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.
Nowadays, the quality of learning and the expansion of education technology, motivate the
researchers to work on learning area more than before. Problem statement: With the rapid advance of
learning contents on the web and also the variety of learning books, finding suitable ones has become a
very difficult and complicated task for learners. Approach: This study aims to propose a learning
system includes the semantic recommender system. Students can employ this application to learn
learning content at anywhere. This system works based on the learners knowledge level and also the
learners request that system asks from the learner at the beginning. Learner will be able to find and
learn the right learning materials to reach their request. Finally, all changes about learner will store in
the learner model in the ontology. The proposed architecture comprises some subsystems and
components. One of the most important of subsystems is a knowledge based system, which covers the
ontology which called VBnet ontology. This ontology consists of three parts; LearnerModel, Domain
Concept and Learning Material. Moreover, we define two other subsystems; Learner performance
evaluation, recommendation system and some modules; Availability checker, Knowledge evaluator,
Exam generator, Request analyzer and user interface. Results: Considering to scope of research we
develop the ontology for Visual Basic.Net programming language and describe all available classes
and subclasses step by step. Also we create some query by SPARQL and show the information retrival
from VB ontology. Conclusion: This system can help to student to learn materials of Visual Basic.Net
with the good quality without the place dependency
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