ArticlePDF Available

The Correlation between Arabic Student’s English Proficiency and Their Computer Programming Ability at the University Level

Authors:
Mrwan Benidris at University of Benghazi
Mrwan Benidris
Hany Ammar at West Virginia University
Hany Ammar
Download full-text PDF
Read full-text
Download citation

Figures

Figures - uploaded by Mrwan Benidris
Author content
All figure content in this area was uploaded by Mrwan Benidris
Content may be subject to copyright.
Content uploaded by Mrwan Benidris
Author content
All content in this area was uploaded by Mrwan Benidris on Oct 14, 2018
Content may be subject to copyright.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
DOI: 10.5121/ijmpict.2018.9101 1
T
HE
C
ORRELATION
B
ETWEEN
A
RABIC
S
TUDENT
’
S
E
NGLISH
P
ROFICIENCY AND THEIR
C
OMPUTER
P
ROGRAMMING
A
BILITY AT THE
U
NIVERSITY
L
EVEL
Mrwan Ben Idris and Hany Ammar
West Virginia University, West Virginia, USA
ABSTRACT
In order to find the relationship between students’ English ability and the students’ programming
comprehension, we conducted a survey. The survey explores if students’ weakness in the English language
affects the ability of the students to understand the programming with respect to the following factors:
Computer Lab, lecturer, mathematics, and logical thinking. This paper analyzed the results of two surveys
conducted in two Libyan universities. Results of the surveys showed that 37%, 38%, and 25% of students
stated that their programming abilities were negatively affected by English, Computer Lab and Lecturer
respectively. While over half of the lecturers mentioned that the students’ lack of English was the main
reason for their weak performance in understanding programming skills. This study found that the
programming ability had a moderate correlation with the Level of English proficiency, r=0.63, for both
universities. Based on English, Computer Lab and Lecturer factors, a regression model was able to explain
that 45% of the variance in programming skills.
KEYWORD
Computer Programming, English language, Computer Lab, Lecturer, Logical Thinking, Mathematics.
1. INTRODUCTION
Complex syntactic rules, confusing structures, complex expressions and uncommon symbols for
programming languages are difficult and complicated for novice programmers to interpret them
quickly [1]. At the university level, learning programming for many beginner students is not easy,
especially if the programming language is English based while the students are not native English
speakers. Computer programming will be difficult for students who are non- native speaker
because of the different issues related to understanding the language command keywords and
syntax. Elazhary said that from her experience as a lecturer, she noticed that students who are not
fluent in English had difficulties in learning, remembering and using conventional programming
languages. Furthermore, she observed that it is even harder for them to comprehend English
compilation error messages [2].
In the Middle East and North Africa, millions of people speak Arabic. Besides, many millions
around the world speak Arabic because of their religions [3]. However, in Arabic countries, most
of the programming courses that are offered by educational institutions are written and taught in
English due to the programming languages being English based. Therefore, Arabic speaking
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
2
students who are non-native English speakers have difficulties in understanding and remembering
the commands of a programming language [4]. On the other hand, many popular programming
languages such as C, C++, Java, JavaScript, and Visual Basic were developed in English
speaking countries [12][4]; while just one Arabic programming language, called Phoneix
Language, was developed in the Arabic language [4].
We need to develop an Arabic programming language for teaching basic programming
knowledge to those who lack proficiency in the English language. Consequently, the Arabic
students can use their native language to comprehend the concepts of programming and use the
new Arabic Programming Language as their first step for efficiently learning programming. The
new Arabic programming language will help the Arabic students to learn a programming
language that was developed in their mother tongue. With the aim of supporting the development
of an Arabic programming language, we conducted survey studies to find out if Arabic students
that are non-native English speakers have difficulties in English programming language
comprehension due to their lack of sufficient English skills [2].
The main contribution of the survey is to provide empirical evidence of the impact of the lack of
English on the students’ programming comprehension with respect to other factors that the
percipients mentioned affect their comprehension of languages programming. Including open-
ended questions in the survey, which allowed participants to write comments freely, will help us
identify any additional factors that may affect their programming ability.
The rest of this paper is organized as follows: section 2 introduces related work, section 3
presents our problem statement, section 4 presents our empirical results, and section 5 conclusion.
