Abstract
The same learning process in educational systems could be boring and time consuming for some learners. This problem arises from the lack of personalized learning sequence for learners with different knowledge level. Recommender systems play an important role in assisting the learners to find suitable learning materials and personalized learning sequence. Use of ontology for knowledge representation in knowledge-based recommender systems would facilitate sharing, reuse and common terminology. Since programming concepts have logical relationships among together so, traditional education systems are more stressful and very time-consuming. This paper aims to propose an ontology based recommender system to present a Personalized Learning Sequence in Programming (PLSP) domain which is depended to learner's knowledge level. A recommender module and, the knowledge base module are integrated together in the proposed framework. The recommender module as the main module in the framework, has three stages which is working based on semantic rules and ontology representation. Evaluation of the system was carried out by comparing the non-recommender system (web-based search) using 32 ICT respondents. Results demonstrate that the participants who used the proposed system spent 1119 seconds to find the suitable learning path in comparison to those who used a non-recommender system (3480 seconds) in the same learning material. It means that learners who follow learning path with PLSP, are more suitable for them. Furthermore, the average mean value of usability test is 4.47, (5 maximum scale) which indicates that the system proved to be useful, was easy to use, and satisfied the users.
Highlights
IntroductionLearners believe that traditional ways for programming learning add more stress during learning process [1]
Programming language is one of the fundamental courses in computer science filed
The purpose of evaluation is to demonstrate the capability of proposed system and show the efficiency of personalized learning sequence in learning process
Summary
Learners believe that traditional ways for programming learning add more stress during learning process [1]. E-learning systems are expected to provide suitable learning materials for different learners. Studies on learning sequence discovery have done to recommend suitable learning sequence to make a personalized learning environment. It mostly focuses on providing of suitable learning sequence to facilitate learning process [4]. Recommender systems play an important role in assisting the learners to find suitable learning materials and personalized learning sequence. We aim to propose a semantic recommendation system to assist learners to learn main concepts of programming domain in the best way. The valuable characteristics of the proposed system are using ontology to represent the knowledge and give personalized learning path based on knowledge level to learners
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