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

Title:
Integrating Computational Thinking Diagnostic Mechanism and Reflective Learning: An Innovative Approach to Enhance Learning Outcomes in Introductory Programming.
Source:
Journal of Computer Assisted Learning. Oct2025, Vol. 41 Issue 5, p1-19. 19p.
Geographic Terms:
Database:
Education Research Complete

Weitere Informationen

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. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)