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Learning programming is not an easy task and students often find this course difficult to understand and pass. A fundamental factor which affects students’ performance is their learning efficacy and motivation. In the classroom, educators know how to motivate their students and how to exploit this knowledge to optimize their teaching when a student shows demotivation signs. In eLearning environments it is much more difficult to evaluate student motivation level. The study identified 19 research papers in teaching and learning programming using eLearning. The papers are derived from a number of digital databases which were published in the last two decades. This study found that a majority of the research in eLearning focuses on student knowledge and skills in programming. To motivate the student, visualization, simulation, animation and game-based approaches have been used in the learning process. These approaches focus on making the interaction attractive rather than identifying and diagnosing student motivation state in the eLearning systems. To enhance the learning process in programming using eLearning, student motivation model needs to be considered.
An Empirical Study: Learning Programming Using eLearning
Rajermani Thinakaran*1, Rosmah Ali2
1Faculty of Engineering, Science and Tehnology, Nilai University,
No. 1, Persiaran Universiti, Putra Nilai, 71800, Nilai, Negeri Sembilan, Malaysia
2Advanced Informatics School, Universiti Teknologi Malaysia International Campus,
Jalan Semarak, 54100, Kuala Lumpur, Malaysia
*Rajermani Thinakaran
Abstract: Learning programming is not an easy task and students often find this course difficult to understand
and pass. A fundamental factor which affects students’ performance is their learning efficacy and motivation. In
the classroom, educators know how to motivate their students and how to exploit this knowledge to optimize
their teaching when a student shows demotivation signs. In eLearning environments it is much more difficult to
evaluate student motivation level. The study identified 19 research papers in teaching and learning programming
using eLearning. The papers are derived from a number of digital databases which were published in the last
two decades. This study found that a majority of the research in eLearning focuses on student knowledge and
skills in programming. To motivate the student, visualization, simulation, animation and game base approaches
have been used in the learning process. These approaches focus on making the interaction attractive rather than
identified and diagnose student motivation state in the eLearning. To enhance the learning process in
programming using eLearning, student motivation model needs to be considered.
Keywords: eLearning, programming.
1. Introduction
Programming defined as the skill of writing code to instruct computers in a certain language
with logical grammar to execute certain task in a computer environment (Anastasiadou & Karakos,
2011). Programming become a compulsory subject in various undergraduate courses and normally
taught in the first year. It is a necessary skill that must be mastered by these students. The
programming subject requires students to understand the programming process stages which consists
of problem definition, designing, coding, debugging and maintenance. The subject also demands
complex cognitive skills such as reasoning, problem-solving and planning which must be understood
and mastered by these students.
However, teaching and learning programming is not an easy task as mentioned by many
studies. While students find this subject difficult to understand and pass due to the required skills. The
failure rate for programming subjects and dropout rate from the course has been in the accumulative
trend and was confirmed worldwide (Gálvez et. al., 2009; Hwang et. al., 2012; Kose & Kose, 2012; Moreno,
2012; Othman, 2013; Tuparov et. al., 2012).
To address these issues, different researches and educators come out with different
approaches to engage the students in learning activities and continue their studies. One of the
approaches is based on the computer-based learning or eLearning (electronic learning).
2. eLearning Environments
Over the last two decades, the invention in eLearning has been growing rapidly due to
advancement in computer and internet technology. eLearning also known as computer-based learning
that includes standalone educational, web-based, mobile learning, computer game-based learning and
augmented reality learning. It can be applied to big and wide variety groups of students, without the
restrictions of place and time.
VanLehn (2011) identified two types of eLearning which are Computer-Based Instruction
(CBI) and Intelligent Tutoring Systems (ITS). In CBI, the students must solve the problems with their
heads or on paper and then enter the answers. Feedbacks and/or hints will be provided based on the
students answers. CBI usually referred as answer-based tutor because it is unaware of any of the
students reasoning or thought processes (Fig. 1).
Figure 1: CBI Learning Process
Chrysafiadi and Virvou (2013) have pointed out that CBI has several limitations when related
to actual classroom teaching. The limitations such as lack of adaptive and contextual support, lack of
flexible support of the delivery and feedback, lack of the cooperative support between student and
system. Therefore, to overcome the CBI limitations, researches(Dehkourdy et. al., 2013) expanded
their interests on ITS.
