5 mutation 1691G&gt;A (Factor V Leiden), F2
20210G&gt;A (prothrombin mutation), MTHFR 677C&gt;T, and PAI-1 variant 4G/5G. This paper aims to
review currently available literature on the prevalence of heritable thrombophilia genetic markers
and their association with thromboembolic events in Bosnia and Herzegovina. PubMed and PubMed
Central databases of the National Center for Biotechnology Information (NCBI) and ResearchGate
were searched to identify the most relevant studies. The results of the previously published studies
show discrepancies when it comes to reported findings, thus implying that further research on this
topic is necessary. It is suggested that new studies include greater sample size in order to confirm the
correlation between the studied variants and conditions associated with heritable thrombophilia in
the Bosnian-Herzegovinian population and to advance the understanding of these variants.
Keywords - Bosnia and Herzegovina, Factor V Leiden, Inherited thrombophilia, MTHFR,
PAI-1, Prothrombin mutation

1.

Introduction

Thrombophilia is a condition putting an individual at risk of venous or arterial thrombosis and is mainly
divided into hereditary and acquired. Hereditary thrombophilia is associated with genetic mutations
influencing the level or activity of proteins involved in coagulation cascade and includes both loss-offunction and gain-of-function mutations [1,2]. Three genetic markers are the most commonly studied as
indicators of inherited thrombophilia. F5 gene variant 1691G&gt;A, usually termed Factor V Leiden, gives
rise to a peptide that is uncleavable by the activated protein C (APC) [3]. According to Inbal and Carp
(2007), this mutation is responsible for 3-42% of pregnancy losses [4]. If present in homozygous state, this
mutation increases a risk for venous thrombosis up to 50-100-fold. The second most studied variant is F2
20210G&gt;A, also known as prothrombin mutation (PTM), that causes elevated levels of prothrombin and 25-fold increased risk of venous thrombosis as well as pregnancy loss [5]. MTHFR gene variant 677C&gt;T
codes for thermolabile variant of protein methylene tetrahydrofolate reductase which is a loss-of-function
mutation and causes elevated levels of homocysteine in blood, the condition known as
hyperhomocysteinemia, which is in turn considered a risk factor for venous thromboembolism [6-8]. The
fourth variant indicative of inherited thrombophilia is 4G/5G in type 1 plasminogen activator inhibitor

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020216
(PAI-1) gene, which is a 4328G&gt;T missense variant located 675 bp from the promoter that results in four
or five guanine nucleotides in a row [9,10]. The protein product of this gene has a role in fibrinolysis and
is associated with adverse pregnancy outcomes, such as intrauterine fetal death, intrauterine growth
restriction, preeclampsia, recurrent miscarriage and placental abruption [11].

The aim of this paper is to provide a comprehensive review of the current knowledge regarding the
prevalence of heritable thrombophilia markers and their correlation with thromboembolic events in Bosnia
and Herzegovina (B&amp;H) based on previously published population studies.

2.

Methods

In order to investigate associations between the abovementioned genetic variants and inherited
thrombophilia that may lead to adverse primary outcomes, National Center for Biotechnology Information
(NCBI) databases PubMed and PubMed Central (PMC), and ResearchGate were searched to discover
relevant studies published previously. Included were original research papers published in peer-reviewed
journals that matched the search of the following keywords: “Factor V Leiden”, “F5 1691G&gt;A”,
“prothrombin”, “F2 20210G&gt;A”, “MTHFR 677C&gt;T”, “PAI-1 4G/5G”, “polymorphism”, “thrombophilia”,
“Bosnia and Herzegovina”. In order to enhance the search, Boolean “AND” and “OR” operators were used
to investigate the association between two searched terms.
3.

Prevalence of genetic markers of inherited thrombophilia in Bosnian-Herzegovinian
population

The search results offered a total of seven studies related to the topic of the prevalence of genetic markers
of inherited thrombophilia in B&amp;H, all of them being conducted as of 2013.
The study of Karić and colleagues in 2013 was the first study which deals with prevalence of MTHFR
677C&gt;T polymorphism in Bosnian-Herzegovinian population. They studied 102 men and 105 women, who
were unrelated and healthy and originating from south-east B&amp;H. At the time of blood sampling, the study
participants ranged between 18 and 84 years with a mean age of 45.62 years. The results have shown that
44.44% were heterozygous and 11.11% were homozygous for the study allele. No significant difference
was found in allele and genotype frequencies between male and female participants [12].

The first study aiming at analyzing Factor V Leiden prevalence in B&amp;H was performed in 2013 by Valjevac
and colleagues. A group of 67 women with mean age of 58.6 years (range 41 to 75 years) with no previous
history of cardiovascular diseases and pregnancy loss was recruited and tested. The study failed to find any
mutant allele, thus suggesting that, considering functional importance of this allele, there is a need to
conduct more research on that topic, as the results of this study were heavily influenced with the small
sample size [13].

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020216
The prevalence of polymorphisms Factor V Leiden, prothrombin mutation and MTHFR 677C&gt;T was
studied by Adler and colleagues (2014). The study involved a cohort of 100 healthy unrelated individuals
from B&amp;H (82 females and 18 males) with the year range of 24-82 years and the mean of 58.8 years. The
analyzed loci were in Hardy-Weinberg equilibrium with the following minor allele frequencies (MAF): 6%
for Factor V Leiden, 6% for F2 20210A allele, and 37.5% for MTHFR 677T allele. The authors noted the
drawback of a small sample size and imbalanced sex ratio. The study, however, demonstrated the coinheritance of thrombophilia markers, since nine participants had Factor V Leiden and MTHFR 677C&gt;T
mutant. Compared to 17 European countries, the prevalence of Factor V Leiden and F2 20210G&gt;A variants
was significantly higher in B&amp;H [14].

Another study examined the prevalence of the same three variants and their association with deep venous
thrombosis (DVT) in B&amp;H [15]. The study group included 111 thromboembolic patients (59 females and
52 males ranging from 21 to 84 years) and 207 healthy controls (105 females and 102 males ranging from
18 to 84 years) with no history of venous thromboembolism (VTE). When it comes to Factor V Leiden
prevalence, 18% of the study group patients were heterozygous and 2.7% were homozygous, while 3.86%
of the control group participants were heterozygous for this variant, which a statistically significant
difference between groups. Statistically significant difference was also found between men with DVT and
the control group, as well as between women with DVT and the control women group. F2 20210G&gt;A
variant was detected in 2.7% of the study group patients and was absent in control group, which was not
statistically significant. Frequencies of MTHFR C677T alleles and genotypes did not differ significantly
between the two groups. Allele frequency and functional significance of Factor V Leiden variant detected
in this study was in agreement with earlier studies in Caucasians [16-20]. Also, the results of this study
were found consistent with the data from other neighboring countries [21-23]. The absence of functional
significance of the studied MTHFR polymorphism was also in line with previously published literature
[4,16,24,25]. Finally, the authors of this study found that 14.9% of the patients from the DVT group were
compound heterozygotes for Factor V Leiden and MTHFR 677C&gt;T variants, therefore proposing further
studies that would aim to analyze whether such genotype combination might be a risk factor for DVT
development [15].
A study of Mahmutbegović and colleagues (2017) enrolled 308 women, including 154 women who
experienced pregnancy loss as the study group (mean age 33 ± 5.4 years) and 154 women with at least one
live-born child and without pregnancy loss as the control group (mean age 31.4 ± 6.7 years) to investigate
the correlation between three genetic markers and pregnancy loss. Detected allele frequencies were 3.9%
in both study and control groups for Factor V Leiden, 1.9% and 1.6% in the study and control groups,
respectively, for prothrombin mutation, and 35.7% and 29.9% in the study and control groups, respectively,
for MTHFR 677C&gt;T. Although allele frequencies obtained in this study were in accordance with allele
frequencies obtained for other European countries, the authors, however, were not able to find the
significant correlation between these three variants and pregnancy loss in Bosnian-Herzegovinian women,
which may be due to small sample size of women with three or four pregnancy losses recorded [26].

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020216
The prevalence of Factor V Leiden, prothrombin mutation, MTHFR 677C&gt;T and PAI-1 4G/5G in BosnianHerzegovinian women and their correlation with recurrent pregnancy loss was studied by Jusić and
colleagues (2018). The study group included 60 women with two or more consecutive pregnancy losses
that occurred before 20th gestation week with the same partner and without history of known causes of
pregnancy losses due to chromosomal abnormalities, chronic diseases, or infections. The control group was
consisting of 80 women with one or more successful pregnancy outcomes and without any pregnancy
complication which could lead to the pregnancy loss. The results have shown that Factor V Leiden and
MTHFR 677C&gt;T were proved to correlate with recurrent pregnancy loss, while prothrombin mutation and
PAI-1 4G/5G were not found to be significantly associated with the pregnancy loss. Reported allele
frequencies were as follows: 7.5% for study and 1.88% for control group for Factor V Leiden, 2.5% for
study and 0.63% for control group for prothrombin mutation, 39.17% for cases and 25% for control group
for MTHFR 677C&gt;T, and 30% for study and 20% control group for PAI-1 4G/5G. The authors are reporting
allele frequencies that were in agreement with previous findings for all study polymorphisms. However,
the role of genetic factors for inherited thrombophilia in recurrent pregnancy loss is still a matter of debate,
especially when it comes to MTHFR and PAI-1 variants studied. Therefore, the authors are suggesting
further studies with larger study and control groups, as well as the need to prevent recurrent pregnancy loss
by assessing the status of these variants and calculating individual risk and optimum therapy for each patient
[27].
In the most recent study by Ašić and colleagues in 2019, the prevalence of common thrombophilia markers
was studied in a population of 130 unrelated healthy Bosnian- Herzegovinians of both sexes, from different
age groups, with no recorded history of thrombotic events and originating from different parts of the
country. Seven markers most commonly associated with the risk of heritable thrombophilia were
investigated, namely Factor V Leiden, F2 20210G&gt;A, MTHFR 677C&gt;T, MTHFR 1286A&gt;C, PAI-1 4G/5G,
PAI-1 -844G&gt;A and F13 V35L. Whereas some of these markers were examined in previous studies as
described above, this is the first study to include MTHFR 1286A&gt;C, PAI-1 -844G&gt;A and F13 V35L
polymorphisms in the population of B&amp;H. The results have shown that the two main thrombophilia markers
Factor V Leiden and prothrombin mutation appeared with MAF values of 0.023 and 0.008 respectively.
For the remaining four loci, reported MAF values were 0.331 for MTHFR 677C&gt;T, 0.323 for MTHFR
1286A&gt;C, 0.446 for PAI-1 4G/5G, 0.588 for PAI-1 -844G&gt;A, and 0.315 for F13 V35L. This study provides
the most extensive population data on the prevalence of main heritable thrombophilia risk factors in B&amp;H
and reported allele frequencies were consistent with those reported for other European populations [28].

4.

Conclusion

Previously conducted studies in B&amp;H represent a small and rather heterogenous group of studies, including
either population studies or case-control studies with the aims to report heritable thrombophilia marker
prevalence in the population or their potential association with DVT, pregnancy loss or recurrent pregnancy
loss. While initial preliminary studies offered surprisingly low or high MAF values for the most well-known
genetic variants Factor V Leiden and F2 20210G&gt;A, later studies reported allele and genotype prevalence

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020216
that is in line with reported data for most European populations. While DVT was found to be positively
associated with Factor V Leiden variants [15], the data for obstetric complications are more controversial
since two studies reported conflicting results. The first study reported no statistically significant association
between Factor V Leiden, F2 20210G&gt;A and MTHFR 677C&gt;T and pregnancy loss [26], while the second
one reported a significant increase in mutant allele frequency for Factor V Leiden and MTHFR 677C&gt;T in
women with recurrent pregnancy loss [27]. Therefore, it is strongly suggested that further studies assess the
functional importance of the most important markers for inherited thrombophilias in B&amp;H by clearly
defining study and control groups in order to assess the potential association of these variants with
conditions such as (recurrent) pregnancy loss and venous thromboembolism with the goal of assessing the
importance of genetic testing in Bosnian-Herzegovinian population and establishing the groundwork for
the personalized treatment of inherited thrombophilia and conditions connected to it. In that effort, larger
study cohorts including individuals from all parts of the country will be necessary.

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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217

Analysis of Transient and Voltage Stability of an 11-Busbar Testing System

Alma Halilović1, Mirza Šarić1
1

International Burch University, Sarajevo, Bosnia and Herzegovina
alma.halilovic@stu.ibu.edu.ba
mirza.saric@ibu.edu.ba

Abstract – A comprehensive treatment from the physical and mathematical perspective supply
modelling, analysis, control and covers a range of topics including modelling, computation of load flow
in the transmission grid, stability analysis of the transient state. It is widely accepted that transient
stability is an important aspect in designing and upgrading electric power system. In utility planning,
transient stability is studied by numerical simulation. It involves the study of the power system
following a major disturbance. In order to study Electric Power System transient stability, the models
to describe their components should be defined. The components are defined using the classical model,
which is valid to time periods up to 2 seconds. This project contains 11 busbars, 1 synchronous
generator, 3 loads and 8 transformers. This research is done in DIgSILENT PowerFactory software
for network modeling and simulation by using Stability Analysis Functions (RMS) advanced feature.
In this paper we are analyses the maximum rated power of distributed generation (DG) considering
only the terms of voltage limit constraints, the N-1 operational criterion analysis and three-phase
symmetrical fault analysis for N-1 criterion is examined.
Keywords - high load, n-1 criterion, synchronous generator, transient stability analysis

1.

Introduction

Stability in Power Systems is one of the importances of a system that had increased. It is the most widely
used from power blackouts. Today, usage of power systems interconnection had increased using of new
technologies and controls, and the increased its usage in highly demanding situations. In order to maximize
the system stability research on power system stability should be carried out. In order to design the perfect
system to solve this problem a detailed study of the design should be performed. In the last years [1], due to
the spread of electric generation facilities and economic factors, Electric Power Systems operate more closely
to their limits. Thus, more than before, it is of crucial importance the existence of methods to assess the
system stability. In [2] there are two kinds of stability problems: voltage stability and transient stability. This
paper addresses the transient stability.
Transient stability analysis of a power system is concerned with the system’s ability to remain in
synchronism following a disturbance. Following a large disturbance, the synchronous alternator the machine
power (load) angle changes due to sudden acceleration of the rotor shaft. The objective of the transient
stability study is to ascertain whether the load angle returns to a steady value following the clearance of the

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
disturbance. The loss of synchronism develops in a very few seconds after the disturbance inception, among
the phenomena transient stability is the fastest to develop. These challenging aspects motivate our choice to
mainly concentrate on transient stability. The conventional transient stability measure of the system
robustness to withstand a large disturbance is its corresponding critical clearing time (CCT). This is the
maximum time duration that the disturbance may act without the system losing its capability to recover a
steady-state operation. Another transient stability measure of great practical importance is the power
(generation or transfer) limit. It is defined as the largest power sustainable without loss of synchronism, given
the occurrence of a large disturbance and it’s clearing scenario. In [4], note that the measures imply
consideration of three distinct phases: the pre-fault, the during-fault, and the post-fault one. In [5] faults need
to be cleared within critical clearing time and after that system need to be able to regain stability. Some of the
most important parameters influencing stability are fault clearance time, fault location, and type of the fault.

2.

Literature Review

Mania Pavella [3] identified three classes of approaches – Decision Tree, KNN and neural network - to
transient stability and analyzed which can meet most stringent requirements of transient stability. It is found
that stability could be achieved with the appropriate combinations of numerical, direct, and automatic
learning techniques.

Mirza Saric and Irfan Penava [5] in their research discussed theoretical background of induction generator, its
simulation model, as well as dynamic response analysis procedure for a wind farm connected to real network.
Thought their research they showed the importance of transient stability in case of integration of large
renewable sources to the network. In terms of rotor angle, frequency and voltage stability issues the observed
case of wind farm integration was not appropriate to connect to the network with induction generator as the
rotor speed was too large, with sharp reduction of reactive power as voltage and active power equal to zero
for period that are too long for system to operate in stable state.

