Effect of Groups Size on Students' Learning Achievement, Motivation, Cognitive Load, Collaborative Problem-Solving Quality, and In-Class Interaction in an Introductory AI Course

Autor/inn/en	Zhan, Zehui; He, Guoqing; Li, Tingting; He, Luyao; Xiang, Siyu
Titel	Effect of Groups Size on Students' Learning Achievement, Motivation, Cognitive Load, Collaborative Problem-Solving Quality, and In-Class Interaction in an Introductory AI Course
Quelle	In: Journal of Computer Assisted Learning, 38 (2022) 6, S.1807-1818 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zhan, Zehui)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0266-4909
DOI	10.1111/jcal.12722
Schlagwörter	Cognitive Ability; High School Students; Cooperative Learning; Artificial Intelligence; Robotics; Computer Science Education; Problem Solving; Teaching Methods; Learning Motivation; Behavior Patterns; Group Dynamics; Academic Achievement; Classroom Communication; Introductory Courses + Suchen Sie Ihr Suchwort? Denkfähigkeit; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Kooperatives Lernen; Künstliche Intelligenz; Robotertechnik; Computer science lessons; Informatikunterricht; Problemlösen; Teaching method; Lehrmethode; Unterrichtsmethode; Motivation for studies; Lernmotivation; Gruppendynamik; Schulleistung; Klassengespräch; Einführungskurs
Abstract	Background: Group size is one of the important factors that affect collaborative learning, however, there is no consensus in the literature on how many students should the groups be composed of during the problem-solving process. Objectives: This study investigated the effect of group size in a K-12 introductory Artificial Intelligence course by comparing the students' cognitive load, learning motivation, collaborative problem-solving quality, and in-classroom interaction between two- and three-student groups. Methods: Forty-eight high school students were randomly assigned to two kinds of groups (i.e., the two-student group, and the three-student group, each consisting of 24 students). During the experiment, Xiaofei robots were used to teach the theoretical and practical content of five AI topics over 6 weeks for 1.5 h each week. Results: The ANOVA results indicated that group size mattered in the AI course, the two-student group was more effective in terms of enhancing students' learning motivation and collaborative problem-solving quality, as well as imposing more cognitive load than the three-student group. The advantage was more obvious in the practical problem context. The Lag Sequential Analysis results indicated that more collaborative learning behavioural sequences existed in the two-student group than in the three-student groups. Contribution: This research provides empirical evidence and potential guidance for group design in Artificial Intelligence Education. Although group size did not affect students' learning achievement, it affected learning motivation, cognitive load, and problem-solving quality and processes. Two-student groups work better than three-student groups in the AI course. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01