Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables

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 <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mi>N</a:mi><a:mo>=</a:mo><a:mn>2</a:mn><a:mn>1</a:mn><a:mn>4</a:mn></a:mrow></a:math> 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.

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Publication Details

Journal
Physical Review Physics Education Research
Published
2025-05-07
DOI
https://doi.org/10.1103/physrevphyseducres.21.010147
Citations
10
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
24.81
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article

Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables

Sebastian Becker-Genschow, Jannik Henze, Julia Lademann
10 citations
Physical Review Physics Education Research
Intelligent Tutoring Systems and Adaptive Learning
24.81
article

Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables

Sebastian Becker-Genschow, Jannik Henze, Julia Lademann
article en
10 citations

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 <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mi>N</a:mi><a:mo>=</a:mo><a:mn>2</a:mn><a:mn>1</a:mn><a:mn>4</a:mn></a:mrow></a:math> 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.

Physical Review Physics Education ResearchVol. 21(1)
University of Cologne (DE)
Openalex Percentile: Top 1%
Intelligent Tutoring Systems and Adaptive Learning
24.81
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Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables — Sebastian Becker-Genschow, Jannik Henze, et al. · Physical Review Physics Education Research (2025) | TGRS Research Map | TGRS