Innocent Davidson and Immanuel Mbangula [6] examined and analyzed the fault that appeared on the 330kV
transmission line between Omburu sub-station and Ruacana power station where the blackout happened for 6
hours. The goal of this research was to investigate what fault occurred, what is the cause and solutions to
prevent such fault occur again. The results from DIgSILENT PowerFactory are compared with data obtained
from NamPower records and it is found that it was the single phase to ground fault.

Ioanna Xyngi, Anton Ishchenko, Marjan Popov, and Lou van der Sluis [7] in their research described the
transient stability analysis of a 10-kV distribution network with wind generators, microturbines, and CHP
plants modeled in Matlab/Simulink and investigated faults that are simulated on various locations. They
showed that in the network with distributed generators (DGs) the protection settings must be adjusted
accordingly in order to have stable system as the undervoltage protection should be different for different
DGs.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
Diaz-Alzate, Candelo-Becerra and Villa Sierra [8] investigated and found a new way of managing and
controlling transient stability based on relative angles. They showed how predefined thresholds of relative
angles which they attained by offline simulations and the relative angles attained during the online operation
with PMUs are useful in the process of monitoring as well as predicting transient stability under real-time
operation. They performed analysis on New England with 39 busbars and IEEE with 118 busbars networks
with different contingencies and control actions that are applied at predicted time. The relative angle and the
predefined thresholds of the relative angle helped in monitoring and predicting of the systems instability with
enough time to respond to oscillations that appeared in the system.

3.

Methodology

In this part we will show 3 different steps of methodology. In first step we will search and show what is the
maximum power that satisfies standards of synchronous generator while checking the voltage profile. In the
second step we will do N-1 operational criterion analysis for 6 different cases in this grid and found the new
maximum power that satisfies the network. In the last step we will do three phase symmetrical fault analysis
for N-1 criterion, with 4 different cases in it.

(a) In the first part of the project the maximum rated power of a generator at BB13 (DG), considering only
the voltage limit constraints is found, and then the three-phase symmetrical fault analysis is performed for the
value of maximum power. We investigate fault duration period of 0.02 seconds. After the RMS simulation is
done, voltage development, rotor angle, active and reactive powers are plotted for the further analysis.

b) In the second step the n-1 criterion in terms of voltage profile development, as well as line and transformer
loading, for 6 different cases for high load scenario, with maximum DG power was investigated. An
operational criterion N-1 can be applied to the existing network, if there may be planned or unplanned
congestion that may exist at a certain moment. If the criterion is satisfied, that means the system will be able
to support a predefined contingency, operating after that, with a minimum performance. The N-1 criterion
requires that the system can be able to tolerate the outage of any one component without disruption and does
not concern itself with the probability of an outage. If an outage is highly unlikely, the criterion is still
generally applied because system failure due to a lost component is unacceptable. The criterion is generally
considered as the need to balance generation and load. For modeling network for 6 different scenarios, 6 lines
from which the network is consisted are modeled with the following event that placed lines one by one out of
service. The voltage on the critical busbar – point of coupling - was monitored along the way, as well as the
voltage in the entire system, with the line and transformer loading, making sure that the voltage or line and
transformer loading does not exceed the permitted limit specified by the standard EN 50160 for delivered
power quality. Minimum upper limit for the voltage, as denoted in the EN 50160 standard, is 0.9 p.u., while
maximum upper limit for the voltage is 1.1 p.u. Regarding the line and transformer loading the constraint
limits determined by the standard EN 50160 is that it does not exceeds loading of 100 %. In such way the n-1
criterion is investigated and the maximum power for which the system is in the stable mode operation is
found for each of the different scenarios when one by one line were out of service. For different events that

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
placed different line out of service, the system will be stable for different maximum power produced from
generator.

c) In the next part of the research the three-phase symmetrical fault is simulated and the rotor angle, active
power, reactive power and voltage development for the following cases, for high load conditions and
maximum DG power is to be reported in the results and discussion part of this research project. Three-phase
symmetrical fault is simulated in the DIgSILENT PowerFactory software for network modeling and
simulation, one second before, during and 5 seconds following the fault on 6 different lines for each of the
case scenario. This research is done in DIgSILENT PowerFactory software for network modeling and
simulation by using Stability Analysis Functions (RMS) advanced feature. First, the maximum power
generation from synchronous generator is found by using the power flow option in the program where all
voltage on all busbars, as well as line and transformer loading in the network, is checked so to satisfy EN
50160 standard limits. Next, in order to satisfy limits, set by EN 50160 standards in terms of voltage profile,
line and transformer loading when 6 lines of which the system is consisted are modeled with an event that
placed line one by one out of service. In such way, by using the power flow analysis function when lines are
out of service the n-1 criterion is investigated. For the third part of the research, where three-phase
symmetrical faults are simulated on each of the 6 lines that were investigated. The duration of the fault is for
the analysis of the 4 case scenarios set on lines to be 0.02, 0.05, 0.5 and 5 seconds and then rotor angle, active
power, reactive power and voltage development for the following cases, for high load conditions and
maximum DG power are plotted in the graphs, and in such way the behavior of the system could be tracked.

d) In the last part of this project the power factor is changed when line 2 is followed with an event that placed
it out of service, thus when investigating the N-1 criterion. Values of power factor that are taken into
consideration are 0.8, 0.9 and 1, both capacitive and inductive while the voltage development is analyzed and
new maximum power of generator is determined in order to satisfy EN 50160 standard for voltage variation
in the network for new values of power factor.

4.

Results and Discussion

A. Maximum Power from Generator in Terms of Voltage Profile

In the first part the maximum voltage in the network is found by changing the power generated by the
synchronous generator while checking the voltage profile of the network in order that voltage does not
increase beyond allowed limits. In the Table III. main results of power flow in terms of voltage magnitude
and angle at the busbar BB11 which is the point of coupling, are shown when network operates with no any
faults occurring in the system. Maximum power generated from synchronous generator that satisfy the
voltage limits set by EN 50160 standard is found to be 286 MW, while the maximum power that satisfy all
criterions from the standard – voltage, line and transformer loading – is found to be 104 MW.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217

Fig. 1. Network Model from DIgSILENT PowerFactory software

The power stability analysis of the given network is done in terms of three-phase symmetrical fault analysis
for the maximum power which satisfies the allowed voltage limits and equals to 286 MW. The three cases
are investigated where the duration of the fault is set to be 0.02 seconds in fist case, 0.05 seconds in second
case and 0.2 seconds in third case. The results obtained when duration of fault is taken to be 0.02, which is
expected to show the best results due to lowest fault duration, are shown in Fig.1. In the Fig 1. where the
graphs of voltage of the busbar which is the point of coupling, angle of rotor of the synchronous generator, as
well as active and reactive power of the synchronous generator are plotted. It can be seen from the graphs
that for the maximum power that satisfy the EN 50160 standard only in terms of voltage profile, the system is
unstable even for the very small periods of fault duration and it shows that for this high power of generator
the network quite inadequate to operate.

B. N-1 Operational Criterion Analysis

Summary of results obtained when different lines in the network placed out of service are presented in the
Table I. and dynamic response of voltage profile in Fig.2., as well as rotor angle in Fig.3. It can be observed
which line is the most critical and which is maximum power for such line. The maximum power that satisfies
the n-1 criterion for the entire network is found to be 93 MW, since it satisfys the n-1 criterion for the most
critical line, which is little bit lower than the maximum power that satisfys the EN 50160 standard for
delivered power quality when all lines are in service that is found to be 104 MW. The maximum power for
line 1 and line 2 is 93 MW, thus, this value of generated power is compared with maximum power of all
other lines in the system, while the voltage magnitude, as well as angle, does not change significantly. In the
Table II. the line and transformer loading is compared for same lines for their maximum power and value of
93 MW, and as it can be seen, there is approximately more that 10% of difference in line loading and around
4% in transformer loading. From the results obtained it can be concluded that the most realiable solution is to
consider value 93 MW as maximum power that satisfy N-1 criterion for entire network.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
Table 1. Voltage developments for maximum power for each line in the network determined by N-1 criterion
Out of service
(BB11)
Line 1 93 MW
Line 2 93 MW
Line 3 93 MW
Line 3 105 MW
Line 4 93 MW
Line 4 105 MW
Line 5 93 MW
Line 5 100 MW
Line 6 93 MW
Line 6 105 MW

UI, Magnitude
MV
67,81801
67,1283
67,4659
68,03866
67,39707
67,94841
65,03935
65,13477
67,48871
68,16291

u, Magnitude
p.u.
1,027546
1,017095
1,022211
1,030889
1,021168
1,029521
0,985445
0,98689
1,022556
1,032771

U, Angle deg
6,905885
6,473696
6,748108
8,197442
6,682203
8,111645
8,237019
9,947232
5,909104
7,01058

Table 2. Line and transformer loading for N-1 criterion in %
N-1 criteria
(BB11)
Line 1
Line 2
Line 3
Line 4
Line 5
Line 6

Power

Loading [%]
line 2/1

93 MW
93 MW
93 MW
105 MW
93 MW
105 MW
93 MW
100 MW
93 MW
105 MW

97,9854
99,39992
87,84784
99,58101
87,93902
99,71524
91,17996
98,65325
87,81764
99,39667

Loading [%]
Two-winding
transformer (5)
93,85382
96,90187
81,66314
84,96854
81,74933
85,08491
84,81535
87,13317
81,63461
84,80878

Fig. 2. Dynamic response for 0.02 s fault duration on lines – Voltage

Fig. 3. Dynamic response for 0.02 s fault duration on lines – Rotor Angle

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
C. Three Phase Symmetrical Fault Analysis for N-1 Criterion

Since it has been shown that the system is unstable for the maximum power that satisfy EN 50160 standard in
term of voltage variation, the three-phase symmetrical fault analysis is done after the N-1 criterion is satisfied
for the observed network. The maximum power on the most critical line is previously found to be 93 MW by
using the N-1 criterion, and in this part, this is the power for which the system is analyzed. The four cases are
examined where the duration of the fault is set to be 0.02 seconds in the first, 0.05 seconds in the second, 0.5
seconds in the third and 5 seconds in the fourth case. Since the line 2 is shown to be most critical in the
network after the N-1 criterion analysis done for this case, the result for this line are shown in the graph
plotted after the RMS simulation done. In the Fig. 4. the dynamic response for 0.02 seconds fault duration on
line 2 in terms of voltage profile is shown. As it can be seen from the graph, when the fault occurs in the
system on the line 2, there is voltage drop at the time of fault occurrence and as the duration of the fault is
0.02 seconds, the system returns to be in the balance eventually. In the Fig. 5. there is rotor angle of
synchronous generator, active and reactive power presented. As it can be observed from the figures, the
system is for the 0.02 seconds fault duration stable and the network for power of 93 MW generated from
synchronous generator is adequate and secure for operation as the system after some period reaches
equilibrium state.

The dynamic response in terms of voltage profile is same as for 0.02 s which is shown is Fig.3., while in Fig.
6. dynamic response of rotor angle of synchronous generator, active as well as reactive power is shown when
duration of fault is taken to be 0.05 s for the three-phase symmetrical fault simulation. As it can be seen from
Fig. 5. when the fault occurs in the system on the any line, there is voltage drop as the fault occurs on the
line, after which, for all lines except line 1, system is stable and able to reach new equilibrium. Voltage
dynamic response is same as in Fig.3 when the fault occurs in the system on line 1. There is the voltage drop
where voltage drops to approximately zero for longer period than it was case on all other lines, and it will
oscillate in the range from value slightly higher than 0 p.u. to approximately 0.35 p.u., with no signs that it
will eventually come to the state of balance. However, observing the dynamic response of rotor angle, active
and reactive power for the line 1 from Fig.7. for 0.05 s fault duration, the system is unstable to adequately
operate since it is unable to attain equilibrium state again.

In the Fig. 8. and Fig. 9. after the RMS simulation is done, the results obtained show that in terms of voltage
development seen from the Fig. 8., at the time of fault occurrence there appears the voltage drop where the
system goes back to the balanced state eventually. In the Fig. 9. the system response of rotor angle of
synchronous generator, active and reactive power show that the system for the 0.5 seconds fault duration is
stable and the network for power of 93 MW generated from synchronous generator is adequate and secure for
operation in case for all analyzed lines except for line 2. Considering case when fault simulated on line 2 for
0.5 s, the dynamic response of voltage development, rotor angle, active and reactive power is similar as
response in Fig. 8. while voltage dynamic response is shown in Fig. 10. There is a major voltage drop in the
system which is the consequence of the fault that occurred on the line 2. The voltage, after it drops to value
slightly higher than zero, is oscillating from that value to approximately 0.35 p.u. Since, also, all other

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
parameters continued to oscillate equally for all 10 seconds and t will not came back to the balanced state,
thus, the system is denoted as unstable in terms of all parameters examined.

Fig. 4. Dynamic response for 0.02 s fault duration on line 2 – Voltage

Fig. 5. Dynamic response for 0.02 s fault duration on line 2 – Rotor Angle (blue), Active (purple) and
Reactive Power (green)

Fig. 6. Dynamic response for 0.05 s fault duration on lines – Rotor Angle (blue), Active (purple) and Reactive

Power (green)
In the Fig. 11. the results obtained from the three-phase symmetrical fault analysis when duration of fault is
taken to be 5 seconds occurring on the line 2 is shown in terms of voltage profile and in Fig. 12. rotor angle
response is shown. Since the duration of the fault on lines is taken to be 5 seconds, which represents too long
period for a fault, it can be observed that there is the breakdown of the system in terms of rotor angle where
the dynamic response is infinitely oscillating where the speed of the rotation is increasing causing system to

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
be out of balance. There is with the voltage drop at the time the fault occurs there is rise in the angle of rotor
which starts to excessively rotate, and drop in active power to the respect of reactive power rise. At the time
there is fault on the line 2 it can be observed that all analyzed parameters are oscillating in the smaller range,
while at approximately 6th second, when the duration of the fault is over, there are greater oscillations where
the system is unable to reach the equilibrium state and, instead, and reaches the state of complete breakdown.

Fig. 7. Dynamic response for 0.05 s fault duration on line 1 – Rotor Angle (blue), Active (purple) and
Reactive Power (green)

Fig. 8. Dynamic response for 0.5 s fault duration on lines – Voltage

Fig. 9. Dynamic response for 0.5 s fault duration on lines – Rotor Angle (blue), Active (purple) and Reactive
Power (green)

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217

Fig. 10. Dynamic response for 0.5 s fault duration on line 2 –Voltage

Fig. 11. Dynamic response for 5 s fault duration on lines – Voltage

Fig. 12. Dynamic response for 5 s fault duration on lines – Rotor Angle

D. Voltage Control by Power Factor Correction for N-1 Criterion
In the Table III. The results of voltage development on the BB11 busbar are presented when the power factor
of the synchronous generator is varied. As the generator is operated under different power factor, there is a
change in the active and reactive power production in order to maintain voltage within limits set by EN

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
50160 standards. The results obtained show how the voltage is regulated by power factor correction as the in
the case of 0.8 capacitive power factor voltage magnitude for 93 MW falls below allowed limits, and new
maximum power is determined to be 45 MW. As in the case of 0.8 inductive power factor the voltage goes
beyond upper allowed limit in case when power production of 93 MW, and the new maximum power for
stable operation is found to be 74 MW. In cases when power factor is 0.9 in both capacitive and inductive
mode, the voltage on the critical busbar, as well in the entire network, stays within allowed limits and does
not change significantly for both power of 93 MW and new found power. It can be then concluded that if the
generator operates under power factor of 0.8 in both modes, there is less active power produced, while if it
operates under power factor of 0.9 in both modes, as well as under power factor of 1, the maximum power of
93 MW previously determined satisfy N-1 criterion and offers stable and secure network operation.
Considering results obtained and presented in Table IV., in terms of line and transformer loading, for power
of 93 MW any power factor in either capacitive or inductive mode less than unity, the power of 93 MW will
distort the network operation and stability. Thus, it can be concluded that considering only voltage
constraints the system will be stable for power factor of 0.9 capacitive and inductive, while when line and
transformer loading taken into consideration, there is all cases when power factor less than 1 new maximum
power for unstable and unsecure network operation.