2. RELATED WORK
Learning and teaching computer programing is not easy, and many students struggle to learn how
to start with it [9]. According to Pedroni [10], learning and teaching programming is a challenge
[11]. Several factors may impact students’ programming ability such as previous computer
programming experiences [6][8][5]. Also, the students’ programming performance can be
increased by implementing multiple approaches to learning the material [9]. Moreover, several
studies have found a positive relation between mathematical and programming ability [5][6][7].
Undoubtedly, many factors can affect novice programmers. However, for Arabic speakers who
lack English proficiency, learning from only English language programs play a significant role in
such a student’s performance in programming [2].
Hanan Elazhary developed Arabic versions of LISP and SQL where the syntax errors are
produced in Arabic, and she tried to discover whether this Arabic software could improve the
programming ability for the Arabic programmers. The participants who were from different
disciplines and ages were not fluent in English. They were asked to write easy programs via the
English and Arabic versions of LISP and simple queries using the English and Arabic versions of
SQL after training had been done for the participants in both versions of LISP and SQL. After
that, two surveys were conducted, one for experienced programmers and the other for beginner
programmers. Around 98% of the beginner participants who were less than 15 years old
preferred the Arabic version of LISP, and they did not show any interest in SQL. About 82% of
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
3
the older novice programmers, who were not computer-related, preferred the Arabic version of
SQL, but they did not show much interest in LISP. On the other hand, approximately 85% of the
participants who had programming experience preferred the English versions of both LISP and
SQL. In addition, the experienced programmers preferred improving their English language
rather than using the Arabic versions [2].
Ashok and Anna analyzed the Java and SQL programming ability of non-native English students
where they prepared two kinds of tests. The first test was an English language test which exams
the student’s ability in identifying the meaning of programming language keywords in social
context. The second test was a Computer Language Test, which tests the student’s ability in
understanding the functional meaning of the keywords in the computer programming context.
The students who are non- native English speaker were divided into two groups (student A and
student B).
• Student A – learning programming courses at higher education where the instructional
language is other than English.
• Student B – learning programming courses at higher education where the instructional
language is English.
The authors proposed this framework for future research to identify the effect of students’ English
comprehension on students’ programming ability [4].
However, despite the fact that a considerable amount of research has been carried out on many
factors such as approaches to learning programming, and mathematics factors that affect
programming performance, our paper focuses on the English language as a factor that affects the
performance of Arabic speakers on the university level with respect to other factors which were
stated by the participants.
3. PROBLEM STATEMENT
Problem
Many of the Arabic novice programmers face difficulties in understanding programming as a
course, and some of them may drop the programming course after attending a few classes. Many
factors may affect students’ understanding of the programming course such as the labs, lecturers,
Mathematics and Logical thinking involved; therefore, these factors will not be ignored in our
study. However, there is another factor that can make programming harder for Arabic students
which is the lack of understanding the English language.
Goal
The goal is to survey the students to explore if the students’ weakness in the English language
affects their ability to understand programming courses. If that survey confirms the influence of
the lack of English on the programming understanding, we will try to find a solution by
developing a programming language which will be Arabic to help novice students understand
programming courses.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
4
Research questions
In our surveys, we wanted to investigate the following research questions, which could help us
understand some of the Arabic students’ programming problems at the university level
1. Do students’ weakness in understanding English affects the ability of students to
understand programming?
2. Are students’ programming skills affected by other factors such as lecturers, labs,
Mathematics background and logical thinking?
4. OUR EMPIRICAL STUDY
Research Design and Instrumentation
A cross-section survey was developed and utilized to collect data to find whether the lack of
students’ English proficiency leads to weakness in understanding programming. The survey
consists of closed and open questions that were asked in the Arabic Language in order to be
unambiguous and understandable to all Arabic students. The selected student answered the first
survey. So, since most of the students did not take the TOEFL or IELTS tests beforehand, the
Students were asked to rate their English language level using a 5-point Likert scale: 1 (poor), 2
(average), 3 (good), 4 (very good), and 5 (excellent). Participants also asked to mention other
factors that affected their programming skills other than English Proficiency. They were also
asked to indicate whether an Arabic programming language could increase their programming
performance. Student programming performance is measured by their GPA in the programming
course.
The second survey was answered by the lectures to take the benefit of the lecturers’ experience
and see if they feel that the lack of students’ English leads to weakness of understanding
programming. And also we tried to find out from the lecturers that there may be other potential
problems affecting the students’ understanding. Finally, we surveyed two universities to compare
the results and avoid bias.
