Instructing with Cognitive Apprenticeship Programming Learning System (CAPLS) for novice computer science college freshmen: An exploration study

• Published in: Educational Technology ＆ Society Vol. 27; no. 2; pp. 183 - 196
• Main Authors: Yu, Chih-Chang, Wu, Leon Yufeng
• Format: Journal Article
• Language: English
• Published: International Forum of Educational Technology ＆ Society 01.04.2024; International Forum of Educational Technology & Society, National Taiwan Normal University, Taiwan; International Forum of Educational Technology & Society
• Subjects: Apprenticeship; blended cognitive apprenticeship; capls; Computer programming; Computer science; computer-assisted learning; Education; Full Length Articles; Learning; learning programming; Methods; student motivation; Study and teaching; Surveys; Teachers; Teaching; Training; Taiwan; Computer-assisted learning; Student motivation; Learning programming; Blended cognitive apprenticeship; CAPLS
• ISSN: 1176-3647; 1436-4522; 1436-4522
• DOI: 10.30191/ETS.202404_27(2).RP07

This study presents a new blended learning model that combines a computer-assisted learning system called Cognitive Apprenticeship Programming Learning System (CAPLS) with instructor co-teaching in an introductory programming course. CAPLS, as its unique aspect, functions as a master in cognitive apprenticeship, guiding learners throughout their learning while also assessing their progress. In contrast, the instructor in physical class settings serves a supportive role, monitoring progress and articulating as needed to fill knowledge gaps. To investigate the impact of this learning model on students' motivation, we used the Motivated Strategies for Learning Questionnaire (MSLQ) at the beginning and end of the semester. College Entrance Math score, midterm and final exams were also used to assess student learning outcomes. The study was conducted with first-year students in the Department of Information and Computer Engineering, and two key findings emerged. First, students' programming proficiency was strongly correlated with their College Entrance Math scores. While math ability impacted programming learning, all students improved their final scores compared to their midterms, with high-scoring math students outperforming their peers. Second, the proposed blended cognitive teaching strategy significantly reduced students' extrinsic goal and self-efficacy levels, but their learning outcomes still significantly improved. This suggests that the proposed teaching model promotes more conscious learning. These results can be used as a reference for improving student learning outcomes and experiences with computer-assisted learning systems.