Table 3. Voltage developments for different power factor
Power factor BB11
Line 2 0.8 (45 MW)
Line 2 0.8 (83 MW)
Line 2 0.8 (74 MW)
Line 2 0.8 (93MW)
Line 2 0.9 (73MW)
Line 2 0.9 (93MW)
Line 2 0.9 (89MW)
Line 2 0.9 (93MW)
Line 2 1 (93MW)

CAP
CAP
IND
IND
CAP
CAP
IND
IND
IND

UI,
Magnitude
MV
59,59856
55,44239
72,79612
75,16263
60,93922
60,2638
72,12859
72,52091
67,06188

u, Magnitude
p.u.

U, Angle deg

0,903006
0,840036
1,102971
1,138828
0,923322
0,913088
1,092857
1,098802
1,016089

3,5407772
13,12576
1,038122
2,164138
7,032856
10,3019
3,275636
3,567566
6,509941

Table 4. Line and transformer loading for different power factor
Power Factor
CAP
CAP
IND
IND
CAP
CAP
IND
IND
IND

4.

Line 2 0.8
Line 2 0.8
Line 2 0.8
Line 2 0.8
Line 2 0.9
Line 2 0.9
Line 2 0.9
Line 2 0.9
Line 2 1

Power
45MW
93MW
74MW
93MW
73MW
93MW
89MW
93MW
93MW

Loading [%]
line 2/1
40,80236
167,4764
92,47962
116,5894
98,69827
131,5861
99,38897
104,098
99,53208

Loading [%] Twowinding transformer
74,93822
123,1931
87,84803
98,82892
93,07358
109,3657
93,99311
96,17869
96,96105

Conclusion

Voltage stability is the main problem concerning utilities due to the continuous growth and deregulation. In
this paper, the network with 11 busbars is examined for a transient stability. Transient stability studies deal

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020217
with the effects of large and sudden disturbances that occurs within the network such as it is a fault, the
sudden outage of a line or the sudden removal or application of load. It is very important to do the transient
stability analysis of a system in order to ensure that the system can handle the transient condition which is
followed by a major disturbance. Transient stability and voltage instability analysis done in this research for
the network with high load conditions shows that for a smaller period of fault duration, the system can be
denoted as stable, while in case when the fault duration is somewhat higher than 0.02 seconds, the system is
unstable and not secure in operation being unable to attain the equilibrium state and synchronism considering
all parameters analyzed – voltage development, rotor angle speed, active and reactive power. In cases when
fault duration greater than 0.02 seconds, there is breakdown state appearing in the network after the fault
where the rotor speed is increasing, thus, causing system to go unstable and out of synchronism. Also, during
the fault, there is voltage drop, active power drop and reactive power rise, after which there is an oscillation
which cannot reach equilibrium. When fault duration increased to 0.05 or 0.5 seconds, the system is unstable
only when fault simulated on one line, while when fault duration is increased to 5 seconds, then for every line
examined and analyzed for three-phase symmetrical fault, the system is unstable.

REFERENCES
[1]

Kundur, P. (1994) Power System Stability and Control. USA: McGraw-Hill, Inc.

[2]

Sucena P., J. P. (2007) Redes de Energia Eléctrica: uma análise sistémica. 2ª edição. Lisboa, IST
Press.

[3]

Mania P. (1997) Power System Stability and Control Comparative Analysis. IFAC Control of
Industrial Systems, Belfort, France.

[4]

Lau, Mark A. and Kuruganty, Sastry P. (2010) "A Spreadsheet Illustration of the Transient Stability
Analysis of Power Systems," Spreadsheets in Education (eJSiE): Vol. 3: Iss. 3, Article 6. Available at:
http://epublications.bond.edu.au/ejsie/vol3/iss3/6

[5]

Saric, M., &amp; Penava, I. (2014, May). Transient stability of induction generators in wind farm
applications. In 2014 14th International Conference on Environment and Electrical Engineering (pp.
230-235). IEEE.

[6]

Davidson I. and Mbangula I. (2014) Power System Modelling and Fault Analysis of NamPower’s
330 kV HVAC Transmission Line. Journal of Energy and Power Engineering 8 (pp. 1432-1442).

[7]

Xyngi I., Ishchenko A, Popov M., and van der Sluis L. (2009) Transient Stability Analysis of a
Distribution Network With Distributed Generators. IEEE Transactions on Power Systems, vol. 24, no. 2.

[8]

Diaz-Alzate, A. F., Candelo-Becerra, J. E., &amp; Villa Sierra, J. F. (2019). Transient Stability
Prediction

for Real-Time

Operation by

Thresholds. Energies, 12(5), 838.

Monitoring

the

Relative

Angle

with

Predefined

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transient stability is an important aspect in designing and upgrading electric power system. In&#13;
utility planning, transient stability is studied by numerical simulation. It involves the study of the&#13;
power system following a major disturbance. In order to study Electric Power System transient&#13;
stability, the models to describe their components should be defined. The components are defined&#13;
using the classical model, which is valid to time periods up to 2 seconds. This project contains 11&#13;
busbars, 1 synchronous generator, 3 loads and 8 transformers. This research is done in DIgSILENT&#13;
PowerFactory software for network modeling and simulation by using Stability Analysis Functions&#13;
(RMS) advanced feature. In this paper we are analyses the maximum rated power of distributed&#13;
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                    <text>Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218

Information Systems Project Success Factors: Literature Review

Nermina Durmic
International Burch University, Sarajevo, Bosnia and Herzegovina
nermina.durmic@ibu.edu.ba
Abstract – The purpose of this paper is to identify and collect most commonly discussed project success
factors in the context of information systems (IS) projects. Through the process of review of 88 books,
relevant studies and scientific works 72 success factors were detected, with a total of 689 appearances,
which are then classified into six factor groups: Planning, Project team, Project management,
Development, Customer, Project facilitation. The paper reveals that factors that were recognized as the
most critical ones for the success of information systems projects by majority of authors belong first to
Planning, and then to Project team and Project management groups of factors. Findings in this paper
are expected to serve as a valuable theoretical basis for future empirical research of success and failure
of projects in modern information technologies (IT) organizations, and development of related IS project
success models.
Keywords – Project success, project success factors, information systems, literature review.

1. Introduction

Despite efforts IT organizations are making today to survive and take a lead in the high competitive market,
reports show that project success rates haven’t changed significantly over the past 15 years. Back in 2003, King
[1] reported that in one IT organization three out of ten projects fail on average. In the same year, Lewis [2]
reported that around 70% of all IS projects fail to fulfill the objectives set, where all failed and defectively
completed projects were included. According to Arcidiacono [3], International Data Corporation published in
2009 that 25% of observed projects failed completely, and 50% of projects required rework. Eight years later,
in 2017, PMI [4] performs a study observing “underperforming” organizations with less than 60% of project
completed successfully, meeting their fundamental goals and business purpose. It is reported that 24% of
projects in these organizations were completed within set timeframes, 25% within budget, 33% met original
goals/business intent, 68% experienced scope creep, 24% were a complete failure and 46% of the budget was
lost in case of project failures [4].

Considering the project definition adopted from Pinto and Slevin [5], explaining a project as an organization
of people committed to common goals, involving valuable, high risk tasks of different sizes that have to be
completed by previously set deadlines for a certain budget with high quality, and must have a very well defined
objectives and sufficient resources necessary for task execution undertakings, it becomes clear that project
success depends on many different factors. It’s very important to recognize and understand these factors
because they serve as a guidance for definition of project management processes [6]. While investigation of

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218
project success factors has been a topic of interest for many researchers and authors, there is still a lack of
literature that summarizes findings in this context. This paper is intended to fill in this gap by collecting success
factors in a broad range of relevant material in order to determine which aspects of project development process
should be given the biggest attention to ensure the project success.

After this introduction, a short background of the topic is presented, followed by explanation of the literature
review methodology. Then, outcomes of the literature review process are presented in several segments, with
short conclusion that gives suggestions for future research directions.

2. Background

A.

IS projects

Most of the authors who contributed to the theory of project management by formulating a concrete definition
of a „project“ agree that the definition is always based around five aspects, regardless of the field the project
belongs to. Those are: people, project goals and requirements, project tasks, resources and various conditions.
More specifically, a „project“ is generally defined as a complex organizational system of coordinated activities
being performed in predefined order to achieve desired outcomes, in accordance with time and resource
constraints ([7], [8], [9], [10], [11]).

Information System (IS) projects on the other hand, which are objects of examination in this review, have more
concrete characteristics. IS projects can be described as IT projects designed to answer the information
processing needs of a certain organization. Attributes that make them different from any other non-IS project
are three-fold: (1) they depend heavily on human resources and significant capital that is usually a constraint;
(2) they are people oriented projects and their stakeholder teams are composed of three groups: development
team members, managers, end users; (3) they are conceptual, meaning that IS projects can often be subjects to
risks that come from stakeholder teams, their lack of knowledge or project type [12].

B.

Project success criteria

When it comes to defining the project success, the majority of researchers agree about the general success
criteria: a successful project is a project completed on time, within scope and budget constraints ([13], [14],
[15]). However, the application of this definition in real project environments is usually not that simple.

The empirical research, conducted by Hussein [16], reveals that inadequate definition of the project success
criteria is commonly a result of incomplete understanding of the project itself and setting unrealistic
expectations about the benefits provided by project outcomes. Better understanding of project stakeholders'
inputs, who have the impact on project context and who define the final outcome expectations, is recognized
as the right approach to solving this challenge [16].

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218
According to Frerer et al. [17] review of project success criteria literature, authors like Pinto and Slevin [18],
Freeman and Beale [19], Khosravi and Afshari [20], Bryde and Robinson [21] define even five to nine criteria
for measuring the project success. Collins and Baccarini [22] and Munns and Bjeirmi [7] find that there is a
direct effect of project success towards project management success. Baccarini [13] concludes that there is no
unique definition of project success that could be applied on any project, and that criteria specific for a given
project needs to be defined at its inception point to ensure that all team members and stakeholders work in the
same direction.

3. Methodology

In order to respond to the research goal, it was necessary to review larger amount of literature, thus semisystematic review approach was selected as the most suitable. It helps discover theoretical aspects and teams,
or common issues within a certain research discipline [23]. Books and journals suitable for review were
collected from journal databases and online libraries. To shorten the material collection process search
keywords like “information systems project success”, “project success factors”, “project success criteria” were
used. 88 books, scientific works and articles were collected. Materials with repeating content adopted from
previous literature were not taken in consideration.

The review process was executed through three steps: (1) in the first literature walkthrough list of unique
project success factors was created, 72 of them in total; (2) frequency of appearance of every factor was
registered; (3) factors were grouped into 6 groups for easier interpretation: Planning, Project team, Project
management, Development, Customer, Project facilitation.

4. Literature Review

A.

Project success seminal works

According to Pinto and Prescott [24] critical success factors represent factors that lead to significant
improvement of project implementation chances, if appropriately addressed. Therefore, many researchers have
tried to recognize critical success factors that can be significant for all IS project in general. Leidecker and
Bruno [25] explain these factors as variables or conditions that, if properly maintained, managed or sustained,
can have a crucial impact on the organization success or failure. Definition of critical success factors may also
depend on development of country, type of organization and business [26]. An overview of project success
factors that have been discussed by the authors in previous studies on this topic is presented in the next sections.

First studies in this field have started in early seventies, and in the next 20 years seven seminal works related
to this topic have been created, written by seven different groups of authors. All other works that followed have
considered these seven works as a starting point of their research. Seven seminal works and project success
factors they define as critical ones for project success are listed below:

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218
-

Sayles and Chandler [27]: Capability and knowledge of a project manager, continuing involvement in
execution of project activities, control subsystems, scheduling and time frames, monitoring activities and
feedback provision.

-

Martin [28]: Project and organizational philosophy, project planning, definition of project goals, control
and monitoring mechanisms, top management support, authority delegation and organization, project
team, resource allocation.

-

Cleland and King [29]: Project schedule, project scope, process of task execution, financial support,
logistic requirements, facility support, market intelligence (who is the client), executive development and
training, manpower and organization, acquisition, information and communication channels, project
review.

-

Baker et al. [30]: Project manager, skills and knowledge of the project team, team commitment, project
goals, project planning, budget and cost estimates, monitoring and control techniques, project inception
difficulties, inadequate hierarchy.

-

Lock [31]: Team commitment to project activities, top management support, communication procedures,
progress review meetings, control mechanisms, project manager

-

Morris and Hough [32]: Technical complexity, project goals, project scheduling, budgeting, legal issues,
implementation issues, project idea and innovation.

-

Pinto and Slevin [33]: Client involvement, human resources, monitoring and control, project team lead,
communication, issue handling, technical difficulties, urgency, project politics, environmental impact.

B.

Project success factors

In this section 72 project success factors collected through literature review process and their groupings are
presented. Graph on Figure 1 shows the comparison of number of different success factors contained in every
one of the six factor groups, while graph on Figure 2 shows the frequency of appearance of success factors in
each group in the reviewed literature.

Figure 1. Number of success factors in each group of factors

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218

Figure 2. Frequency of appearance of success factors in literature

Charette [34] claims that IS projects almost never fail for only one or two reasons. According to him the reason
of projects failing is a combination of few factors from the following list: bad estimation of necessary resources,
poorly defined project requirements, unrealistic expectations and project goals, absence of communication
between customers, poor management of users and developers, inadequate technology, lack of a good reporting
of the project status, poor risk management, low quality of project management and development practices,
project complexity. Ewusi-Mensah [12] agrees with him, indicating that the cancelation of IS development
projects is usually caused by few combined factors, such as: project objectives, knowledge and skills of a
project team, monitoring and control, lack of involvement of the top management, project costs and deadlines.
Both authors consider definition of project goals and management as the most significant factors.

Moohebat et al. [26] did an investigation about the country difference impact on project success factors,
considering developed and developing countries. According to their research, the only project success factor,
which is of equal importance for both groups of countries, is the top management support.

Procaccino et al. [35] focus on the project success factors strictly from developers' point of view. They find
that successful project for a developer means a project that is managed the way that ensures that development
team has enough of necessary resources and the least possible amount of distractions when executing their
daily jobs. For them, involvement of the customer in the project execution who is available to give feedback
for the work done, and well defined project scope lead to successful project outcomes [35].

Egorova et al. [36] focus on stakeholders' point of view, dividing them into three groups: strategic-view
stakeholders, operational-view stakeholders and tactic stakeholders. In their work, Egorova et al. [36] state that
both operational and strategic stakeholders place „understanding the customer's problems“ to the first place.
Operational respondents give a special attention to good programming, and strategic respondents see „customer
involvement“ and „completed and accurate requirements“ as more important factors. Tactic stakeholders
choose „very good project management“ as the most important factor for the project success. For both
operational and tactic respondents, „team experience“ plays the essential role. Frese and Sauter [37] divided
reviewed projects into failed, challenged and successful projects groups, aiming to see if there are common
factors affecting project outcomes in all three groups. The conclusion they draw is that the quality of customer
involvement and requirements definition affect the project's final status in all three groups.

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Planning factors

In 95% of reviewed literature the Planning group of factors is discussed as the essential one for the project
success. Project planning, scheduling and control, project requirements and scope, project goal, mission and
vision are recognized as leading success factors in this group by majority of authors. All Planning success
factors are listed in Table 1.