The Pilot Study
We conducted a pilot study for the students of Faculty of IT at the University of Benghazi. In this
study 35% of the students mentioned the lecturer is a reason that affected their ability of
understanding programming. Accurately 20% of students indicated that the lack lab assistance as
the reason which is shown in Figure 1. We added these two factors, Lab and Lecturer, to our main
factor which is the English language to avoid these two factors from affecting our results.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
5
35%
45%
20%
lecturer
Lab
English
Figure. 1 The Pilot study results
Our Independent and Dependents Factors
The teachers added two new independent factors which are the Mathematics and the logical
thinking. So, with the result of the pilot study, the surveys explore the effect of the five
independent factors which are lecturers, labs, mathematics, the logical thinking and the English
proficiency on the computer programming ability (GPA) which is our dependent variable.
Participants and Data Collection
Because we were going to investigate a limited number of undergraduate students and wanted to
ensure that we included students in different years, we used stratified random sampling from the
population of the two universities. The alumni students were excluded because it was difficult to
communicate with them. The students were categorized into different strata based on their current
year. Additionally, I included all programming lecturers who are interested in participating in the
survey.
Table 1: The participants
Faculty of IT
University of Benghazi
Department of CS
Omar Al-Mukhtar University
Students Lecturers Students Lecturers
First year 23
15
First year 15
30
Second year 24 Second year 18
Third year 20 Third year 15
Fourth year 23 Fourth year 14
Fifth year 21
Total 111 15 Total 62 30
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
6
Table 1 shows that the sample size of the students for both universities is 173 students (N1=111 +
N2=62) and for the teachers is 45 instructors (N3=15 and N4=30). The samples N1 and N3 were
taken from the students and lecturers of the Faculty of IT – the University of Benghazi while the
samples N2 and N4 were taken from the students and lecturers of the Department of Computer
Science – Omar Al- Mukhtar University.
5. DATA ANALYSIS RESULTS
Initially, the dependent variable (GPA) and the level of English proficiency were analyzed using
scatter plot. A linear relationship between these two factors was found as a result. So, I choose to
use linear regression method and descriptive statistics to analyze the data.
Table 2: The independent variables from the Students’ point of view
Independent
variables
Faculty of IT
University of Benghazi
Department of CS
Omar Al-Mukhtar University
N1 (%) N2 (%)
English 44 (40%) 20 (32%)
Lab 37 (33%) 29 (48%)
Lecturer 30 (27%) 13 (21%)
# of students N1 = 111 N2 = 62
As shown in Table 2, accurately 40% of the participated the University of Benghazi (N1) students
indicated the English language as the first factor that had a negative impact on their GPA. The
Lab and Lecturers were selected as negative factors with percentages 33% and 27%, respectively.
On the other hand, precisely 48% of Omar Al-Mukhtar (N2) students explicitly indicated that
their programming abilities were affected by the lack of labs. While 32% stated that the lack of
English proficiency affected their GPA and the remaining 27% said that our programming
abilities were negatively influenced by the teacher inability in giving the explanation.
From the displayed results in Table 3, the teachers (N3 and N4) were asked to rate the level of all
students skills in the English language, where the rate has five levels (1= Bad, 2= Satisfied, 3=
Good, 4= Very Good, and 5= Excellent). The second column describes sample 3 (N3) which is
University of Benghazi’s faculty members who provided their opinions in percentages. For
instance, a bit more than a quarter (27%) pointed out that students do not have enough English
language skills and this could be the main reason of low GPA. The Same percentage (27%) of
sample N3 loaded the reason for having low scores among IT students in Benghazi as lack of
logical thinking in the IT students. Exactly 20% of teachers mentioned that there are no enough
Labs at the university, so the students could not practically practice. Precisely 13% of teachers
said that students have lack of deep understanding of mathematics, and the same percentage of
teachers mentioned that some of their colleagues do not provide enough information to their
students in the class. In contrast, most of the teachers at Omar Al-Mukhtar University, 63%
supported the idea of students should improve their English language before starting study
programming courses. Roughly the quarter of the instructors at the same university indicated that
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
the university did not update most
that the low mathematics background of the student has a negative impact on their GPA and a
relatively small percent mentioned that lecturers and logical Thinking might be the
Table
3: The Independent Variables from the Teachers’ Point of View
Independent
variables
University of Benghazi
N3 (%)
English
4 (27%)
Mathematics
2 (13%)
Logical thinking 4
(27%)
Lecturer
2 (13%)
Lab
3 (20%)
# of teachers
N3 = 15
As shown in figure 2 more than half of the lecturers, and 22% of the lectureres are confident that
the English and the Lab showed the first and the second impact
students respectively. On the other hand students had selected these two factors with percentage
of 37% for the English and 38% for the Lab. 25% of the students believes that their lecturers were
the reason behind their lack
of programming, while 7% of the lecturers agree with them. No
student stated that the math and the logical thinking as factors that affected their programming
understanding. 9% and 11% of the lecturers indicated that the lack of the programming caused by
t
he weak background in math and the lack of the students’ ability to think logically,
Figure. 2 The percentage of independent variables for the all samples
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
the university did not update most
equipment and facilities at Labs. Just 7% of the teachers said
that the low mathematics background of the student has a negative impact on their GPA and a
relatively small percent mentioned that lecturers and logical Thinking might be the
reasons.
