Modeling a Problem-Solving Approach Through Computational Thinking for Teaching Programming

• Published in: IEEE transactions on education Vol. 67; no. 2; pp. 1 - 0
• Main Authors: Tareq, Zebel-Al, Yusof, Raja Jamilah Raja
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active learning; approach model; Computational modeling; computational thinking (CT); computer science; computing skills; Conferences; Control Groups; Education; Game theory; game-based learning (GBL); Problem based learning; Problem solving; problem-based learning (PBL); problem-solving instructional methods; Programming; Programming profession; Questions; Software algorithms; Sorting; sorting algorithm; Sorting algorithms; Students; Syntax; syntax-based learning (SBL); Teaching methods; Workshops
• ISSN: 0018-9359; 1557-9638
• DOI: 10.1109/TE.2024.3354425

Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being able to formulate an algorithmic solution computationally and then transform it into code is essential for students. Research Questions: What are the effective teaching approaches for fostering the development of problem-solving and programming skills? How do CT concepts contribute to the formulation of a PSA model for programming problems and its translation into an effective teaching method? How can an effective teaching method that utilizes the PSA model be identified and distinguished from other approaches? Methodology: A preliminary study pointed out the difficulties experienced when teaching programming, inspiring the formulation of a PSA model that used CT concepts. An experimental study on problem-based and game-based programming workshops that utilized the PSA model through sorting algorithms was performed on experimental groups consisting of 30 students each. A syntax-based programming workshop consisting of 30 students was used as the control group. All the participants were recruited through a pretest that incorporated basic programming questions. The participants had to answer a posttest after the workshop. Findings: The results showed that the participants exhibited no significant difference between the pretest and posttest for the syntax-based learning (SBL). However, there is a significant difference between the pretest and posttest of both the problem-based learning (PBL) and the game-based learning (GBL) workshops. There was no significant difference significant difference for the pretest scores of all three workshops. The analysis of the posttest further confirmed that the experimental groups (PBL and GBL) exhibited significant difference in the scores compared to the control group. However, the posttest results did not differ significantly between the experimental groups (PBL and GBL).