Table 1. Planning group of project success factors
Planning success factors
Project planning, scheduling
and control

Requirement specification
and scope
Definition and understanding
of project goals, mission and
vision
Budgeting – cost estimates
Project/technical complexity
Process and working
procedures
Time estimations
Project organizational
philosophy/ organization
structure
Realistic expectations
Project itself/ project idea
Project strategic fit
Project size
Project pace
TOTAL (max = 88)

Source
[5], [18], [27], [28], [29], [30], [31], [32], [33], [35], [36],
[37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47],
[48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58],
[59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69],
[70], [71], [72], [73], [74]
[11], [12], [18], [20], [26], [34], [35], [36], [37], [38], [39],
[40], [43], [45], [47], [49], [50], [52], [53], [55], [56], [58],
[60], [62], [67], [68], [69], [70], [71], [74], [75], [76], [77],
[78], [79], [80], [81], [82], [83], [84]
[5], [11], [12], [18], [26], [28], [30], [32], [33], [34], [37],
[43], [45], [47], [48], [50], [52], [58], [60], [61], [63], [66],
[67], [68], [69], [72], [74], [75], [76], [77], [81], [83], [85],
[86], [87], [88], [89], [90], [91]
[12], [29], [30], [36], [39], [45], [50], [51], [53], [59], [60],
[62], [64], [67], [68], [69], [71], [73], [74], [78], [81], [89]
[12], [34], [47], [48], [63], [69], [70], [74], [78], [79], [81],
[82], [87], [90], [92]
[6], [34], [35], [49], [64], [66], [67], [68], [69], [70], [74],
[75], [81], [87], [93]
[12], [22], [35], [36], [50], [53], [71], [83], [94]
[6], [12], [28], [29], [38], [57], [59], [73], [95]

[36], [37], [58], [71], [75], [81], [96], [97]
[6], [29], [49], [70], [76], [95]
[6], [26], [38], [60], [75]
[78], [87]
[59], [92]

Freq.
49

%
56%

41

47%

39

44%

22

25%

15

17%

15

17%

10
9

11%
10%

8
6
5
2
1
84

9%
7%
6%
2%
1%
95%

Morisio et al. [45] write that definition of requirements before projects starts or, if not possible, their completion
in the initial phases is a factor of success, which supports the “Glass law” which says that insufficiently defined
requirements are the major reason for project failures. Zouaghi and Laghouag [11] find that clear definition of
needs through requirements is one of three factors that present a high risk for the final result of a project.
According to Kappelman et al. [52], not documenting the functional performance and reliability of
requirements and scope is an early warning sign of IS project failure, which shouldn't be ignored. Definition
of requirements is also stated by Frese and Sauter [37] as a common factor for successful, challenged and failed
projects. Nasir and Sahibuddin [74] rated the clear requirements and specifications factors as the most
important ones among all project success factors.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
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Reel [75] sees project complexity as the basic problem of computing in the context of project development.
Handerson [78] agrees with him, saying that complexity, together with the project size, is the main reason why
large IT projects fail. On the other hand, Nguyen [87] does agree that complexity, from technical perspective,
makes a strong negative effect on project success, but unlike Handerson [78], he rates project size as a factor
that almost doesn't affect the project success. Ogden [76] finds that the project idea is a success factor, but not
a very important one for the project success.

Hirshfield and Lee [96] say that successful projects are ones with realistic expectations and timeframes, and
suggests „planning in advance“ as an activity that should ensure meeting schedule related conditions [96].

Project team factors

As presented in Table 2, 89% of reviewed literature detected Project Team related factors as the most common
success factors in an IS project creation. Role of a project manager, team commitment and communication are
recognized as leading success factors in this group.

Morisio et al. [45] asserts that human factors play a key role in software development. Zouaghi and Laghouag
[11] and Ogden [76] also put the accent on productivity and motivation of the project team and their crossfunctionality.

According to the research study of Wong et al. [54], poor project manager's effectiveness serves as a critical
project failure factor. Manager's capability and skills are recognized by Nguyen [87] and Nasir and Sahibuddin
[74] as a strong positive effect on a project's success. Perkins [98] states that the major cause of project failure
is project manager not having the required knowledge, or not being able to apply it appropriately. While many
researchers share opinion that project manager's field experience is also very important, Kaya et al. [70]
disagree with that. Surprisingly, researchers in only 2% of reviewed literature found that working environment
is a factor that affects the success of an IS project. Unlike Nguyen [87] and Pinto and Slevin [33], Nasir and
Sabihuddin [74] even find environmental influences as completely unsubstantial factor.

Hong et al. [73] suggest that it's important to have a good communication among all related parties including
planners, consumers and developers for establishment of a good project model.

Table 2. Project team group of project success factors
Project team success factors
Project manager

Team commitment

Source
[12], [26], [29], [30], [31], [35], [36], [37], [38], [39],
[42], [43], [47], [49], [50], [52], [54], [55], [57], [70],
[71], [74], [76], [77], [78], [80], [83], [85], [87], [88],
[90], [91], [92], [94], [98], [99]
[6], [11], [26], [27], [28], [30], [32], [31], [33], [35], [37],
[38], [39], [40], [41], [44], [48], [52], [55], [58], [59],
[61], [66], [70], [71], [72], [74], [75], [76], [93], [100]

Freq.
36

%
41%

31

35%

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Communication

Knowledge and skills of
development team
Capability, skills and
experience of a project
manager
Team composition and
assembly
Personal Recruitment/
Ambition
Education and training
availability
Team motivation and
productivity
Losing skilled team
members
Experience of development
team
External consultant
Knowledge sharing
Teamwork and collaboration
Team building
Personal interests
Knowledge application
Working environment
Adding new team members
Access to talented people
Best practices and lessons
learned
TOTAL (max = 88)

31

35%

21

24%

21

24%

11

13%

5

6%

5

6%

4

5%

[45], [52], [54], [75]

4

5%

[12], [36], [47]

3

3%

[49], [69], [76]
[38], [54], [101]
[41], [78]
[12], [47]
[44], [98]
[98], [56]
[33], [87]
[45]
[47]
[75]

3
3
2
2
2
2
2
1
1
1

3%
3%
2%
2%
2%
2%
2%
1%
1%
1%

78

89%

[5], [12], [26], [29], [31], [33], [34], [36], [37], [38], [39],
[43], [47], [48], [52], [53], [56], [60], [61], [63], [66],
[67], [69], [70], [72], [73], [74], [76], [79], [90], [93]
[12], [30], [37], [41], [42], [49], [52], [53], [62], [66],
[67], [68], [69], [70], [72], [74], [78], [81], [82], [87],
[98]
[27], [33], [36], [37], [45], [49], [50], [55], [61], [63],
[66], [67], [68], [69], [70], [72], [74], [81], [82], [95],
[98]
[5], [12], [36], [38], [66], [69], [74], [82], [86], [90], [91]
[12], [30], [41], [60], [77]
[29], [47], [70], [88], [98]
[11], [59], [74], [81]

Project management factors

Project management activities are defined as success factors in 85% of the reviewed literature (Table 3). In this
group, top management support and effective monitoring and reporting are recognized as leading success
factors.

Whittaker [50] avers that inadequate risk management is among biggest IS project failure reasons. As the
organization gets bigger, risk management becomes more significant factor of success. Taylor [51] states that
inability to manage the risk and project related uncertainties has been frequently recognized as a critical
segment of IS project management. Kappelman et al. [52] find the lack of support of top managers as an
extremely important early warning sign of IS project failure, even the most important among other factors.
Nguyen [87] emphasizes that good management in general is essential for a project to succeed, especially
human resources management, quality management and time management.

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Table 3. Project management group of project success factors
Project management
success factors
Top management support

Monitoring and reporting
Change management
Project risk management
Effective leadership
Executive management
support
Quality management
Time pressure
Measurement systems
Authority delegation
Time management
Late failure warning signals
Success criteria Definition
Overtime handling
TOTAL (max = 88)

Source

Freq.

%

[5], [11], [12], [26], [28], [33], [34], [35], [36], [47],
[48], [50], [52], [54], [55], [57], [60], [61], [66], [67],
[68], [69], [70], [72], [73], [74], [78], [81], [91], [92],
[94]
[12], [26], [27], [28], [29], [33], [34], [47], [48], [50],
[55], [56], [59], [60], [63], [64], [65], [67], [68], [69],
[70], [71], [72], [74], [79], [81], [93], [98]
[26], [37], [41], [42], [44], [46], [47], [50], [52], [55],
[56], [61], [64], [67], [69], [71], [74], [75], [79], [89],
[90], [91]
[6], [11], [14], [34], [38], [41], [45], [47], [50], [51],
[55], [59], [67], [74], [78], [80], [92], [101], [102]
[12], [38], [41], [47], [63], [67], [69], [71], [74], [90],
[99], [100], [103]
[12], [37], [44], [58], [71], [83], [97], [100]

31

35%

28

32%

[41], [62], [64], [65], [70], [74]
[33], [34], [75], [76]
[12], [31], [76]
[28], [31]
[39], [78]
[53]
[52]
[45]

22
19

21%

13

15%

8

9%

6
4
3
2
2
1
1
1
75

7%
5%
3%
2%
2%
1%
1%
1%
85%

Development factors

Development related factors are recognized as ones critical for project success in 46% of the reviewed
literature. Technology and tools, together with the availability of adequate resources are recognized as leading
success factors in this group. Yet, many authors agree that success of technical development depends on the
proper project planning phase.

May [53] concludes that projects with inflexible technical architecture and undefined guidelines for managing
the project technical requirements have high risk of failures. According to him the key of success lays in correct
handling of technical aspects of the project. White and Fortune [47] underline that quality of planning must be
taken into account peculiarly to have a successful development phase, and that it's extremely important that
schedule of development activities is realistic.

All detected Development group success factors are listed in Table 4.
Table 4. Development group of project success factors
Development success factors

Source

Technology, tools

[12], [32], [34], [49], [50], [57], [59], [61], [67], [68],
[69], [71], [74], [75], [81], [82], [88], [91], [92]
[28], [34], [37], [47], [49], [53], [65], [66], [67], [71],
[72], [74], [76], [81], [82], [94]

Adequate resources
availability

Freq.

%

19

22%

16

18%

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Development approach
IT infrastructure
Testing, verification and
validation
Programming
Data quality and integrity
Architecture and design
Technical tasks
Interface with other projects
Facility support
TOTAL (max = 88)

[18], [74], [83], [91]
[54], [64], [74], [83]
[26], [54], [79], [80]

4
4
4

5%
5%
5%

[26], [36], [80]
[26], [91]
[53], [80]
[30], [33], [60]
[57]
[29]

3
2
2
2
1
1
40

3%
2%
2%
2%
1%
1%
46%

Customer factors

Customer related group of factors is recognized as an important one for IS project success in 42% of reviewed
literature, having the overall customer involvement as the most critical factor.

Frese and Sauter [37] find that certain level of user involvement is a prevalent factor of project success and
failure. According to Hirshfield and Lee [96] project team with their project manager can be sure their project
meets its goals only if end users are involved in the process. On the contrary, Nasir and Sahibuddin [74] claim
that project champion is not important in project development process at all.
All detected success factors in the Customer group are presented in Table 5.

Table 5. Customer group of project success factors
Customer success factors
Customer involvement
Customer approval
Involvement of project
champion
Inflexible customer
TOTAL (max = 88)

Source
[5], [11], [33], [35], [36], [37], [42], [45], [47], [48], [49],
[52], [54], [59], [60], [61], [66], [67], [68], [69], [71], [72],
[73], [74], [82], [83], [84], [85], [88], [94], [96], [97], [100]
[5], [33], [36], [72]
[26], [49], [58]
[54]

Freq.
33

%
38%

4
3

4%
3%

1
37

1%
42%

Project facilitation factors

Project facilitation factors are recognized as project success factors in 17% of reviewed literature. Although
the most significant literature about project management and project success doesn’t write about
troubleshooting, conflict handling or external influences as project success factors a lot, the 10-factor model of
the project development process defined by Pinto and Slevin [33] lists troubleshooting as its tenth component.
Human error factor is recognized as the success factor by White and Fortune [47] and Levenson [79], but
Attarzadeh and Ow [13] who also discuss human error factors as significant ones for the project success, claim
that the reason for the human error is the cause of bad project management and inability of responsible roles to
convert the theory of project management into practice.

�Journal of Natural Sciences and Engineering, Vol. 2, (2020)
DOI number: 10.14706/JONSAE2020218
All detected success factors in the Project facilitation group are listed in Table 6.

Table 6. Project facilitation group of projects success factors
Project facilitation success
factors
Troubleshooting
Conflict handling
External influences
Human error factor
Tolerance of bad news
Technical difficulties
Start-up difficulties
TOTAL (max = 88)

Source
[5], [26], [33], [48], [70], [72]
[39], [47], [53]
[47], [95], [98]
[47], [79]
[90]
[89]
[30]

Freq.

%

6
3
3
2
1
1
1
15

7%
3%
3%
2%
1%
1%
1%
17%

5. Conclusion

The paper summarizes findings of the review of 88 works that discuss factors that affect the success of IS
projects. While each of 72 detected success factors can play a major role for the outcome of an IS project, the
majority of authors agree that project planning, scheduling and control; requirements and defined project scope;
definition and understanding of project goals, mission and vision; role of a project manager; team commitment;
communication and involvement of customers belong to the most significant ones. On the other hand, technical
difficulties; overtime work; project size and strategy; development team dynamics; overtime handling; project
architecture and design are the least frequent success factors in reviewed literature. Detected factors are
classified into 6 groups, according to the segment of IS project development process these factors may have an
impact on. The outcome shows that Project team group of factors is found to be the most diverse and highly
significant, while Planning group of factors is recognized to be the most significant one for the IS project
success.

During the review process, it is noticed that not a lot of empirical research was conducted on this topic in the
last 10 years, which results in the lack of literature with fresh findings and conclusions published in this period.
This paper provides a foundation for conducting such empirical research as a future research direction, with
two-fold goal: (1) to discover if recent trends in the process of IS project development – like Agile
methodologies, and unpredictable dynamic of software market today, resulted in significant changes in the list
of key project success factors and definition of “project success” overall; (2) to establish a project success
model that can be used as a guidance in the process of IS project development.

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                    <text>Journal of Education and Humanities
Volume 3 (1), pp. 3-17, Summer 2020
Original research paper
ISSN 2566-4638
© International Burch University

https://dx.doi.org/10.14706/JEH2020311

Relationship between thinking styles and
cognitive load: A contextual study of Arab
special learners
Mogbel Aid K Alenizi
Northern Border University
alenizimogbel@gmail.com

Abstract: The current study aims to assess the relationship between
thinking styles and cognitive load of regular students and of the
students with learning difficulties. It also evaluates to what extent
cognitive load is related with patterns of thinking according to
Harrison and Bramson’s theory. Random samples of 105 male and
female regular students’ along with 79 male female students with
learning disabilities were chosen for the study. An interview form
was used to identify the family situation of the samples and the Raven
matrix sequence test was used to determine the intelligence level of
those with learning difficulties. To diagnose the nature of samples’
learning difficulties, Michael Best’s scale was used and to measure
five thinking patterns (synthetic, ideal, pragmatic, analytical, and
realistic) researchers’ self designed tool was used. To measure
cognitive load, a scale prepared by ASRC was used. The results of
the study indicated that those with learning difficulties think random,
i.e. they do not use the five methods of thinking in an organized way
for their academic achievements and in problem solving which
burdens their cognitive faculty. As for regular students, their
thinking was organized, and they used the five methods of thinking
in a regular manner to enhance their academic achievement, which
eventually reduces their cognitive load.