3: The Independent Variables from the Teachers’ Point of View
Faculty of IT
University of Benghazi
Department of CS
Omar Al-
Mukhtar University
N3 (%)
N4 (%)
4 (27%)
19 (63%)
2 (13%)
2 (7%)
(27%)
1 (3%)
2 (13%)
1 (3%)
3 (20%)
7 (24%)
N3 = 15
N4 = 30
As shown in figure 2 more than half of the lecturers, and 22% of the lectureres are confident that
the English and the Lab showed the first and the second impact
on programming skills for the
students respectively. On the other hand students had selected these two factors with percentage
of 37% for the English and 38% for the Lab. 25% of the students believes that their lecturers were
of programming, while 7% of the lecturers agree with them. No
student stated that the math and the logical thinking as factors that affected their programming
understanding. 9% and 11% of the lecturers indicated that the lack of the programming caused by
he weak background in math and the lack of the students’ ability to think logically,
respectively.
Figure. 2 The percentage of independent variables for the all samples
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
7
equipment and facilities at Labs. Just 7% of the teachers said
that the low mathematics background of the student has a negative impact on their GPA and a
reasons.
Mukhtar University
N4 (%)
19 (63%)
2 (7%)
1 (3%)
1 (3%)
7 (24%)
N4 = 30
As shown in figure 2 more than half of the lecturers, and 22% of the lectureres are confident that
on programming skills for the
students respectively. On the other hand students had selected these two factors with percentage
of 37% for the English and 38% for the Lab. 25% of the students believes that their lecturers were
of programming, while 7% of the lecturers agree with them. No
student stated that the math and the logical thinking as factors that affected their programming
understanding. 9% and 11% of the lecturers indicated that the lack of the programming caused by
respectively.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
The correlation between the GPA and the level of English proficiency had been cal
r=0.63, which means the correlation is moderate.. However, to gain more insight of the nature of
this data, a statistical regression model was designed to study the effect of the level of English
Proficiency, lecturers, and labs on students’ GPA a
Omar Al-Mukhtar University.
As shown in table 4a and 4b, the multiple regression analysis provides a significant model with
some attractive results and p-
value < 0.05. The independent value explained about
Square = 0.46) of the total variation in the dependent variable (GPA for N1), and around 44%
(GPA for N2); where the level of English has a positive effect on GPA which means when the
level of English Proficiency
increases the GPA for the student
factors have a negative association with the GPA which means when the lack of labs and effort
lecturers increase, the student’s GPA decrease. The variation of the observed GPA (standard
error)
about the regression line is 0.66.
6. T
HREATS TO
V
ALIDITY
1. Construct Validity
: The University of Benghazi’s results depend on the data that was
collected during a war condition. Indeed, the university buildings were destroyed entirely,
every college moved to
one or more high school buildings where they study only in the
evening period. These circumstances affected the new students where we found that 60%
from freshman chose the lab as the first factor that influenced their programming
2. Internal Validity:
The teachers’ sample size is considered small when applying statistical
analysis methods.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
The correlation between the GPA and the level of English proficiency had been cal
r=0.63, which means the correlation is moderate.. However, to gain more insight of the nature of
this data, a statistical regression model was designed to study the effect of the level of English
Proficiency, lecturers, and labs on students’ GPA a
t two universities, University of Benghazi and
As shown in table 4a and 4b, the multiple regression analysis provides a significant model with
value < 0.05. The independent value explained about
Square = 0.46) of the total variation in the dependent variable (GPA for N1), and around 44%
(GPA for N2); where the level of English has a positive effect on GPA which means when the
increases the GPA for the student
increases (Positive relationship). While, the lab and lecturer
factors have a negative association with the GPA which means when the lack of labs and effort
lecturers increase, the student’s GPA decrease. The variation of the observed GPA (standard
about the regression line is 0.66.
