Augmenting Learning Environments Using AI Custom Chatbots: Effects on Learning Performance, Cognitive Load, and Affective Variables

Autor/inn/en	Julia Lademann; Jannik Henze; Sebastian Becker-Genschow
Titel	Augmenting Learning Environments Using AI Custom Chatbots: Effects on Learning Performance, Cognitive Load, and Affective Variables
Quelle	In: Physical Review Physics Education Research, 21 (2025) 1, Artikel 010147Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Zusatzinformation	ORCID (Julia Lademann) ORCID (Jannik Henze) ORCID (Sebastian Becker-Genschow)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
Schlagwörter	Forschungsbericht; Artificial Intelligence; Man Machine Systems; Natural Language Processing; Technology Uses in Education; Instructional Materials; Elementary School Students; Grade 6; Science Instruction; Physics; Foreign Countries; Student Attitudes; Psychological Patterns; Cognitive Processes; Difficulty Level; Self Efficacy; Germany + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Mensch-Maschine-System; Natürliche Sprache; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Lehrmaterial; Lehrmittel; Unterrichtsmedien; School year 06; 6. Schuljahr; Schuljahr 06; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Physik; Ausland; Schülerverhalten; Cognitive process; Kognitiver Prozess; Schwierigkeitsgrad; Self-efficacy; Selbstwirksamkeit; Deutschland
Abstract	This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating topic-related learning material. The study assesses the impact of learning with AI-generated explanations as Supplemental Material on the learning experiences and performance of sixth-grade students, with a particular focus on proportional relationships in mathematical and physical contexts. The randomized controlled study with N=2?1?4 students compared supplementary learning material in the form of traditional textbook material with explanations previously generated by an AI custom chatbot. The results demonstrated that while the AI-generated materials had an indefinite impact on learning outcomes, they significantly enhanced positive-activating emotions, situational interest, and self-efficacy while reducing intrinsic and extrinsic cognitive load. These findings underscore the potential of AI to transform educational practices by fostering a superior learning experience. However, further research is required to clarify its impact on learning performance and long-term learning outcomes. The study highlights the importance of careful integration and customization of AI tools to maximize their benefits in physics education. (As Provided).
Anmerkungen	American Physical Society. One Physics Ellipse 4th Floor, College Park, MD 20740-3844. Tel: 301-209-3200; Fax: 301-209-0865; e-mail: assocpub@aps.org; Web site: https://journals.aps.org/prper/
Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2025/3/08