Keywords: Cognitive load;
thinking patterns; Harrison
and Bramson theory; special
learners; learning disability

Article History

Submitted: 13 May 2020
Accepted: 18 June 2020

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

1. INTRODUCTION
It is important for students to acquire scientific knowledge and operations,
thinking skills and problem solving skills, but the common teaching practices in
the educational field pay more attention to memorization, but rarely pay
attention to the mental processes of the learners which eventually is reflected in
learners’ differential levels of educational achievement. Cognition helps us
understand human behavior through the mental processes; it is significant in
learning processes as well because knowledge acquisition goes through several
stages until it stabilizes in the mind (e.g. emotions, awareness, attention and
memory). Due to the limited capacity of the brain, the information stored
determines the nature of its processing. Every individual has his/her own
cognitive capacity to process a mental function, and any disturbance in such
processes cause cognitive load. The educators and teachers should not give
excess information as the increased load of information may hinder the learning
process of the ordinary students, and students with special needs in particular
(Zoghbi, 2012).
Al-Maati (2005) indicated that thinking is a refined cognitive process that
involves re-organization of the elements of a given situation in a noble way that
requires problem solving skill. In other words, it involves many other cognitive
processes such as attention, awareness, remembrance etc., and some cognitive
skills such as classification, conclusion, analysis, installation, comparison,
generalization and so on. There are a number of theoretical perceptions of
thinking styles that differ from one another in terms of individuals’ preference in
their thinking. One such model is the Paivio model (1971), which envisions the
existence of two types of preferences of individuals and their ways of thinking:
verbal thinking and conceptual thinking.
Harrison &amp; Bramson’s (1982) model proposes that the idea of thinking
styles are closely related to the study of educational psychology and cognitive
psychology, as the roots of research in the methods of thinking emerged in the
early seventies of the last century as naming of personal concepts, but the concept
of style is more related to personality (Harrison &amp; Bramson, 2008). For those with
learning difficulties, it is clear that they have difficulties in memorization,
understanding, attention and awareness. They mainly suffer a lack of
understanding and awareness, so those involved in developing curricula should
take into account learners’ low ability of retaining and understanding
information. Saudi Arabia is witnessing an alarming increase in the number of
cases with learning difficulties. As their percentage ranged from 5% to 10% of the
total population, the cognitive load of learners with learning difficulties needs to
be taken care of well, so that the decision-makers could take into account their
low abilities of memorization and understanding (Aburiah 2007). The presentday students need reduced load of knowledge/information during their learning
process in order to use their higher thinking skills which require a lot of
information and extensive mental processes for a successful learning (Mai, 2012)

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�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

Statement of the problem
The cognitive load theory is related to facilitating the processing of
information in working memory with a lot of efforts (Sweller et al, 1998).
Memory, with its coding, storing, and retrieval of information, is the basis for
most of thinking and learning. Discrimination and recognition processes also
depend on memory, so that the individual can perform several mental processes
through the information stored in the memory (Abboud &amp; Jassem, 2011).
The cognitive load is concerned with the way in which knowledge
resources are used during the process of learning and problem solving (Shehab,
2011). Thus, thinking styles are influenced by the nature of the subject (the
internal cognitive load) or the way in which students demonstrate the required
information and activities (the external cognitive load) (Sweller, et al., 1998).
Therefore, educational materials should be designed to keep learners' cognitive
load at its lowest level during the learning process (Stachel, 2011). Each learner
has a preferred style of processing information, which is also known as learning
method. Therefore, the level of cognitive load during the learning process may be
affected by the learner's preferred learning method or his/her method of
processing the information presented to him. The cognitive load theory is based
on cognitive structure consisting of partially independent processing operations
for visual / spatial verbal and auditory information that interact with long-term
memory (Pass, et al., 2003). From the above it is clear that the excessive cognitive
load negatively affects the styles of thinking. The level of cognitive load can be
reduced by finding effective ways to present information to the learners.
Learning methods can explain the differences among learners and in terms of the
ways they process information. Given the paucity of studies in Arabic context,
the present study explores thinking styles in the light of Harrison and Bramson's
theory and its relationship to the cognitive load of ordinary students and those
with learning difficulties, by answering the following two questions:
Is there a relationship among the styles of thinking (synthetic, idealistic,
pragmatic, analytical and realistic)?
Is there any relationship between thinking style and cognitive load of the
learners?
Objectives of the study
The study has following objectives:
a. What are the patterns and levels of cognitive load between the students with
learning difficulties and regular students?
b. How Harrison and Bramson's theory accounts for this difference?
Theoretical Background
The cognitive load theory has recently become one of the crucial theories to
describe cognitive processes involved in learning using multimedia or internetbased learning (Brunken, et al, 2003, p. 53). Pass et al (2003, p.1) refers to cognitive
load theory as a framework for research on cognitive processes and educational
design. Allen (2011, p. 11) suggests that cognitive load theory assumes that an

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individual allocate part of his mental processes in order to process or learn a
bundle of information. To perform a task, the amount of knowledge resources
needed requires processing of memory, which eventually loads the cognitive
efficiency (Huang et al, 2006, p. 141; Yao, 2006; Curie, 2008). The idea of cognitive
load theory is based on the premises that working memory has a very limited
capacity and learning process needs active working memory. If the working
memory capacity exceeds the maximum limit, then the learning becomes
ineffective. It assumes that long-term memory has unlimited capacity. Increased
levels of cognitive load may result from the content of educational materials,
problem solving skill in learning using traditional methods (Abu Riyash, 2007, p.
196). Therefore, there should be variation in the content to suit various learning
methods (Sweller, 2008).
Adnan Yousef Al-Atoum (2004) sees that each individual has his/her own
way of thinking, and the way of thinking measures individuals' linguistic and
cognitive preferences and their levels of flexibility in their work and in their
dealing with others; though there are different approaches to the understanding
of thinking style in terms of types and nature of the methods followed by
individuals in their thinking processes. For instance, the Paivio model (1971)
envisions two types of individuals' preferences; verbal reasoning and conceptual
way of thinking. Harrison and Bramson referred to the individual’s preferred
methods of dealing with different life situations, and these methods include the
scale of thinking as prepared by Harrison and Bramson (Magdy Abdel Karim
Habib 2008, p. 5-11). It includes the following methods: A. Synthetic thinking
means the individual’s ability to communicate new and original ideas is
completely different from what others do in synthesizing various ideas. In this
process, an individual looks for views that may provide better equipped
solutions, and link seemingly opposing views. It requires clarity and creativity.
B. Idealistic thinking is the individual's ability to form different points of view
towards goals and to pay attention to the needs of what is beneficial for him and
the society. It focuses on social values. C. Pragmatic thinking is the individual's
ability to verify what is right and wrong in terms of personal experience and
freedom to experiment and excel in finding new ways of doing things using the
available resources. D. Analytic thinking is the individual's ability to confront
problems carefully and in a systematic way, pay attention to detail and plan
carefully before making a decision, and collects as much information as possible
while not forming a holistic view (Anwar Omar Ibrahim, 2007, p. 18). E. Realistic
thinking includes reliance on observation and experimentation of the real life
things or events.
2. REVIEW OF RELATED LITERATURE
Cognitive Load:
Working memory (WM, hereafter) regulates the efficient use of cognitive
resources (Mayer &amp; Moreno, 2003), and there are other factors too such as

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�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

individual traits and knowledge repository, as well as fresh information related
to a specific task (Wouters, Paas, &amp; van Merriënboer, 2009). Individuals with
greater WM capacity have more attentional capacity to devote to complex tasks;
thus, an individual with high WM may experience less cognitive load (i.e., find
the task less difficult) than an individual with low WM. The established
relationships between WM and performance on complex tasks (Geary, Frensch,
&amp; Wiley, 1993; Linderholm &amp; van den Broek, 2002; Schelble et al., 2012), and
between cognitive load and complex task performance (Beilock &amp; DeCaro, 2007;
Paas et al., 2003) support this idea. Thus, individuals with fewer attentional
resources (i.e., lower WM) are likely to perceive a complex task as requiring more
mental effort than those who possess more attentional resources. Given the
impacts of cognitive load and WM on complex tasks and the similarity of the
demands of creative thinking tasks to other complex tasks (Beaty &amp; Silvia, 2012;
Benedek et al., 2012; Benedek et al., 2014; Nusbaum &amp; Silvia, 2011; Lee &amp;
Therriault, 2013; Silvia, 2015), links among WM, cognitive load, and creative
thinking are likely.
Flad (2002) conducted a study aimed at identifying the effect of increasing
cognitive load in the standards of self-report and bilateral tasks of mental effort
in the problem solving process. The results of the study indicated that there was
a positive and statistically significant relationship between the cognitive load and
the difficulty of the task. Likewise, Farnsworth (2009) conducted a study aimed
at identifying differences in the Cognitive load as perceived by teachers in
training manual or electronic assistive technology to teach reading and writing
to the blind. The results of the study showed that there were no statistically
significant differences between the groups of technological devices in
quantitative measures of cognitive load or the efficiency of the Braille method in
learning to read and write. While the results of the interviews indicated that there
were qualitative differences in the required mental effort (cognitive load)
between the groups of technological devices.
Abdul Amir Aboud and Mahdi Jassem (2011) conducted a study aimed at
identifying the level of cognitive load among middle school students, and
identified the differences between males and females from arts and science
specializations. The results indicated a decrease in the level of cognitive load
among the sample members in general, but there were no statistically significant
differences in terms of gender and specializations. The results also indicated that
there were no statistically significant differences in the level of cognitive load in
terms of areas of study. Abu Joudeh (2004) aimed to know the effect of an
educational program based on the theory of cognitive load in developing critical
thinking skills. Statistical indication of the California test of critical thinking skills
as a whole and of each skill reflected the effectiveness of the educational learning
program based on cognitive load theory in developing critical thinking. AlShamsi and Hassan Study (2009) aimed at knowing the cognitive load of middle
school students in Baghdad, and concluded that there were statistically
significant differences in their possession of a low ability to high ability tasks.

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The study also concluded that there were no statistically significant differences
in terms of their gender and specializations.
Thinking Styles:
Fouqia Abdel-Fattah (2007) explored the relationship between thinking styles
and moral judgments, and revealed that there were differences between the
prevailing thinking methods among the academic staff, as per their styles and
specializations. The results indicated that there were statistically significant
differences between the averages of male and female. Ideal thinking style was in
favor of females, and analytical thinking style was relatively in favor of scientific
specializations. Al-Sukari and Abdul-Fattah (2006) studied emotional
intelligence and its relationship to thinking styles among a sample of university
students. The study revealed that there was statistically significant positive
relationship between emotional intelligence and ideal and analytical thinking
styles, but statistically significant negative relationship between Pragmatic
thinking styles. There was a statistically significant relationship with the rest of
the thinking styles. Zhang, Li-Fang (2001) showed the relationship between
thinking styles and personality patterns.
3. RESEARCH METHODOLOGY
The research sample included a group of regular students and students with
learning difficulties who were randomly selected from some primary schools in
the northern border region of Rafha, Saudi Arabia. A total of 105 regular students
included 60 males and 45 females. A total of 79 learners with learning difficulties
included 56 males and 23 females. The study was conducted in the second
semester of academic year 2019-2020. The method used in the current study was
descriptive in nature. Pearson correlation coefficient was used to measure
thinking styles and cognitive load of the students with learning difficulties. The
same was used for the regular students as well.
Hypotheses:
The hypotheses formulated are as follow:
H01 = There is no statistically significant correlation between the scale of thinking
styles and the measure of cognitive load among students with learning
difficulties.
H2 = There is a statistically significant correlation between the scale of thinking
styles and the measure of cognitive load among ordinary students.
Study tools:
Family Diagnostic Interview Form: The aim of the questionnaire was to
identify the economic, social and cultural levels due to the important role of these
levels in influencing research variables.

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�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

Raven Colored Sequential Matrices (Takaneen, Emad Ahmad Hassan,
2014): Its goal was to measure intelligence, and it was largely free of cultural
influence. It mainly depended on the collective application. It could be applied
individually in certain circumstances. Successive matrices consisted of 36 items
distributed in three sections: (a), (a) b, and (b), and colored matrices were suitable
for ages from 5.6 to 10.5 years, and were suitable for those who had disabilities.
Colors were used as the background to the problems, to make the test more
interesting and clear.
Psychometric properties of the test:
Stability of the test: The coefficient of persistence in the study sample
ranged from male and female students to repeat the test after two weeks to the
stability factor of (0.85), and p-value at the level of (0.01).
Validity of the test: Formative validity was used, where the correlation
coefficient was estimated by months between the total grades (0.77) in the first
application of the test, while the correlation coefficient was (0.81) in the second
application.
A student’s behavior scale (Best and Sharif, 2007) was used to assess the
nature of learning difficulties of the samples. This scale is one of the survey tools
for the detection and initial recognition of learning difficulties through the
teacher’s assessment of the verbal and non-verbal behavioral features. Verbal
measure includes assimilation and language whereas non-verbal measures
include general knowledge, motor coordination, personal and social behavior.
This scale was valid for individual application in the age group of 5.5 - 14 years,
and it consisted of 24 questions sets distributed on two scales; 13 questions sets
for the verbal scale and 11 for the non-verbal measure. Under each paragraph
five graded questions (1, 2, 3, 4, 5………………) were given wherein each grade
represented the level of teacher’s assessment of the student's ability. The score
ranged from 24 to 120. The score was interpreted on the basis that each regular
student got a score of minimum 48 and students with learning difficulty got
lesser than that.
The psychometric properties of the scale
Honesty: Michael Best (1981) codified the scale to assess the significance
of honesty of the sample, whereby the validity of the scale for gender variable
was * 17.32 and the status of learner variable (normal students, and students with
learning difficulties) was 98. 28*. The confidence interval was found to be 0.38 –
2.25. To measure thinking styles within the framework of Harrison and
Bramson's theory, the researcher adopted the following five thinking styles:
synthetic, ideal, pragmatic, analytical, realistic. These five styles represented a
reference framework and thus the researcher validated that in that case the
content of the scale was able to achieve the set out goals. The researcher had the
following procedures in building the scale:

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The content of the questions sets was well defined. The questions sets
were developed in the light of Harrison and Bramson's theory. The total number
of question sets (25) was divided into five dimensions; each dimension was
having five questions sets as distributed in table 1 below:
Table 1. Distribution of questions and questions sets thinking style-wise
Dimensions
Order of questions
No. of question sets
Realist

1-2-3-4-5

5

Synthesist
Pragmatist
Analyst

6-7-8-9-10
11-12-13-14-15
16-17-18-19-20

5
5
5

Idealist

21-22-23-24-25

5

Psychometric properties of the scale: To ensure statistical validity, it was applied
to a sample of 25 students, and the following equation was applied to the results.
(Z = 2) = Seronov - Colmogrov = to know the nature of the distribution of data
(normal or not).
The significance level of 0.01 meant that the distribution was not normal.
Since the distribution was not normal, laboratory tests were not applied to the
data, rather non-parametric tests were applied to data (Mann-Whitney's test for
calculating terminal honesty). The results are as shown in the following table 2:
Table 2. Results of psychometric properties of the scale test
Gr. N Total
Avg.
Z value
Sig.
St. sig.
score
score
level
Max 8
100
12.5
3.393
0.001
Sig.
Min 8
36
4.5

The table above shows that the value of the significance level is 0.001, which is
statistically significant, because it is less than 0.05. This indicates that there are
differences between the maximum and minimum. This means that the tool has
terminal honesty.
Internal consistency validity: To extract this type of validity, correlation
coefficients were found between the five styles and the results as shown in Table
3 below:
Table 3. Correlation coefficients between the five thinking styles
Correlation
Syn.
Ideal.
Prag.
Analy.
Real.
Factors
Synthesist
1
**-.202
*-0.10
**-0.347
**-0.297
Idealist
1
**-0.307
**-0.191
**-0.272
Pragmatist
1
**-0.272
**-0.161
Analyst
1
*-0.11

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�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

Realist

1

It is clear from table 3 that there is a negative correlation with a function at the
level of 0.01, but it is very weak among the five thinking styles. The negative
correlation between one group (structural and pragmatic) and the other one
(analytical and realistic) is at the level of 0.05. It is indicated that negative
correlations are quite higher at the top level factors, but it decreases over the
downward factors. The results confirm the validity of the scale because the styles
are distinct and are independent of one another.
Stability of scale:
The stability was determined by the following two styles: Mid
fragmentation, Alpha-Cronbach equation
The value of each of them is as shown in the table 4 below:
Stability
type
NA

Table 4. Stability of scale test results
SpearmanSig.
AlphaSignificance
Brown
level
Cronbach
level
coefficient
0.78
0.001
0.73
0.003