ALIDITY
: The University of Benghazi’s results depend on the data that was
collected during a war condition. Indeed, the university buildings were destroyed entirely,
one or more high school buildings where they study only in the
evening period. These circumstances affected the new students where we found that 60%
from freshman chose the lab as the first factor that influenced their programming
The teachers’ sample size is considered small when applying statistical
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
8
The correlation between the GPA and the level of English proficiency had been cal
culated,
r=0.63, which means the correlation is moderate.. However, to gain more insight of the nature of
this data, a statistical regression model was designed to study the effect of the level of English
t two universities, University of Benghazi and
As shown in table 4a and 4b, the multiple regression analysis provides a significant model with
value < 0.05. The independent value explained about
46% (R
Square = 0.46) of the total variation in the dependent variable (GPA for N1), and around 44%
(GPA for N2); where the level of English has a positive effect on GPA which means when the
increases (Positive relationship). While, the lab and lecturer
factors have a negative association with the GPA which means when the lack of labs and effort
lecturers increase, the student’s GPA decrease. The variation of the observed GPA (standard
: The University of Benghazi’s results depend on the data that was
collected during a war condition. Indeed, the university buildings were destroyed entirely,
one or more high school buildings where they study only in the
evening period. These circumstances affected the new students where we found that 60%
from freshman chose the lab as the first factor that influenced their programming
ability.
The teachers’ sample size is considered small when applying statistical
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
9
3. Conclusion Validity: Which answered this question, have we drawn the correct
conclusions? And to ensure that the right statistical methods were selected a specific care
had been taken. Furthermore, in this paper, all formal statistical tests are based on random
samples.
4. External Validity: It is related to the ability to generalize the results. This study is based
on data collected from two universities which are from the same country. Consequently,
while many of the results could be captured in any Arabic county, we cannot generalize
the results because they are not based on multiple studies that have replicated the same
survey in different Arabic countries.
7. C
ONCLUSION AND
F
UTURE
W
ORK
Factors such as English, labs, lecturers, mathematical and logical thinking affected the ability of
the students in programming. Descriptively, 51% from the lecturers and 37% of the students
believe that the English is the most mentioned factor that affected the students’ ability in
programming. While 38 % of the students and 22% of the lecturers stated labs. About 45% of the
variance in programming skill could be observed by the level of English proficiency, labs and
lecturers. However, the student never worked with an Arabic programing language, In future, we
decided to conduct an experiment using Arabic programing language, English programing
language, and TOFEL or ILTS test in order to determine the level of English proficiency for the
students. By testing the student we avoid any bias that related to the English language factor.
A
CKNOWLEDGMENT
We show appreciation to both Mr. Khirallah Alferjani, the head of the computer science in the
Faculty of IT at University of Benghazi, and Mr. Adel Fadel, the chief of the computer science at
Omar Al-Mukhtar University, for helping us during the survey distribution stage by facilitating
our communications with students and teachers.
R
EFERENCES
[1]
Youssef A. Bassil, and Aziz M. Barbar, “MyProLang – My Programming Language A Template-
Driven Automatic Natural Programming Language”, World Congress on Engineering and
Computer Science, October 2008.
[2]
Hanan Elazhary, “Facile Programming”, the International Arab Journal of Information
Technology, May 2012, pp. 256-261.
[3]
Majdi Beseiso, Abdul Rahim Ahmad, and Roslan Ismail, “A Survey of Arabic Language Support
in Semantic Web”, International Journal of Computer Applications, November 2010, pp. 35-40.
[4]
Ashok Kumar Veerasamy and Anna Shillabeer, “Teaching English Based Programming Courses
to English Language Learners/Non-Native Speakers of English”, International Proceedings of
Economics Development and Research (IPEDR), 2014, pp. 17-22.
