Treffer: The Influence of Scaffolding for Computational Thinking on Cognitive Load and Problem-Solving Skills in Collaborative Programming

Title:
The Influence of Scaffolding for Computational Thinking on Cognitive Load and Problem-Solving Skills in Collaborative Programming
Language:
English
Authors:
Yoonhee Shin, Jaewon Jung (ORCID 0000-0003-2282-0379), Seohyun Choi, Bokmoon Jung
Source:
Education and Information Technologies. 2025 30(1):583-606.
Availability:
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed:
Y
Page Count:
24
Publication Date:
2025
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
DOI:
10.1007/s10639-024-13104-0
ISSN:
1360-2357
1573-7608
Entry Date:
2025
Accession Number:
EJ1457890
Database:
ERIC

Weitere Informationen

This study investigates the effects of metacognitive and cognitive strategies for computational thinking (CT) on managing cognitive load and enhancing problem-solving skills in collaborative programming. Four different scaffolding conditions were provided to help learners optimize cognitive load and improve their problem-solving abilities. A total of 110 participants were randomly assigned to one of the four groups. The four-week experiment included scaffolding, with two hours of Python programming each week to solve two real-world problems. Upon completing the learning process, participants' cognitive load and problem-solving skills were assessed. The results provide empirical evidence that using faded worked examples (WOE) combined with metacognitive scaffolding for CT effectively optimizes cognitive load and enhances problem-solving skills in collaborative programming, leading to improved efficiency and complexity in their solutions.

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