ITS known as step-based tutor which allows the students to enter information for each step of
the problem solving process just as they might if they were solving the problem on paper. The
feedbacks and hints will be provided based on the analysis of the responses to each problem solving
step by the students. In recent years, the development and improvement of ITS has been growing
inexorably with involvements multidisciplinary expertise from knowledge representation, psychology,
databases, artificial intelligence, software engineering and user interfaces. ITS typically refers to
(Dehkourdy et. al., 2013): (1) a problem solving system that can support and assist to give feedbacks
and suggestions to students; (2) model tracing that guesses the student present mastery and possible
next step in order to support problem solving; (3) knowledge tracing that evaluates the student
capabilities and concept-mastery in order to give new tutorial or topics to learn; and finally, (4)
tutorial conversations for support problem solving.
3. Programming Tutoring Tools
For quite number of students, grapping the concetpt of writing computer programs is a
problem. For decades, researchers and educators have invented various approaches to overcome the
intended problems. One of the approaches is using Programming Tutoring Tools (PTTs) in eLearning
environment. This PPT is derived from ITS. This idea is to create a learning process where students
can receive tutelage, resolve exercises and receive instant feedbacks that tries to imitate one-to-one
human based tutoring.
Some of the identified PTTs that are discussed in this paper are actually based on a through
search from significant papers that were published in quality journals or have been presented at
significant international conferences. In addition these PPTs have been assessed by their particular
PPT such as ADIS (Warendorf & Tan, 1997) and IList (Fossati, 2008) developed as a
teaching aid for Data Structures course to enhance students understanding on related topics such as
linked-lists, stacks, queues, trees and graphs.
J-LATTE (Holland et. al., 2009) and @KU-UZEM (Kose & Deperlioglu, 2012) developed to
teach programming language such as Java and C in terms of design and syntax. OOPS (Gálvez et. al.,
2009) and CIMEL ITS (Moritz et. al, 2005) are tutoring systems which covers the Object- Oriented
Programming topics. WebTasks (Rößling & Karakos, 2008) and ALLIGATOR (Mosconi et. al., 2003)
are web-based system build to engage students with an active learning environment by providing
them with multiple informative and tutoring feedback components. WebTasks designed for
submitting, testing, and discussing student solutions on Java programming. The platform supports
multiple choice questions, type in the missing method tasks, and uploads solution for Java class.
ALLIGATOR, a visual programming environment which allows students without any
particular programming skills to build their own systems, by connecting to a web site and visually
composing data-flow diagrams. OCLS (Othman et. al., 2013) to support the teaching and learning of
the introductory programming course with the objective to provide supporting virtual learning aids to
the students to promote active learning. COLLEGE (Bravo et. al., 2005) was developed for facilitating
collaborative programming learning. Editing or revising, compiling of the source code, and executing
of the object programs are the main features of the system. The system also provides a collaborative
support that comprised of an instant messaging tool and a decision-making tool. In addition, the
system offers awareness functionalities to facilitate the perception and carrying out of group work.
INCOM (Lee et. al., 2009) and AutoLEP (Wang et. al., 2011) designed to help novice
students in logic programming and to attain their programming skills. INCOM coach students
individually as they solve their homework assignments to better prepare them for subsequent
classroom activities. Upon request, the system informs the student about possible errors occurring in
their solution attempts and provides correction hints to improve their solutions. While through
AutoLEP, the system helped the students to adequately test and evaluate the programs.
ProBot (Moreno, 2012) using digital game concept to reinforce and improve students abilities
in programming control structures. The system detects student errors and misconceptions
automatically by the interface to carry semantic validation. The progressive difficulty levels are
designed base in the same order as in the course outline. LOs (Tuparov et. al., 2012), is simulation-
based learning object for introductory programming course. This system was developed to help the
students to understand the learning content and increased the students motivation regarding the course
in self-regulated learning.
Marmoset (Spacco et. al., 2006) is a Java programming project submission and testing system.
The system also helps the instructor to monitor student progress on a programming assignment at any
time. EduJudge (Verdú, 2012) was developed based on integration of a submission system with a
virtual learning environment of references. The system allows for the submission, management and
automatic evaluation of programming exercises and the development of competitions as part of a
Moodle course. WPAS (Hwang et. al., 2012) designed for supporting programming learning activities
with various difficulty levels. PASS (Law et. al., 2010) as a program submission/assessment system
with the primary aim to assisting beginners in learning programming.