[5]
Brenda Cantwell Wilson and Sharon Shrock, “Contributing to success in an introductory computer
science course: A study of twelve factors, SIGCSE Technical Symposium on Computer Science
Education, 2001, pp. 184-188.
[6]
Byrne, P., and Lyons, G., “The effect of student attributes on success in programming”, ACM
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 9, No. 1, March 2018
10
SIGCSE Bulletin, 2001, pp. 49-52.
[7]
Bergin, S., and Reilly, R., “Programming: Factors that influence success”, SIGCSE Technical
Symposium on Computer Science Education, February 2005, pp. 411-415.
[8]
Vennila Ramalingam, Deborah LaBelle, and Susan Wiedenbeck, “Self-efficacy and mental
models in learning to program”, SIGCSE conference on Innovation and technology in computer
science, 2004, pp. 171 – 175.
[9]
Prince Yaw Owusu, Kofi Adu-Manu, John Kingsley Arthur, and Charles Adjetey, “Performance
of Students in Computer Programming: Background, Field of Study and Learning Approach
Paradigm”, International Journal of Computer Applications, September 2013, pp. 17-21.
[10]
[10]M. Pedroni (2003), “Teaching Introductory Programming with Inverted Curriculum
Approach” [Online], Available: http://e-collection.ethbib.ethz.ch /eserv/eth:28338/eth-28338-
01.pdf (Accessed: March 21, 2011).
[11]
Regina A. Garcia and Lilac A. Al-Safadi, “Comprehensive Assessment on Factors Affecting
Students' Performance in Basic Computer Programming Course towards the Improvement of
Teaching Techniques”, International Journal for Infonomics (IJI), 2013, 682-691.
[12]
From siliconindia:
http://www.siliconindia.com/shownews/10_Most_Popular_Programming_Languages- nid-
106520- cid-2.html.
View
View
View
Learning Programming Difficulties: Toward an Integrated Conceptual Framework
Chapter
  • Aug 2023
Computer programming languages are becoming more indispensable as our world becomes more computerized. This paper highlights the importance of the factors affecting programming learning difficulties. A survey method was employed to measure the relationships between variables related to programming learning difficulties. A total of 227 students studying for a computer programming diploma at Umm Al-Qura University in Saudi Arabia were surveyed for this purpose. The methodology for the study was structural equation modeling, and AMOS software was used to test the structural and measurement model and study the interlinkages between variables. The theoretical framework employed in this study comprised the technology acceptance model and experiential learning theory. The indirect factors were English language competency, learning materials, educational facilities, and teaching practices. The study concluded that the interactions of these factors explain the programming learning difficulties experienced by students enrolled in programming courses. Moreover, the factors which had the greatest effect on programming learning difficulty were English language competency and educational facilities. Therefore, the factors mentioned above should be considered by educational institutions for enhancement and ongoing development because of their connection with the programming learning difficulties experienced by students.KeywordsProgramming languagelearning difficultieslearning environmentsteachinglearning materials
View
A Comparison Study of Machine Learning Algorithms for Credit Risk Prediction
Chapter
  • Aug 2023
The banking industry performs credit score analysis as an efficient credit risk assessment method to determine a customer’s creditworthiness. In the banking industry, machine learning could be used for a variety of uses involving data analysis. A method of data analysis that is capable of self-regulation has been made possible by the development of modern techniques, such as classification approaches. The classification method is a form of supervised learning in which the computer acquires knowledge from the provided input data and then utilizes it to classify the dataset, which is used for training purposes. This study presents a comparative analysis of the various machine learning algorithms that are utilized to evaluate credit risk. The methods are used by utilizing the German Credit dataset that was collected from Kaggle, which consists of 1,000 instances and 11 attributes, all of which are used to determine if transactions are good or bad. The findings of data analysis using Logistic Regression, Linear Discriminant Analysis, Gaussian Naive Bayes, K-Nearest Neighbors Classifier, Decision Tree Classifier, Support Vector Machines, and Random Forest are compared and contrasted in this study. The findings demonstrated that the Random Forest algorithm forecasted credit risk effectively.KeywordsCredit RiskBankingMachine LearningPredictionFeatures
View
View
View
View
View
Teaching Programming to Students with Vision Impairment: Impact of Tactile Teaching Strategies on Student’s Achievements and Perceptions
Article
Full-text available
  • Jul 2020
