Enhancing programming education: The impact of AI-based pedagogical agents on student self-efficacy, engagement, and learning outcomes

In recent years, learning programming has been a challenge for both learners and educators. How to enhance student engagement and learning outcomes has been a significant concern for researchers. This study examines the effects of AI-based pedagogical agents on students' learning experiences in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Educational Technology ＆ Society Jg. 28; H. 2; S. 279 - 294
Hauptverfasser: Lin, Hao-Chiang Koong, Tseng, Chun-Hsiung, Chen, Nian-Shing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: International Forum of Educational Technology ＆ Society 01.04.2025
International Forum of Educational Technology & Society, National Taiwan Normal University, Taiwan
International Forum of Educational Technology & Society
Schlagworte:
Artificial intelligence
Computer programming
Educational aspects
Educational research
Generative artificial intelligence in education: Theories, technologies, and applications
learning experience
pedagogical agent
programming education
self-efficacy
Self-efficacy (Psychology)
Study and teaching
China
Pedagogical agent
Learning experience
Programming education
Artificial intelligence
Self-efficacy
ISSN:1176-3647, 1436-4522, 1436-4522
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In recent years, learning programming has been a challenge for both learners and educators. How to enhance student engagement and learning outcomes has been a significant concern for researchers. This study examines the effects of AI-based pedagogical agents on students' learning experiences in programming courses, focusing on web game development using JavaScript and Phaser. We developed two pedagogical agents: a debugger that provides context-sensitive assistance and a chatbot that offers guidance based on pre-configured Phaser knowledge. The experiment involved 60 sophomore students from a university in southern Taiwan, and they were randomly assigned to control and experimental groups. The study measured changes in students' self-efficacy (creative, persuasive, and change dimensions), JavaScript proficiency, debugging efficiency, and overall engagement. Results show significant improvements in all self-efficacy dimensions and JavaScript proficiency for the experimental group. Debugging log analysis showed that students who used the pedagogical agents were able to fix bugs more quickly and more effectively. Qualitative analysis of student reflections indicated more positive learning experiences and deeper engagement with learning content in the experimental group. These findings suggest that integrating AI-based pedagogical agents can enhance students' learning experiences in programming courses.
ISSN:1176-3647
1436-4522
1436-4522
DOI:10.30191/ETS.202504_28(2).TP02