It is clear from the table that the stability coefficients have relatively high values
that allow the tool to be applied safely, and with this form of honesty and
reliability the tool has become valid. The cognitive load scale as prepared by the
American Space Agency Research Center (ASARC), was further translated and
codified by Al-Banna (2008). The researcher assessed the cognitive load and its
relationship to the styles of thinking of ordinary students and of those with
learning difficulties, on the task load index of the National Aeronautics Space
Administration (NASA), which allows measuring the total workload by itself
during the completion of the task or immediately after it. It consists of six
dimensions; each of them constitutes a source of the total workload represented
in defined requirements such as physical requirements, time requirements,
performance, effort, and frustration. It also consists of a scale sheet assessing the
degree to which the scale dimensions contribute to the overall load. The scale
included a description of the five dimensions and instructing the student to place
a mark (x) on the intersection of eleven gradients with the horizontal line under
each question and make sure to place a mark (x) on one of the gradient lines and
not between the gradient marks. The total load is calculated by dividing the total
cognitive load of the six measures divided by 15 which is the number of possible
statistics between each pair of measures. The study found that there is a high
degree of honesty, as the correlation coefficient is 0.52 between the scale of
thinking styles and the cognitive load (Al-Banna, 2007). Al-Banna (2007) verified
the stability of the scale by the Alpha Cronbach method with a value of (0.77). It

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is clear from the above that the scale enjoyed a good degree of honesty in many
studies and therefore it was used in the current study as well.
Research procedures:
The researcher followed the following steps in carrying out the research
as follows:
A questionnaire was applied to identify the economic and social status of the
sample so as to ensure that these conditions did not affect the study variables.
The scale of thinking styles and cognitive load was applied to 105 ordinary
students in some government primary schools in the northern border region of
Rafha, to determine the mental requirements of their preferred methods of
thinking.
The questionnaire of methods of thinking and the cognitive load was
applied to 79 students with learning difficulties from some government primary
schools in the northern border region in Rafha. The procedures for diagnosing
learning difficulties carried out in two stages: first, application of Raven's
successive matrix test to determine the level of intelligence of the sample, which
measures non-verbal intelligence, and was largely free from any cultural
influence, second, using the Michael Best scale to diagnose and identify people
with learning disabilities. The researcher used statistical methods to know the
effect of the five thinking methods (syntactic, idealistic, pragmatic, analytical and
realist) on the cognitive load of students with learning difficulties and of regular
students as well.
4. RESULTS &amp; DISCUSSION
The First hypothesis:
1. There is no statistically significant correlation between the scale of different
styles of thinking (synthesist, idealist, pragmatist, analyst, and realist) and cognitive
load among students with learning difficulties. Pearson correlation coefficient
was used to measure the relationship between thinking styles and cognitive load
of the students with learning difficulties. The results of the Pearson correlation
coefficient are given in table 5 below:
Table 5. Pearson correlation coefficient result of students with learning difficulties
Thinking
Total degree of cognitive
Styles
load
Synthesist
0.004
Idealist
0.005
Pragmatist
0.006
Analyst
0.003
Realist
0.008
) -(there is no correlation

12

Indication
*---*----*--------*
----*

�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

It is clear from table 5 that there is no correlation between the thinking styles and
the cognitive load of people with learning difficulties. This means that they have
random thinking, that is, they use the five thinking styles in a random,
disorganized manner, and this also indicates that the sample suffers from this
weakness due to, to the fact that students do not use sound mental awareness in
their academic achievement, which increases their cognitive load.
The second hypothesis:
There is a statistically significant correlation between thinking styles and
cognitive load among ordinary students. The results of the Pearson correlation
coefficient are given in table 6 below.
Table 6. Pearson correlation coefficient result of regular students
Thinking
Total degree of Cognitive load
methods
Synthesist
0.238
Idealist
0.235
Pragmatist
0.240
Analyst
0.236
Realist
0.237
(**)(t) is at 0.01

Indication
**
**
**
**
**

It is clear from table 6 that there is a correlation between thinking styles and
cognitive load of regular students. This strong relationship means that thinking
is organized for them, that is, they use the five methods of thinking in an
organized way. This indicates that the sample has the ability to use the five
thinking methods in their academic achievement and in solving their problems.
This may be due to the fact that students use mental perceptions in a proper way
in their academic achievement in their efforts to use their ability to organize the
curriculum content and reduce their cognitive load.
Psychologists and educational researchers believe that explicit
instructions are necessary for the learners to do the best what is expected of them
(Klahr &amp; Nigam, 2004; Mayer, 2004), and they have provided empirical support
to their claims. Research has clearly shown that for novices (almost all), explicit
instruction is more effective than partial guidance (Clark, Kirschner, &amp; Sweller,
2012). Zhang (2002) found that students with higher cognitive development level
tended to use a wide range of thinking styles than the students with lower
cognitive development. The results of the present study suggest similar patterns
wherein normal students follow a regular pattern in terms of thinking styles
during a cognitive function, whereas the students with learning disabilities
exhibit a random pattern. Thinking styles vary among the regular students
exhibit a particular style of thinking (study based on Sternberg’s theory of selfgovernment) under the dimensions of functions, forms, levels, scope and
learning (Thomas &amp; John, 2019). They observed differences in preferences of

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thinking styles in terms of gender, but the present study exhibited contrary
results. Thomas and John’s (2019) study helped the learners’ self-efficiency to
gain a sense of self-efficiency, and also helped the teachers to better realize
students’ strengths and weaknesses to take necessary steps to compensate for
their limitations. Cheng (2019) also proposed similar results that qualitative
conception of learning was significantly related with a wide range of thinking
styles among the students with hearing impairments. Likewise, this present
study found a direct relation between thinking styles and learners’ cognitive
load. Overloaded working memory during various learning processes cause
learning impairments in normal cases as well (Kalyuga, 2015, 2016; Sweller,
2011). Therefore, it is imperative to note that the students with learning
difficulties do suffer cognitive burden in their learning processes if the content
and the teaching strategies are not considered well (Likourezos et al, 2019).
5. CONCLUSION &amp; RECOMMENDATIONS
In conclusion, the researcher presents a set of recommendations which is
expected to lead the development of educational work by reducing the cognitive
load by using thinking styles that encourage creativity. The recommendations
are:
1. Teachers should be encouraged to diversify their teaching methods to suit
learners’ thinking patterns.
2. Agencies and institutions concerned with students with learning difficulties
should provide them with educational programs appropriate for the learners,
such as the Learning Resource Room (LRC), because this would reduce the
severity of the difficulty of the student, and trained and qualified staff should
follow-up well to deal with the cases of learning difficulties.
3. Attention should be paid to students' preferred methods of thinking, especially
those with learning difficulties, and taking this into consideration while framing
educational curricula and designing educational activities that may stimulate
creativity and innovation.
4. Appropriate attention should be given to school activities that encourage
creativity, and improvise methods of thinking that encourage creativity.
5. Establishing educational programs and holding workshops and seminars
dealing with explaining the types of thinking and their roles in educational
process; these will eventually help in reducing the cognitive load of the students
with learning difficulties and of regular students as well.
6. Further studies should be carried out to assess the dominant thinking styles
among the special learners in the variety of learning tasks so that better
arrangement of subject content and their delivery can be sequenced well.

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�Relationship between thinking styles and cognitive load:
A contextual study of Arab special learners
Mogbel Aid K Alenizi

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17

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                    <text>Journal of Education and Humanities
Volume 3 (1), pp. 18-29, Summer 2020
Original research paper
ISSN 2566-4638
© International Burch University

https://dx.doi.org/10.14706/JEH2020312

An observation on the introduction of mobile
messenger apps for collaborative online tasks
in post-secondary education
Robert Schrenk
University of Applied Sciences Eisenstadt
robert@schrenk.cc

Abstract: Positive effects of cooperative and collaborative learning
have been investigated by a large number of studies. When using
cooperative learning in blended or online learning the use of online
forums is a popular means to organize the cooperation between
learners in order to assist the learning process besides the lessons in
presence.
In the last years the introduction of instant messengers like
WhatsApp, Facebook Messenger and such were becoming more
popular and enjoy the reputation to be easier to use as they run on
mobile phones and are always at hand. It can be expected that
students behave differently depending on the device and
communication tool that they use. Consequently, this would have an
impact on the learning outcomes. Recent researchers claim a
negative impact of the use of mobile phones on the students’ grade
point average (GPA).
Within this article cooperative online assignments were used as
instruments to compare the use of an instant messenger compared to
communication using traditional online forums. The results show a
significant impact on the length of contributions within the
cooperative tasks and a significant impact on the working times of
the learners. The GPA of learners was not significantly influenced.

Keywords:
Cooperative/collaborative
learning; distance education
and telelearning; postsecondary education;
teaching/learning strategies
Article History
Submitted: 1 January 2020
Accepted: 22 June 2020

�An observation on the introduction of mobile messenger apps for collaborative online tasks in
post-secondary education
Robert Schrenk

1. INTRODUCTION
The positive effects of cooperative and collaborative learning on several aspects
of learning have been investigated by a large number of studies (Rahman et al.,
2020; Casey &amp; Fernandez-Rio, 2019; Delić &amp; Bećirović, 2016; Bećirović &amp; Akbarov,
2015; Sharan, 2014). Higher learning outcomes can be achieved in settings of
small groups rather than a single person working. The terms cooperative and
collaborative learning are often used synonymously although there is a different
meaning (van Leeuwen &amp; Janssen, 2019). Within this article the abbreviation CL
stands for collaborative learning. This means that the learners need a “mutual
engagement of participants in a coordinated effort to solve the problem together”
(Roschelle &amp; Teasley, 1995, p. 70).
In order to facilitate collaborative assignments, the use of discussion
forums is very popular. These are seen as the traditional form of communication
in online courses at universities (Bećirović &amp; Brdarević-Čeljo, 2018) or in Massive
Open Online Courses (Srba, Savic, Bielikova, Ivanovic, &amp; Pautasso, 2019).
Some researchers experiment with other tools as an alternative to
discussion forums like chatrooms, social networking sites or community
question answering systems (Jeff, Stephen, Huang, &amp; Indy, 2010; Moorthy et al.,
2019; Srba et al., 2019) and as a very new kind of implementation the use of
instant messengers, like WhatsApp, for the purpose of teachers’ guidance
(Raiman, Antbring, &amp; Mahmood, 2017). Especially the possibility to introduce
seamless learning scenarios seems promising and allows the creation of
collaborative learning outcomes without dependence on location or time
(Schmid &amp; Schrenk, 2017).
Although the introduction of such tools seems very appealing, current
research has showed a negative impact of social networking sites on the academic
achievement. A significant negative correlation seems to be present between the
frequency of the students’ use of Facebook or the Internet per day for
entertainment and their GPA (grade point average) (Feng, Wong, Wong, &amp;
Hossain, 2019).
Whereas discussion forums, social networking sites and such are mainly
used on personal computers, instant messengers are dedicated to be used on
mobile devices like smartphones and tablets. Mobile devices are always at hand
and are used very frequently by their users. Therefore, it seems very promising
that learners may contribute more frequently and accurately within a
collaborative learning process (Bećirović, Brdarević-Čeljo &amp; Zavrl, 2018).
Research revealed that within a group of 118 college students more than 57% of
messages were answered within less than one minute and 79% of messages were
answered within an hour (Rosenfeld, Sina, Sarne, Avidov, &amp; Kraus, 2018).
On the other hand, the use of mobile devices may affect the contribution
in a negative way. Research analyzing the impact of the use of mobile devices
compared to desktop/laptop computers on the contribution of people in surveys
revealed that mobile device users needed more time for their contributions and
were more likely to interrupt tasks (Liebe, Glenk, Oehlmann, &amp; Meyerhoff, 2015).

19

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

Furthermore, there is a negative correlation between the frequency students used
Facebook or the Internet per day for entertainment and their GPA (Feng et al.,
2019). Interestingly, according to the statistics of Rosenfeld et al. (2018) more than
90% of instant messages were sent between 8am and 12pm.
Thus, the research question of this work is: which impact has the use of an
instant messenger on the length of messages, grades and times of contribution
compared to discussion forums? The study is guided by the following
hypotheses:
H1: there will be a statistically significant difference between the use of an instant
messenger in comparison to a discussion forum regarding the length of
messages.
H2: there will be a statistically significant correlation between the use of an
instant messenger in comparison to a discussion forum regarding the students’
GPA.
H3: there will be a statistically significant difference between the use of an instant
messenger in comparison to a discussion forum regarding the times of
contribution.
2. METHODOLOGY
For this study students’ communication behavior was observed during a blended
learning course that implemented cooperative learning scenarios. “Observation
allows the description of behavior as it occurs naturally” (McMillan, 2012, p. 164)
and “puts you where the action is and lets you collect data” (Bernard, 2006, p.
344). According to Bernard (2006, p. 356) “participant observation makes it
possible to collect quantitative survey data”.
The quasi experiment as other possible method was considered but
discarded. Within an experiment the researcher treats a specific group in a
planned way and compares the results to another, untreated group (McMillan,
2012). For this study this approach was not applicable. All participants had to
pass all activities using all types of media to pass the course. Therefore, splitting
into two groups was no option and the “single-group posttest-only design”
seemed to weak as an option (McMillan, 2012).
In quantitative research an observation focuses on particular aspects of
behavior and quantifies it in some way. The “researcher strives to be as objective
as possible” (Leedy &amp; Ormrod, 2005, p. 180). According to McMillan (2012) this
is a “low-inference observation”. In this observation only quantitative data is
collected automatically and does not need to be interpreted during the collection.
The only possible influence of the observer in this study is, that the contributions
were graded during the observation. But as grading and giving feedback is a
normal part of the learning process the effects to the data are considered to be
minimal.

20

�An observation on the introduction of mobile messenger apps for collaborative online tasks in
post-secondary education
Robert Schrenk

2.1. PARTICIPANTS
This research took place as part of a lecture about “basics of e-Learning” in the
master degree program “Applied Knowledge Management” at the University of
Applied Sciences in Burgenland (Austria) in the summer semester 2019. In that
lecture, the students learned about e-Learning principles and trends that include
the topic mobile learning and collaborative learning.
All participants were obligated to execute all tasks to pass the course. As
the overall learning outcome of this lecture, the students had to collaboratively
design a collaborative online course for a given topic. Before that, they had to
undergo two collaborative online tasks themselves to gain experience and
practice on collaborative online learning. Based on these two collaborative tasks
their communication behavior was analyzed.
2.2. DATA COLLECTION TOOLS AND PROCESS
During the first lecture, students were informed that the two collaborative tasks
will be observed for a reflection and analysis. In order to minimize possible
influence on the communication behavior, they were not informed in detail about
hypotheses or research questions.
For the purpose of this research a special kind of instant messenger, called
“eduMessenger”, was used. This messenger connects to the learning
management system Moodle, that was used for the discussion forums, and stores
all messages using the very same discussion forums in Moodle. That way all
meta-information related to messages was at hand for the analysis. The main
differences between the two types of media was, that the students using the
messenger were informed about new messages via push notifications on mobile
devices, while the other group was informed via email notifications on the
computer. Contributions to the discussion should have been made on the
particular device.
As a consequence, the learners using the messenger had to answer on their
mobile phones, while the others answered using their computers and a regular
keyboard. During the learning process all contributions of the students were
constantly graded and feedback was given to propagate their contribution. At
the end of the course all students were asked to take part in a short survey, to
reflect upon their attitudes towards the used media and lessons learned. At that
stage, they were informed about the purpose of the study and were given a
possibility to opt-out from the study. After the survey was finished, all contents
of the Moodle-forums were exported, the contributions were anonymized and
analyzed. The contributions of those students who did not give their consent to
be part of the study were removed.
Out of the 33 students, who participated the course, 32 finished the
questionnaire and 29 agreed to include their data into the analysis, only 3
disagreed. One participant dropped out during the course and was not able to
take part in the questionnaire at all. These data were removed too.

