A flowchart‐based intelligent tutoring system for improving problem‐solving skills of novice programmers

TLDR

Intelligent tutoring and personalization are regarded as the two most important factors in learning systems research, and an effective tool to improve problem‑solving ability is an intelligent tutoring system that mimics a human tutor’s one‑to‑one personalized and adaptive teaching. In this paper, a novel Flowchart‑based Intelligent Tutoring System (FITS) is proposed benefiting from Bayesian networks for decision making to aid students in problem‑solving activities and learning computer programming. FITS leverages Bayesian networks and a multi‑agent system with an automatic text‑to‑flowchart conversion approach to engage novice programmers in flowchart development and improve their problem‑solving skills, and a quasi‑experimental design was adopted to investigate its efficacy. Students in the FITS group showed greater improvement in problem‑solving abilities than the control group, and FITS proved especially effective for students with lower prior knowledge.

Abstract

Abstract Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem‐solving ability is an I ntelligent T utoring S ystem which is capable of mimicking a human tutor's actions in implementing a one‐to‐one personalized and adaptive teaching. In this paper, a novel F lowchart‐based I ntelligent T utoring S ystem ( FITS ) is proposed benefiting from B ayesian networks for the process of decision making so as to aid students in problem‐solving activities and learning computer programming. FITS not only takes full advantage of B ayesian networks, but also benefits from a multi‐agent system using an automatic text‐to‐flowchart conversion approach for engaging novice programmers in flowchart development with the aim of improving their problem‐solving skills. In the end, in order to investigate the efficacy of FITS in problem‐solving ability acquisition, a quasi‐experimental design was adopted by this research. According to the results, students in the FITS group experienced better improvement in their problem‐solving abilities than those in the control group. Moreover, with regard to the improvement of a user's problem‐solving ability, FITS has shown to be considerably effective for students with different levels of prior knowledge, especially for those with a lower level of prior knowledge.