Integrating Computational Thinking Diagnostic Mechanism and Reflective Learning: An Innovative Approach to Enhance Learning Outcomes in Introductory Programming

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Bibliographic Details
Title: Integrating Computational Thinking Diagnostic Mechanism and Reflective Learning: An Innovative Approach to Enhance Learning Outcomes in Introductory Programming
Language: English
Authors: Ting-Ting Wu (ORCID 0000-0003-4970-7042), Hsin-Yu Lee (ORCID 0000-0003-3257-305X), Pei-Hua Chen (ORCID 0009-0002-0431-4499), Wei-Sheng Wang (ORCID 0000-0003-1263-4820), Yueh-Min Huang (ORCID 0000-0001-7052-1272)
Source: Journal of Computer Assisted Learning. 2025 41(5).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 19
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Computation, Thinking Skills, Educational Diagnosis, Diagnostic Tests, Programming, Computer Science Education, Introductory Courses, Programming Languages, Undergraduate Students, Critical Thinking, Problem Solving, Creativity
DOI: 10.1111/jcal.70121
ISSN: 0266-4909
1365-2729
Abstract: Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its potential application as a diagnostic instrument for reflection remains insufficiently explored within programming education. Objectives: This study aims to develop and evaluate a CT-based diagnostic reflective report system as a technological intervention to facilitate structured reflective learning in programming education. Furthermore, it investigates the impact of this system on knowledge construction, higher-order thinking skills (HOTS), and project performance within an introductory Python programming course. Methods: The study employed a quasi-experimental design spanning two academic semesters, involving 82 undergraduate students randomly assigned to experimental (n = 42) and control (n = 40) groups. The experimental group utilised weekly CT-based diagnostic reflective reports, whilst the control group engaged in traditional reflective practises. The curriculum integrated Python programming with Raspberry Pi embedded systems. Assessment measures included pre- and post-tests for knowledge construction, a validated questionnaire for HOTS evaluation, and the Creative Product Analysis Matrix (CPAM) for project performance assessment. Results and Conclusions: Implementation of the CT-based diagnostic reflective report system demonstrated statistically significant improvements in knowledge construction, critical thinking, and problem-solving skills compared to traditional approaches. Project performance metrics, including valuable, logical, useful, understandable, and well-crafted, showed marked enhancement. However, no significant impact was observed regarding creativity. These findings substantiate the efficacy of integrating CT diagnostic mechanisms with reflective learning practises.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1484310
Database: ERIC
Description
Abstract:Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its potential application as a diagnostic instrument for reflection remains insufficiently explored within programming education. Objectives: This study aims to develop and evaluate a CT-based diagnostic reflective report system as a technological intervention to facilitate structured reflective learning in programming education. Furthermore, it investigates the impact of this system on knowledge construction, higher-order thinking skills (HOTS), and project performance within an introductory Python programming course. Methods: The study employed a quasi-experimental design spanning two academic semesters, involving 82 undergraduate students randomly assigned to experimental (n = 42) and control (n = 40) groups. The experimental group utilised weekly CT-based diagnostic reflective reports, whilst the control group engaged in traditional reflective practises. The curriculum integrated Python programming with Raspberry Pi embedded systems. Assessment measures included pre- and post-tests for knowledge construction, a validated questionnaire for HOTS evaluation, and the Creative Product Analysis Matrix (CPAM) for project performance assessment. Results and Conclusions: Implementation of the CT-based diagnostic reflective report system demonstrated statistically significant improvements in knowledge construction, critical thinking, and problem-solving skills compared to traditional approaches. Project performance metrics, including valuable, logical, useful, understandable, and well-crafted, showed marked enhancement. However, no significant impact was observed regarding creativity. These findings substantiate the efficacy of integrating CT diagnostic mechanisms with reflective learning practises.
ISSN:0266-4909
1365-2729
DOI:10.1111/jcal.70121