The United Nations (UN) 2030 agenda involved 17 Sustainable Development Goals (SDGs) to achieve a better and more sustainable world for all. The fourth Sustainable Development Goal called for “ensuring inclusive and equitable quality education and promoting lifelong learning opportunities for all”. Despite international efforts to achieve such a goal, many students with vision impairment (VI) who wish to pursue a degree in computer science face significant challenges and must overcome social and technical obstacles. One challenge is learning how to program as a key skill for pursuing a degree in the field of computer science. This paper explores practical issues in teaching students with VI the basics of programming and presents recommended practices based on a suggested workshop setup. The workshop ran for three weeks, for a total of 60 teaching hours, and involved designing and implementing complete curricula and multi-modal activities to simplify the acquisition of basic programming concepts. Workshop data was collected using several data collection methods—i.e., interviews, observation, questionnaires, performance records, and daily journals. The results indicated an improvement in participants’ programming skills, which was detected through their performance records and final project evaluations. The participants also showed a high interest in learning programming and positive attitudes towards the experience. However, the participants’ experience also involved some challenges such as understanding abstract concepts, code navigation, and some technical issues. The study is hoped to contribute to the literature on education inclusion and to bridge the digital divide in our society.
View
View
Facile Programming
Article
Full-text available
  • May 2012
High-level languages and very high-level languages have been developed to simplify programming. But, programming is still hard for many people especially those from disciplines that are not computer-related. Facile programming implies the modification of programming languages to be easily learnt, remembered, and used by programmers from different disciplines. This is achieved by studying and trying to tackle the practical difficulties that face such programmers. The paper addresses the difficulty of learning, remembering, using, and understanding compilation error messages of common English-like programming languages by programmers who are not fluent in English. To tackle this problem, we developed Arabic versions of LISP and SQL in an attempt to figure out whether developing versions, of common programming languages, that are like natural languages of programmers would improve their programming capability. Syntax errors in the Arabic versions can be detected and the corresponding error messages are produced in Arabic. To encourage the use of these Arabic versions, we also developed translators that can translate programs between the corresponding Arabic and English versions of these programming languages for portability. This paper explains the Arabic version of SQL, but reports results from our experience with the Arabic versions of both LISP and SQL.
View
Performance of Students in Computer Programming: Background, Field of Study and Learning Approach Paradigm
Article
Full-text available
  • Sep 2013
Many factors can be attributed to the high rate of failure in computer programming courses. This paper studies the background of students, their fields of study and learning approaches applied to the study of programming courses. It is worth considering as a major factor and necessary to research into the causes of failure of students in programming courses from the learner perspective. Programming courses form part of the core concentration areas for students especially studying Information Technology (IT) and Computer Science as well as those other fields of study sandwiched with IT in an undergraduate degree programs. Through the use of questionnaires, interviews and focused group, a survey was conducted using one hundred (100) students at the middle and end of the semester. The responses from the three groups of students were compared. Their opinions to the usefulness of their background, field of study and learning approaches toward programming courses were investigated. The needs and concerns about these key factors are highlighted in the survey and discussed thereby leading to the inferences made and then proposed recommendations on the learning approach in relation to the background and field of study of students in computer programming courses in order to improve understanding of programming by students, hence, reducing failure rates.
View
MyProLang - My Programming Language: A Template-Driven Automatic Natural Programming Language
Article
Full-text available
  • Apr 2012
Modern computer programming languages are governed by complex syntactic rules. They are unlike natural languages; they require extensive manual work and a significant amount of learning and practicing for an individual to become skilled at and to write correct programs. Computer programming is a difficult, complicated, unfamiliar, non-automated, and a challenging discipline for everyone; especially, for students, new programmers and end-users. This paper proposes a new programming language and an environment for writing computer applications based on source-code generation. It is mainly a template-driven automatic natural imperative programming language called MyProLang. It harnesses GUI templates to generate proprietary natural language source-code, instead of having computer programmers write the code manually. MyProLang is a blend of five elements. A proprietary natural programming language with unsophisticated grammatical rules and expressive syntax; automation templates that automate the generation of instructions and thereby minimizing the learning and training time; an NLG engine to generate natural instructions; a source-to-source compiler that analyzes, parses, and build executables; and an ergonomic IDE that houses diverse functions whose role is to simplify the software development process. MyProLang is expected to make programming open to everyone including students, programmers and end-users. In that sense, anyone can start programming systematically, in an automated manner and in natural language; without wasting time in learning how to formulate instructions and arrange expressions, without putting up with unfamiliar structures and symbols, and without being annoyed by syntax errors. In the long run, this increases the productivity, quality and time-to-market in software development.
