Universität zu Köln

Rücker, Cilia Ricarda ORCID: 0009-0002-3673-0745 and Becker-Genschow, Sebastian ORCID: 0000-0002-2461-0992 (2025). Enhancing enthusiasm for STEM education with AI: Domain-specific chatbot as personalized learning assistant. Computers and Education Open, 9. pp. 1-13. Elsevier. ISSN 2666-5573

PDF 1-s2.0-S2666557325000746-main.pdf Bereitstellung unter der CC-Lizenz: Creative Commons Attribution. Download (1MB)

Abstract

[Artikel-Nr.: 100315] Generative AI has been increasingly integrated into educational settings for its potential to facilitate personalized learning. However, evidence-based implementation concepts remain essential to realize its pedagogical value. Therefore, this study investigates the educational efficacy of ADA, a domain-specific AI chatbot customized for secondary mathematics education, in enhancing learning outcomes and student engagement. A cluster- randomized controlled study was conducted with 195 ninth-grade students from German secondary schools in authentic classroom settings. The objective of the study was to compare ADA’s personalized support against conventional differentiation materials. The intervention targeted the Heron method for estimating square roots in a single-lesson intervention with a pre-post assessment. As one of the few cluster-randomized controlled studies on custom AI chatbots in secondary mathematics education, this investigation assessed both affective and cognitive aspects of learning simultaneously to provide a comprehensive research picture. The findings indicated a high degree of student acceptance across the dimensions of the Technology Acceptance Model. Additionally, situational interest significantly improved in the chatbot condition. The study found that trends in performance and emotional responses were favorable, while cognitive load increased slightly. The findings emphasize the evident potential of customized AI chatbots to supplement differentiated instruction in the domain of mathe- matics education. They provide a critical foundation for future research investigating the potential of AI chatbots to enhance student learning through careful integration and customization.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Rücker, Cilia Ricarda UNSPECIFIED https://orcid.org/0009-0002-3673-0745 UNSPECIFIED Becker-Genschow, Sebastian UNSPECIFIED https://orcid.org/0000-0002-2461-0992 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-812461
Identification Number:	10.1016/j.caeo.2025.100315
Journal or Publication Title:	Computers and Education Open
Volume:	9
Page Range:	pp. 1-13
Number of Pages:	13
Date:	December 2025
Publisher:	Elsevier
ISSN:	2666-5573
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Mathematics and Science Education > Institute of Physics Education
Subjects:	Education Physics
Uncontrolled Keywords:	Keywords Language Artificial intelligence ; Chatbot ; Personalization ; Education ; STEM ; Mathematics English
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/81246