SITS: A solution-based intelligent tutoring system for students’ acquisition of problem-solving skills in computer programming

Danial Hooshyar, Rodina Binti Ahmad, Moslem Yousefi, Moein Fathi, Shi Jinn Horng, Heuiseok Lim

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Abstract In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor’s actions in implementing one-to-one adaptive and personalised teaching. Thus, in this research, a solution-based intelligent tutoring system (SITS) is proposed. It benefits from Bayesian networks in managing uncertainty based on the probability theory for the process of decision-making so as to aid students learn computer programming. Additionally, SITS benefits from a multi-agent system that employs an automatic text-to-flowchart conversion approach to engage novice programmers in flowchart development with the aim of improving their problem-solving skills. Finally, the performance of SITS is investigated through an experimental study. It is revealed that SITS is not only capable of boosting students’ learning interest, attitude and technology acceptance, but it also helps students achieve more in terms of problem-solving activities.

Original languageEnglish
Pages (from-to)325-335
Number of pages11
JournalInnovations in Education and Teaching International
Volume55
Issue number3
DOIs
Publication statusPublished - 2018 May 4

Keywords

  • Problem-solving skills
  • computer programming
  • flowchart development
  • intelligent tutoring system

ASJC Scopus subject areas

  • Education

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