View
Programming: Factors that Influence Success
Conference Paper
Full-text available
  • Jan 2005
This paper documents a study, carried out in the academic year 2003-2004, on fifteen factors that may influence performance on a first year object-oriented programming module. The factors included prior academic experience, prior computer experience, self-perception of programming performance and comfort level on the module and specific cognitive skills. The study found that a student's perception of their understanding of the module had the strongest correlation with programming performance, r=0.76, p‹0.01. In addition, Leaving Certificate (LC) mathematics and science scores were shown to have a strong correlation with performance. A regression module, based upon a student's perception of their understanding of the module, gender, LC mathematics score and comfort level was able to account for 79% of the variance in programming performance results.
View
Contributing to success in an introductory computer science course: A study of twelve factors
Conference Paper
Full-text available
  • Mar 2001
This study was conducted to determine factors that promote success in an introductory college computer science course. The model included twelve possible predictive factors including math background, attribution for success/failure (luck, effort, difficulty of task, and ability), domain specific self-efficacy, encouragement, comfort level in the course, work style preference, previous programming experience, previous non-programming computer experience, and gender. Subjects included 105 students enrolled in a CS1 introductory computer science course at a midwestern university. The study revealed three predictive factors in the following order of importance: comfort level, math, and attribution to luck for success/failure. Comfort level and math background were found to have a positive influence on success, whereas attribution to luck had a negative influence. The study also revealed by considering the different types of previous computer experiences (including formal programming class, self-initiated programming, internet use, game playing, and productivity software use) that both a formal class in programming and game playing were predictive of success. Formal training had a positive influence and games a negative influence on class grade.
View
A Survey of Arabic Language Support in Semantic Web
Article
Full-text available
  • Nov 2010
Information availability is a key factor in the acquisition of knowledge. Access to information either in the general area or even in more specific ones like sciences, languages, and religion become wider since the use of semantics in World Wide Web. Semantic Web technologies assist in the acquiring of information by creating processes that link information to another. However, the technology supports mostly languages using Latin family scripts. Arabic is still not well supported.This paper, reports on the survey of the support for Arabic in some of the existing Semantic Web technologies, and give future scenario in applying Semantic Web for Arabic applications. Finally, multilingual support for these new technologies is also discussed.
View
Comprehensive Assessment on Factors Affecting Students' Performance in Basic Computer Programming Course towards the Improvement of Teaching Techniques
Article
  • Mar 2013
Learning how to program correctly is a challenging task for both the students and the instructors. In this regard, basic computer programming course’s instructors play a significant role for the students, as what they will learn in an introductory course will be the foundation for their further programming studies. This paper studies the factors of both instructors and students that affect the latter’s performance in the basic computer programming course offered by the Information Technology Department (IT Department) of King Saud University (KSU). A questionnaire was distributed to and retrieved from target respondents for data collection. Frequency count and chi-square test were used to analyze the responses gathered. Results showed that there is no significant relationship between the students’ factors and instructors’ factors as perceived by students in the course. However, the respondents noted the most important to least important factors that will assist the university and its faculty to concentrate on the areas that needs to be maintained and areas that needs to improve in teaching and learning process which will lead to the improvement of teaching techniques in computer programming courses but also continuous provision of quality education in Saudi Arabia.
View
The effect of student attributes on success in programming
  • Jan 2001
  • 49-52
  • P Byrne
  • G Lyons
Byrne, P., and Lyons, G., "The effect of student attributes on success in programming", ACM SIGCSE Bulletin, 2001, pp. 49-52.
Self-efficacy and mental models in learning to program
  • Jan 2004
  • 171-175
  • Deborah Vennila Ramalingam
  • Susan Labelle
  • Wiedenbeck
Vennila Ramalingam, Deborah LaBelle, and Susan Wiedenbeck, "Self-efficacy and mental models in learning to program", SIGCSE conference on Innovation and technology in computer science, 2004, pp. 171 -175.