21

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

2.3. DESIGN OF THE COLLABORATIVE TASKS
The students were split into 8 groups. Each group consisted of 4-5 students.
In the first task [T1] the students had to discuss the pros and cons of collaborative
online tasks based on literature that was given to them. Each group was asked to
agree upon the most important three pros and cons as the outcome of the task,
but for the grading only the quality of each single message was considered
according to the criteria (1) number of contributed pros/cons and (2) if
arguments were based on literature. For each message the students could be
awarded 5 points, and 10 points as maximum for the whole task. The students
had a time range of 14 days for discussion and providing an outcome.
In the second task the students had to develop an own collaborative task
[T2a], and provided feedback to at least two colleagues [T2b]. The feedbacks
ought to contain (1) if the designed tasks engage collaboration among learners,
(2) all aspects of Salmon’s eTivity-concept (Salmon, 2002) were fulfilled and (3)
additional hints were given. T2a was awarded 10 points at maximum, in T2b each
feedback could be graded with 5 points. T2 in total had a maximum of 20 points.
The feedback had to be done within a time range of 21 days.
In both tasks the students had the choice to contribute with few high
quality posts or with a higher amount of posts with minor quality.
By design the students were asked to use a certain type of media for a certain
task.
Groups
1-4
5-8

Table 1 Disposition of groups, tasks and type of media
T1
T2a
eduMessenger
Free choice
Forum
Free choice

T2b
Forum
eduMessenger

The purpose of this was to give all the students the opportunity to use a
messenger and a discussion forum at least once during the course.
For each task a dedicated discussion forum was provided and the groups were
separated using the ”separated groups”-feature in Moodle. This means that the
groups could not see the other groups nor their process. Consequently, an
influence between the groups was prohibited.
Unfortunately, many students did not follow the guidelines and used both
media types within all tasks. Whatever seemed more appropriate for them in a
particular situation was used.

22

�An observation on the introduction of mobile messenger apps for collaborative online tasks in
post-secondary education
Robert Schrenk

3. FINDINGS
3.1. H1: LENGTH OF MESSAGES
H1: there will be a statistically significant difference between the use of an instant
messenger in comparison to a discussion forum regarding the length of
messages.
Figure 1 shows the average length of messages of forum posts compared
to messenger posts. Posts contributed using the messenger seem to be shorter
than those contributed using the forum.

Figure 1: MediaType and lengths of contributions

An independent samples t-test was conducted to compare the length for
messages created by the messenger or the forum.
Table 2 T-test of MediaType on length of contribution
Independent Samples Test
Levene's Test for
Equality of
Variances

length

Equal
variances
assumed

t-test for Equality of Means

F

Sig.

t

df

Sig. (2tailed)

Mean
Difference

Std. Error
Difference

22,439

,000

4,799

346

,000

555,011

115,643

23

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

Equal
variances not
assumed

5,132

336,311

,000

555,011

108,152

The t-test shows a significant difference in the lengths of contribution for
forum (M = 1143.66, SD = 1241.68) and eduMessenger (M = 588.65, SD 768.268);
t(346) = 4,799, p = 0.000.
3.2. H2: IMPACT ON GPA
H2: there will be a statistically significant correlation between the use of an
instant messenger in comparison to a discussion forum regarding the students’
GPA.
As mentioned in section 3.3, students mixed both types of communication
for a natural use of their communication channels and did not follow the
guideline to use the predetermined type of media for one assignment, and the
other type of media for the other assignment. Consequently, it was not possible
to analyze the effect on the GPA by a comparison of the two assignments.
Therefore, a new variable “MediaTypeRatio” [MTR] was introduced to
determine a correlation between the MTR and GPA. MTR indicates the amount
of posts written using the messenger as a percentage of the amount of posts
written using the forum. If, as proposed by H2, the use of an instant messenger
has a negative impact on the GPA there must be a correlation of this ratio
compared to the graded results.
Both assignments had a cap of 30 points as maximum. Because of that cap,
the correlation was tested with and without a cap of 30 points.

MTR

Table 3 Correlation between MTR and GPA
MTR GPA without cap
Pearson Correlation
1
-,007
Sig. (2-tailed)
,969
N
29
29
**. Correlation is significant at the 0.01 level (2-tailed).

GPA max. 30
,056
,771
29

There was no correlation between MTR and GPA without cap r = -0.01, n = 29, p
= 0.969.
There was no correlation between MTR and GPA with cap r = 0.06, n = 29, p =
0.771.
3.3. H3: TIMES OF CONTRIBUTION
H3: there will be a statistically significant difference between the use of an instant
messenger in comparison to a discussion forum regarding the times of
contribution.

24

�An observation on the introduction of mobile messenger apps for collaborative online tasks in
post-secondary education
Robert Schrenk

All produced posts were categorized according to the hour they were
written as (1) before 8 am, (2) between 8am and 4pm, and (3) after 4pm.
Figure 2 shows the allocation of messages over day times.

Figure 2: MediaType and times of contribution

An independent samples t-test was conducted to compare the times of
contribution for messages created using the messenger or the forum.
The t-test showed a significant difference in the times of contribution for the
forum (M = 2.52, SD = 0.56) and the messenger (M = 2.35, SD 0.56); t(346) = 2.79,
p = 0.006.
Table 4 T-test of MediaType on times of contribution
Levene's Test
for Equality of
Variances

Workshift

Equal
variances
assumed
Equal
variances not
assumed

t-test for Equality of Means t-test for Equality of Means

F

Sig.

t

df

Sig. (2tailed)

Mean
Difference

Std. Error
Difference

,829

,363

2,789

346

,006

,16865

,06048

2,789

316,897

,006

,16865

,06048

25

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

4. DISCUSSION AND CONCLUSIONS
The results of this study reveal that the use of an instant messenger on mobile
devices significantly reduces the length of written messages in comparison to
messages that are written on a computer. This may be misinterpreted as a
decreased quality of the learning outcomes. This is not necessarily true, if the
assignment is designed accordingly.
Therefore, it must be assured that either the length of contributions does
not predetermine the points awarded, or learners can compensate shorter
contributions with higher frequency and quantity. For the purpose of
collaborative assignments, this can even be advantageous as it raises the flow of
the communication in the learning process. Qamar, Riyadi and Wulandari (2019)
reported similar experience when they introduced the popular messenger
WhatsApp to a Blended Learning.
Learners who contribute in a discussion will think about the subject and
reflect on the outcomes more frequently. Consequently, it can be expected that
they identify themselves more with the outcome of the collaborative work and
are overall more actively concerned with the learning.
Furthermore, the combination of traditional digital communication
channels like forums and new channels like messengers allows to expand the
times of contributions of the learners. They stick to the learning on a more
frequent basis instead of providing punctual contributions. So, the learning
happens perpetually on a seamless basis. This means that learners can learn
whenever (Sinanović &amp; Bećirović, 2016) and wherever they want, also during
breaks or holes in their working schedule.
Interestingly the use of an instant messenger has another significant effect, that
was not analyzed by the initial hypotheses. The analysis focused on the
contributions that were required by the assignments. It was very salient that
many contributions did not get a grading. Most of these messages were intended
to support the social binding of the group.
An investigation into this showed that out of 200 forum posts, only 33
(16.5%) were not intended for grading, but out of 128 messenger posts these were
63 (42.6%). A chi-square test approved a significant association between the
MediaType and the purpose of grading, χ2 (1) = 28.93, p = 0.000 (0 cells have
expected count less than 5, minimum expected count is 40.83).
This proves, that the introduction of instant messengers in online learning
significantly supports the social cohesion of a learning group in comparison to
traditional forms of digital communication. Instant messengers can help to bring
close all collaborators of a group in a virtual team, so that collaborators assist
each other on a mutual basis. Berewot and Fibra (2020) found a similar impact on
students motivation in project learning.
Compared to the findings of Liebe, Glenk, Oehlmann and Meyerhoff
(2015, p. 24) and Feng et al. (2019) who suggest a negative impact of the use of
instant messengers on the grade point average, no such significant impact could
be confirmed in this study. Furthermore, research findings show that willingness

26

�An observation on the introduction of mobile messenger apps for collaborative online tasks in
post-secondary education
Robert Schrenk

to communicate (Rizvić &amp; Bećirović, 2017) and learning styles (Mašić, Polz &amp;
Bećirović, 2020) are significantly affected by GPA.
This makes the introduction of instant messengers to the learning very
attractive, although there must still be some awareness about possible negative
impacts, that were not discussed in this study (e.g. privacy), and there are certain
limitations to the tasks because of the form factor of the devices.

27

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

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                    <text>Journal of Education and Humanities
Volume 3 (1), pp. 30-42, Summer 2020
Professional paper
ISSN 2566-4638
© International Burch University

https://dx.doi.org/10.14706/JEH2020313

Multimodal Analysis of two Anti-Semitic
Posters in the Independent State of Croatia
Damir Bešlija
International Burch University
d.beslija@gmail.com

Abstract: Drawing on the researches of Rotim (2012) and Macut
(2012), two posters of the same kind published by the State Reporting
and Promotion Office under the Prime Minister's Office (Državni
izvještajni i promičbeni ured pri Predsjedničtvu vlade; Further in the
text: DIPU) are analysed from the perspective of critical discourse
analysis as well as multimodal analysis. Thus, the analysis of the text
as well as images of the two posters was conducted and different
linguistic and non-linguistic devices employed in this type of an
advertising poster were identified and explained. The poster is
observed as a social practice and different Discourses used in the
text are identified. Thus, the use of a masculine man who represents
the Croatian people and ideas in this image and the non-human,
animalistic representation of the Jews are clarified in terms of
dominant ideology of the period in question and vividly portrayed
through the poster. The paper also points to the unavoidable impact
such posters and the promoted ideologies have on the society’s
perception of the Jews.

Keywords: Critical
Discourse Analysis,
Discourse Analysis, AntiSemitism, Anti-Semitic
propaganda, Ideology.
Article History

Submitted: 1 June 2020
Accepted: 30 June 2020

�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

1. INTRODUCTION
With the establishment of the Independent State of Croatia on April 10, 1941, and
the adoption of racial and anti-Semitic laws, the persecution of Jews, Serbs, Roma
people, communists, as well as all those who opposed the Croatian policy, began.
The totalitarian regime had the task of creating a homogeneous state and the
Croatian authorities took Nazi Germany as their role model. In order to convince
people of validity and desire to enforce anti-Semitic laws, the government
launched a vigorous propaganda that was very similar to the one in nationalsocialist Germany and fascist Italy.
When the supporters of the Independent State of Croatia came to power,
they put under control all media that could be exploited for informing the public
about their current affairs. This media control allowed them to reach out to every
citizen and expose their policies, as well as glorify the Fascist movement and
leader. In the early days of the Independent State of Croatia, the central
institution for the control of the media-promotion system, known as the State
Secretariat for National Education was founded, and finally, in January 1942, the
State Reporting and Promotional Office under the Prime Minister's Office was
established. The establishment of these offices only proves the fact that
propaganda played a large role in NDH (Goldstein, 2001).
Its anti-Semitic rhetoric having its role model in Nazi Germany and Fascist
Italy, the Independent State of Croatia invested large amounts of money into
promotion and advertisement of newly created theories that supported the
Holocaust and the most significant person who endeavoured to proliferate
different kinds of art exhibiting anti-Semitic ideas, was Joseph Goebbels, the
president of the Reich Ministry of Public Enlightenment and Propaganda
(German: Propagandaministerium). Advertisements of different events,
including the “Exhibition on the development of Judaism and their destructive
work in Croatia before 10/6/41. The solution to the Jewish question” (Croatian:
Izložba o razvoju židovstva i njihovog rušilačkog rada u Hrvatskoh prije 10.
IV.1941. Rješenje Židovskog pitanja; translated by the author) were meant to
appeal to emotions of common people and to assert the State’s ideology (Jareb,
2009).
As different ideologies have intertwined in these areas for centuries, some
of which have had a significant impact on human lives, this paper draws
attention to devastating anti-Semitic propaganda, in particular to the posters for
the exhibition held in 1942 in Zagreb and Sarajevo, and seeks to establish a link
between the way posters convey information and the socio-political context in
which they are created. Furthermore, the paper analyses the posters in terms of
formal, functional, and social approaches to advertisement discourse and points
to the ways in which the use of multimodal discourse practice can project a
particular ideology. Finally, it seeks to point out how the impact of a not-soclearly visible ideology can be devastating.

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2. LITERATURE REVIEW
Advertisement genre is usually used to promote and eventually sell certain
products or ideas (Jones, 2012) and advertisements are believed to be one of the
most useful persuasive devices prominently displayed in newspapers, leaflets,
posters and nowadays mainly on-line. Thus, they are used as an effective tool
aptly exploited for promoting dominant ideology and accomplishing one’s aims
through different linguistic and non-linguistic devices. They might or might not
attract the people’s closer attention, but they surely indicate how people think
and what they believe in (Cook, 1996).
Karlsson (2015) analyses advertising as a process of persuasion and
identifies several steps in the process, including comprehension, acceptance,
attitude change and retention of the message that is being conveyed. Namely, the
product or idea that is being advertised needs to be comprehensible enough for
a viewer to accept it and, consequently, change his attitude. Finally, research has
shown that our perception of the message being advertised is rather
subconscious, which is contrary to the belief that our acceptance (or refusal) of
the product is a matter of choice (Karlsson, 2015).
Since advertisements are very influential and might possibly sway one’s
opinion, they are usually considered a very controversial genre. Two most
prominent characteristics of advertising material is that it uses language in a way
that is appealing to the target audience, and that the language used is usually
followed by some visual aids in order to make it more memorable or to dramatize
the content. Thus, it is of considerable importance that both linguistic and nonlinguistic properties of advertisements be systematically analysed (Cook, 1996).
An additional dimension that advertising carries is ideology. Ideologies
are proliferated by constructing specific versions of reality adopted by followers
of certain beliefs, who are interconnected and share common customs and ideas
(Jones, 2012). Hence, these subliminal ideological messages in advertisements are
frequently the focus of the modern linguistics analysis conducted by a close
observation of the text’s linguistic features and their relationship with the context
that surrounds them. Judith Williamson (1978), for instance, claims that
advertisements have two main functions: the economic one which makes us
potential buyers of certain products and the ideological function which gathers
people around certain idea and produces the feeling of unity (Chong, 2017).
The theoretical background of the current paper needs to be based on
critical discourse analysis and multimodal discourse analysis due to the fact that
language is combined with other modes of communication, i.e. images and
visuals, and they are exploited as the main tools politics exploits for promoting
its own ideologies and accomplishing its goal.
Critical Discourse Analysis
Critical discourse analysis refers to the field that unites linguistic
disciplines and social science and aims at studying and analysing written and
spoken texts in order to find and understand the discursive sources of power,

32

�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

dominance, inequality and bias (Dijk, 1998). Furthermore, as Rogers claims,
critical discourse is always “socially, politically, racially and economically
loaded” (Rogers, p. 6). Its main focus is examining the relationship between the
usage of language and the contexts (either social or political) in which it occurs.
Moreover, critical discourse analysis explores issues such as gender, ethnicity,
cultural differences, ideology and identity and how these are constructed and
reflected in texts.
Fairclough and Wodak (1997) define principles of critical discourse and
state the major four as following:
A
Social and political issues are constructed and reflected in discourse.
Critical discourse analysis addresses political and social issues and examines
ways in which these are constructed and reflected in the use of discourse.
B
Power relations are negotiated and performed through discourse. Critical
discourse analysis conversational interaction, and aims at defining who controls,
i.e. who allows the person to express themselves and how they allow that.
C
Discourse both reflects and reproduces social relations. Social relations are
both established and maintained through the use of a discourse.
D
Ideologies are produced and reflected in the use of discourse. Critical
discourse analysists claim, that ideologies are what represent and construct
society. They are usually focused on forming relations of power which are based
on gender, class and ethnicity. Critical discourse studies aim to make connection
between social and cultural practices and the values and assumptions that
underlie the discourse. They try to reveal what people say and do in their use of
discourse in relation to their views of world, themselves and relation of each
other.
Any analysis of any text that contains linguistic elements is based on four
main assumptions, which revolve around the facts that (1) it is never absolutely
clear what is expressed by a certain expression; that (2) what language means is
the matter of place and time in which it is used; that (3) we use language to
display different social identities we possess; and that (4) linguistic features of
languages are always combined with some non-linguistic elements (Jones, 2012).
Multimodal discourse analysis
Modal discourse analysis refers to analysing how certain types of
advertisement use different modes of communication in order to convey their
message (Martinez Lirola, 2016). The posters which this paper analyses combine
both visual and textual modes. We could say that the textual basis of the posters
is rather strengthened by the images which are supposed to attract readers’
attention. However, the posters need to be observed as a whole together with all
the modes used in order to fully comprehend the message they send.
Much research has focused on political and ideological advertising
primarily through electronic media (Shäffner &amp; Bassnett, 2010) or interviews
conducted for purposes of political advertising (Chen, 2007). However, to our
knowledge, there are not many papers which have focused on the posters as
overly influential means of proliferating political and even ideological beliefs. In