4. Discussion
From the number of PTTs have been stated in the Section 3 all the tutoring tools used
multimedia resources to engage the students. The tools used games, visualization, simulation and
animation to deliver the lesson. Some PTTs integrate with automated assessment and learning
management features to support the learning process. Automated assessment supports a variety of
evaluation formats such as assignment, quiz and test. In conjunction it provides an automatic feedback
and monitor student learning progress.
K. Chrysafiadi and M. Virvou (2013) suggested that to become more adaptive or personalized
tutoring tools, student characteristics need to be considered. They are a number of students
characteristics that have been identified which are knowledge and skills, errors and misconceptions,
learning styles and preferences, affective and cognitive factors, motivation and meta-cognitive factors
(Thinakaran & Ali, 2014). From the identified PTTs which as discussed in Section 3, all the tutoring
tools were designed to improve student knowledge and skills. Some of these tutoring tools used errors
and misconceptions characteristic in the learning process to improve programming knowledge.
Another important student characteristic is motivation, since motivation is considered as one
of the key factors that lead student performance. In PTTs, motivation has been seen as a matter of
design. Although designing motivating PTTs is important, keeping students motivated for the whole
learning period is one of the main challenges. Due to the importance of motivation, there are number
of researches to detect motivation state in eLearning. Table 1 presents previous research work on
assessing motivation in eLearning and features that indicate the presence of motivation.
Table 1: Previous Research Work on Assessing Motivation in eLearning
Motivation factors
del Soldato & du Boulay
Effort, Confidence &
de Vicente & Pain
Effort, Confidence &
Zhang et al. (2003)
Attention & Confidence
Beck (2004)
Qu & Johnson (2005)
Confidence, Confusion &
Kim et al. (2007)
Confidence & Effort
Hershkovitz &
Nachmias (2008)
Engagement, Energization &
Takemura et. al. (2008)
Importance & Expectation
Cocea & Webelzahi
Engagement, Self-Esteem,
Self-Regulation & Goal
Ramaha & Ismail (2012)
Confidence, Effort &
Law et. al. (2010)
Self-Efficacy, Reward And
Recognition, Individual
Attitude and Expectation,
Effect & Clear Direction
Park & Kim (2011)
Self-Efficacy, Goal
Orientation, Task Value &
5. Conclusion
Writing programming involves planning, designing, testing and debugging. To learn on how
to develop a program, students need to understand the programming language syntax. Difficulty to
understand program logic and the concept often lead to student frustration and lack of motivation to
learn programming. Finally, these issues contribute to the high rate of dropouts in computing courses.
From the studies (Section 3), PTT has been used to assist students in their programming learning
process. The studies also found that motivation has been seen as a matter of design. Since motivation
is an important factor in learning, a motivation model to detect student motivation needs to be
included in tutoring systems. This motivation model can bring many benefits such as detects student
motivation state and provides learning materials according to students motivation state. Include the
motivation model in PTTs, the PTTs can become more adaptive, personalized and tailored to the
students learning process more effectively.
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... В то же время, обучение компьютерным наукам и программированию относят к довольно сложным задачам, требующим от обучающихся интенсивного выполнения упражнений [9] в специализированном программном обеспечении (компиляторах, терминалах, интегрированных средах разработки (ИСР)) [10]. Соответствующие образовательные курсы имеют достаточно высокий процент отсева и неуспеваемости обучающихся [11][12][13][14][15], особенно в первый год обучения [16,17] из-за сложностей в понимании логики конструирования компьютерных программ и синтаксиса языков программирования [18]. ...
... Дисциплину «Технологии веб-доступности» необходимо включить как отдельный предмет (цикл или модуль) в учебные планы бакалавриата направлений подготовки, выпускающих преподавателей ИТ-дисциплин, веб-разработчиков и веб-дизайнеров, для формирования компетенций, соответствующих российским профессиональным стандартам [41, 42]. гиперссылки представлены в виде текста, определяющего точное и однозначное направление перехода 9 (13,8) 6 (9,2) 3 (4,6) 5 (7,7) 8 (12,3) 3 (4,6) 12 (18,5) 19 (29,2) обеспечен достаточный контраст между фоном и текстом 4 (6,2) 5 (7,7) 0 (0,0) 0 (0,0) 24 (36,9) 21 (32,3) 4 (6,2) 7 (10,8) ...
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