The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming

被引：0

作者：

Shin, Yoonhee ^{[1
]}

Jung, Jaewon ^{[2
]}

Choi, Seohyun ^{[1
]}

Jung, Bokmoon ^{[3
]}

机构：

[1] Hanyang Univ, Coll Educ, Wangsimni Ro 222, Seoul, South Korea

[2] Korean Educ Dev Inst, 7 Gyohak Ro, Jincheon Gun, Chungcheongbuk, South Korea

[3] Korea Natl Univ Educ, 241-20 Hanguktongsin Ro, Gurye Gun, Jeollanam Do, South Korea

来源：

EDUCATION AND INFORMATION TECHNOLOGIES | 2024年

关键词：

Higher education; Computational thinking; Cognitive load; Problem-solving; Collaborative programming; WORKED EXAMPLES; STUDENTS;

D O I：

10.1007/s10639-024-13104-0

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

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.

引用

页数：24

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