Scaffolding Computer Programming Learners' Self-Regulated Learning in Problem-Solving

• In Event: Computers and Internet Applications in Education SIG Paper Session

Abstract

This study examines the effect of self-regulated learning scaffolds on learners’ cognitive load and problem-solving performance, considering cases from well-structured to ill-structured tasks in a computer programming course. Sixty-seven undergraduates were randomly assigned into one of two groups based on the scaffolding condition. Participants in both groups were asked to solve problems using Python over three weeks, and their cognitive load levels were measured after each week. The results showed that novice learners’ self-regulated learning skills can be influenced by scaffolding, which contributes to complex problem-solving performance. The germane cognitive load of the scaffolding group was higher for well-structured problems than that of the control group. The results provide implications for designing scaffolds for programming courses using problem-based learning.

Authors

• Yoonhee Shin, 21st Century Partnership for STEM Education

• Donggil Song, Sam Houston State University