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Volume 3, Issue 1, Summer 2020

such papers, analysis similar to this one was done and posters were analysed
from the perspective of modal discourse analysis with their potential ideological
influence further clarified Aulich &amp; Sylvestrová, 1999; Johnston, 2006; Popova,
2012).
The current study
Through the analysis of the two aforementioned posters, observed as a
social practice, the present paper aims to communicate the socio-cultural
situation of the period and how social and power relations were established
through the use of both linguistic and non-linguistic devices, visual elements in
particular. Thus, relying on two theoretical constructs, namely critical discourse
analysis and multimodal analysis, the current paper seeks to show how ideology
promoted by the image on the poster is identified and explain its influence on the
society’s perception of Jews. Due to the fact that posters, advertising posters in
particular, send different subliminal messages and sometimes skilfully conceal
some strong political ideologies, this paper is an attempt to help readers
recognize and understand how such messages are conveyed, which might lessen
the devastating effect different ideologies might have on them.
3. METHODS AND DATA
Two advertising posters of the same kind published by the State Reporting and
Promotional Office under the Prime Minister's Office (Croatian: Državni
izvještajni i promičbeni ured pri Predsjedničtvu vlade; translated by the author)
were selected from the book Media and Promotion in the Independent state of
Croatia (Croatian: Mediji i promidžba u Nezavisne Države Hrvatske; translated
by the author) written by Jareb (2009). They can be found in a private collection
which belongs to professor Eli Tauber who lives in Sarajevo. The posters are
presented and analysed by the use of textual analysis methodology, which
involves the analysis of linguistic (i.e. grammatical and lexical) and non-linguistic
(i.e. images, symbols) features in the posters. Finally, ideological functions of the
posters are presented and explained together with a possible effect they might
have had on the discourse community to which they had been presented.
The posters may be found in Appendix section and due to the fact that the
posters are originally in Croatian, the original texts as well as their translations
are presented below.
1. Original text:
ŽIDOVI
IZLOŽBA O RAZVOJU ŽIDOVSTVA
I NJIHOVOG RUŠILAČKOG RADA
U HRVATSKOJ PRIJE 10IV1941
RJEŠENJE ŽIDOVSKOG
PITANJA U N.D.H.

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�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

1.V.1942
1.VI.1942
Translation:
JEWS
EXHIBITION ON THE DEVELOPMENT OF JUDAISM
AND THEIR DESTRUCTIVE WORK
IN CROATIA BEFORE 10IV1941
THE SOLUTION TO THE JEWISH
QUESTION IN N.D.H.
1.V.1942
1.VI.1942
2. Original text:
ŽIDOVI
IZLOŽBA O RAZVOJU ŽIDOVSTVA
I NJIHOVOG RUŠILAČKOG RADA
U HRVATSKOJ PRIJE 10IV1941
RJEŠENJE ŽIDOVSKOG
PITANJA U NDH
6.-20. RUJNA 1942
FERHADIJA ULICA BR. 11 (BIVŠA BOGOSLOVIJA)
ULAZNICA KN. 10.-ZA SKUPINE KN. 5 PO OSOBI
Translation:
JEWS
EXHIBITION ON THE DEVELOPMENT OF JUDAISM
AND ITS DESTRUCTIVE WORK
IN CROATIA BEFORE 10IV1941
THE SOLUTION TO THE JEWISH
QUESTION IN NDH
6.-20. SEPTEMBER 1942
FERHADIJA STREET NO. 11 (FORMER FACULTY OF THEOLOGY)
TICKET KN. 10.-FOR GROUPS KN. 5 PER PERSON
4. RESULTS AND DISCUSSION
The posters from Zagreb and Sarajevo contain several linguistic and nonlinguistic elements that are analysed in the following sections. The first notable
non-linguistic feature that grabs readers’ attention is the image of a snake
wrapped around a muscular man who is trying to kill it. In the poster from
Sarajevo (Figure 2) this image is even more influential due to the fact that it is
colourised and it vividly portrays certain ideologies that are represented through
colours.
The most significant linguistic elements that are analysed are the text, its
form and content. As it could be seen in the previous section, the texts from
Sarajevo and Zagreb slightly differ in word choice, however that does not majorly
influence the conveyed message.

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�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

Figure 1: Poster from Zagreb

Figure 2: Poster from Sarajevo

The first part of the analysis will focus on the language of the two posters.
The very first property of language to be discussed is its ambiguity, i.e. the same
message that is being conveyed by certain linguistic or non-linguistic devices
might be understood differently. In these posters, ambiguity can be observed in
the phrase “exhibition on the development of Judaism”, which, on its own,
indicates that there is an exhibition in which some posters showing how Judaism
has developed are displayed and thus anyone seeing the poster and reading only
the first line without knowing the context and focusing on the image presented
on the posters would possibly conclude that this exhibition was about Jewish
tradition and culture. Even though this situation is highly improbable, taken all
the historical context and developing anti-Semitic beliefs of that time, it shows
how a single sentence can be seen and understood differently.
The second property of language is that it is placed in the world. This
means that language is always used in the material world, it is situated in time
and reflects its circumstances, it exhibits some kind of a relationship between
people who use it, and it can always be compared within a relation towards other
languages. The language of two posters, therefore, is placed in the material world
of Zagreb and Sarajevo streets during The Second World War and it exhibits the
relationship of three participants: The State, ordinary people and the Jews.
It is also rather interesting to observe how phrases and sentences are put
together to form a coherent and cohesive text, while possibly referring to some

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�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

other source of information. When it comes to the analysis of the posters, one
might conclude that the text present on them is coherent because it follows a
generic framework which sets certain expectations about how advertising should
be organised and what kind of social actions will follow. A reader will
understand that there is an exhibition on the development of Judaism at certain
place and time, and that everybody is invited. In addition, Sarajevo’s poster
suggests that the exhibition is not free, but that group visits can get a discount.
Furthermore, the posters’ text exhibits both lexical and grammatical
cohesion. There is an obvious lexical chain between Jews, development of
Judaism and the solution to the Jewish question. Grammatical cohesion, on the
other hand, is seen in the use of a conjunction and (figure 1):
EXHIBITION ON THE DEVELOPMENT OF JUDAISM
AND THEIR DESTRUCTIVE WORK
After reader’s attention was caught by an ‘ordinary’ event that might present
Jewish culture, and adds a new piece of information that tells more about the
exhibition which will actually present the Jews as a destruction force.
Another element that adds to grammatical cohesion is the use of
referencing. In the poster from Zagreb (figure 1), the pronoun their refers to the
Jews from the title. By this the creators of the poster mark a whole group of
people, as if destruction were something naturally inherent to the Jewish
population.
EXHIBITION ON THE DEVELOPMENT OF JUDAISM
AND THEIR DESTRUCTIVE WORK
In the poster from Sarajevo (figure 2), the reference is different and, instead
of referring to the title, it refers to Judaism. By this, the creators of the poster
rather blame ideology and religion for destruction than their followers.
EXHIBITION ON THE DEVELOPMENT OF JUDAISM
AND ITS DESTRUCTIVE WORK
Moreover, the third property of language refers to its function of showing who
are the people (or participants) who use it. The posters show that The State was
publicly expressing its fascist ideology, but that, at the same time, the audience
consisting of ordinary people shared government’s political views and was
interested in such an event. This element is closely related to ideological
behaviour that has been previously defined and exemplified and clearly portrays
how the Fascist Nazi ideology was being used to represent one group of people
(Jews) in contrast to the other (the Aryans).
The last assumption is that language is never used in isolation, i.e. it is
always followed by certain non-linguistic elements. These elements might be
facial expressions, gestures, tone of voice, different fonts or graphics. In the case

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of the posters, image plays rather central role because it most vividly depicts the
power relation between Jews and Croats. It sends a very strong message: the
monstrous snake which has stars of David all along its body represents Jewish
people attacking a very masculine man who, on the other hand, represents all
that is Croatian.
Furthermore, the title “Jews” is written in much larger letters than the rest
of the text in order to attract readers’ attention. However, it does not necessarily
mean that it is the most important part of the poster. Actually, the whole text is
written with capital letters which might mean that all the information present on
the poster is, if not of the same, then of almost equal importance.
The poster from Zagreb is much simpler in terms of colour than the poster
from Sarajevo. While the first one is just black and white, the second one depicts
the colours of the Croatian Chessboard and that of a stereotypical Aryan
Caucasian man with ginger hear. More interestingly, the snake on the second
poster doesn’t only have the stars of David on it to suggest its Jewish identity,
but is also coloured in blue which is one of the biblical colours of Israel (both
nation and country).
Finally, another interesting observation is that the snake wrapped itself
around the man's waist and covered his genitals. Taken the context in which Jews
were condemned on the basis of their genetics and their physical appearance was
scientifically analysed as rather unhealthy, this probably implies that the Jews
not only ruled over economy and politics, but that they began to infiltrate
traditional families, thereby "polluting" them (Jareb, 2009).
The posters that are analysed in this paper clearly have the aim to inform
people about the events that will take place in Zagreb and Sarajevo, as well as
give further information about the time and entrance fee. However, informing or
advertising is done in a way that undermines the Jews, who are presented as evil.
The Jews are believed to have been a main destruction force and the exhibitions
will, therefore be about “the Jewry’s destructive work” in Zagreb and “Judaism’s
destructive work” in Sarajevo (as analysed before).
Moreover, at the end of the posters’ text, the authors suggest that at the
exhibition there will be given a “solution to the Jewish question”. Back then “The
Jewish Question” was a common way of addressing the Jewry and everything
connected to it. However, a choice of words is interesting because the event will
give a solution to, or will solve the Jewish Question as if it were a good deal of
misfortune or a problem that is to be solved. Finally, the poster from Sarajevo
informs people about entrance fee and a discount that is to be given for group
visits. By this, it clearly communicates two things; it shows that the event is
prestigious and only for the people who can actually pay for it but it also
encourages institutions and individuals to organise groups and come in large
numbers.
All these linguistic and non-linguistics elements are combined to portray
different ideologies through the posters and point to specific social and political
issues, as well as (in)directly assert the authors’ opinion (Aulich &amp; Sylvestrová,

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�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

1999). There are two ideologies which are present in these two posters and which
will be discussed further.
Firstly, the ideology of anti-Semitism which was a core of the NDH, found its
place in all the media, and the highlight of it is certainly the aforementioned
exhibition organized by the DIPU at the Art Pavilion at Strossmayer's Square in
Zagreb from May 1, 1942 to June 1, 1942. Apart from Zagreb, the exhibitions that
aimed at promoting aforementioned ideologies were staged in Osijek and
Sarajevo, and very similar posters were exploited in advertising these events. The
content of the posters accused Jews of exhausting the Croatian nation, the
economical and ideological occupation of Croatia, and all of this was usually
justified by the belief that the existence of the Jewish people threatened the
survival of any state wherever they lived. It is through this exhibition, which was
created in 1942 after severe and cruel persecution of the Jews, that the Facist
regime ultimately convinced the Croatian people of the correctness of their
decisions (Gitman, 2012).
Yet another ideology that is found in these two posters, and that was very
often used to empower the message being conveyed is the ideology of
masculinity. Nowadays, sexuality is often used in advertising for the purpose of
making the process more appealing to the opposite gender. Nudity is usually
manifested in the form of visuals, although it can be expressed through verbal,
musical, or scent elements (Gould, 1994). However, the elements of masculinity
presented through nudity in these two posters for their primary aim have to
show how strong and handsome is a man who is to protect the Croatian nation.
The ideology present in the posters helps people create a shared worldview but
also limits their ways of looking at reality. That is way many people were not
aware of the atrocities that were done to the Jewish population (Zuckerman,
2010).
In regards to ideology, it is clear how both posters openly support two of
them which were present in the NDH politics, fascism and anti-Semitism, and
exemplify their functions. The first function is ideational, meaning that the Jews
were chosen as a specific subject around which revolves a new worldview that
represents them as evil characters. The second function of the ideologies of the
posters is interpersonal, and its main task is to create a relationship with readers
who, if not yet, might become followers of that idea. This function is especially
significant for forming a certain discourse community which might later on
participate in creation of new advertising materials. The last function is purely
textual, and takes care of how the text itself is structured.
Finally, several different discourses might be found in the posters.
Discourse of advertising is a primary discourse because both posters are
advertisements of a kind and intend to inform readers about the exhibitions. In
addition, discourse of politics is also very obvious since the posters speak about
“the solution to the Jewish question”, which is, as already stated, a political
phrase used by the NDH government. Ultimately, unlike two aforementioned
discourses which are rather textual, another discourse present in a form of image
is discourse of art. Namely, through this artistic depiction of the Jewry and a

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Volume 3, Issue 1, Summer 2020

Croatian man, the authors send a strong message which tells that this exhibition
is a cultural event.
The current study is of great importance because it exemplifies and
analyses how the NDH employed a variety of devices, both linguistic and nonlinguistic, in order to proliferate the ideology and institutionally assert antiSemitism as well as make ordinary people blame the Jews for all problems in the
society. One can also see how the government makes a difference between a pure
Croat who is represented as a masculine man, and a Jew who is depicted as a
snake. Both posters rely on the linguistic and non-linguistic structure, but also on
emotion and feelings.
Moreover, these posters have an enormous influence on the society in a
sense that they establish a certain sort of a relationship between the readers who
share the government’s opinion and the Jews. The advertisements of the
exhibition clearly communicate the fact that the Jews are an evil, destructive force
and that the exhibition will provide some kind of a solution to the Jewish
Question. Nevertheless, we have to take into consideration that only two posters
of the anti-Semitic propaganda were analysed in this paper. In order to get a
complete image of the NDH propaganda and its influence on society, an analysis
of a larger number of advertisements needs to be done.
Ultimately, taken the unprecedented analysis of such posters from the
modal discourse analysis perspective that is presented here, this paper might be
useful for future studies on the topic of Croatian anti-Semitic politics, in terms of
defining and exemplifying the ways in which different advertising and
ideological discourses might be used to sway public’s opinion. It also might serve
future researches as a reference for evidence of anti-Semitic presence in spheres
of culture and public life in the Independent State of Croatia.

5. CONCLUSION
Two advertising posters published by the State Reporting and Promotional
Office under the Prime Minister's Office display all four properties of language:
(1) language is ambiguous, (2) it is always in the world, (3) it displays different
identities of its users and (4) it is never used in isolation. They also might be
observed from a perspective of three different ways of looking at discourse and
analysed as a part of Critical discourse analysis.
Furthermore, the authors of the posters used a variety of linguistic and
non-linguistic devices in order to make them more cohesive, coherent and to
include some outside references, which is an instance of intertextuality. In
addition, both of these posters make use of different discourses, such as discourse
of advertising, discourse of politics and discourse of art. The primary purpose of
the posters is to make readers perform an action of visiting the exhibition. It is
important to emphasise how both of them contain the same anti-Semitic ideology
with rather no hidden agenda: The Jews are a destructive force and an evil power
that needs to be eliminated.

40

�Multimodal Analysis of two Anti-Semitic Posters in the Independent State of Croatia
Damir Bešlija

The analysis provided in the paper relies on Critical Discourse and
Multimodal Analysis and it points to a blend of specific vocabulary and word
choices as well as concrete and vivid imagery employed to create textual and
visual meaning in order to show how discourses are constructed and what is their
purpose, as well as how ideologies are promoted and how they shape readers’
ideology. Thus, the political message clearly sent through the posters at the time
was that one nation, e.g. Jews, depicted in a non-human, animalistic shape,
fighting a brave Croatian warrior, represented a destructive force that needed to
have been dealt with and then, at the time, needed to have been continually
warned against. Without any doubt, such a vivid imagery combined with the
appropriate text contributed to shaping the ideology of the readers and
exhibition visitors at the time.

41

�Journal of Education and Humanities
Volume 3, Issue 1, Summer 2020

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