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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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American Physical Society
2025-05-01
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| Series: | Physical Review Physics Education Research |
| Online Access: | http://doi.org/10.1103/PhysRevPhysEducRes.21.010147 |
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| _version_ | 1849313600563314688 |
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| author | Julia Lademann Jannik Henze Sebastian Becker-Genschow |
| author_facet | Julia Lademann Jannik Henze Sebastian Becker-Genschow |
| author_sort | Julia Lademann |
| collection | DOAJ |
| description | 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=214 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. |
| format | Article |
| id | doaj-art-ddf4bcf3f1744bb49ad20e095a6db6bc |
| institution | Kabale University |
| issn | 2469-9896 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Physics Education Research |
| spelling | doaj-art-ddf4bcf3f1744bb49ad20e095a6db6bc2025-08-20T03:52:42ZengAmerican Physical SocietyPhysical Review Physics Education Research2469-98962025-05-0121101014710.1103/PhysRevPhysEducRes.21.010147Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variablesJulia LademannJannik HenzeSebastian Becker-GenschowThis 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=214 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.http://doi.org/10.1103/PhysRevPhysEducRes.21.010147 |
| spellingShingle | Julia Lademann Jannik Henze Sebastian Becker-Genschow Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables Physical Review Physics Education Research |
| title | Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables |
| title_full | Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables |
| title_fullStr | Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables |
| title_full_unstemmed | Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables |
| title_short | Augmenting learning environments using AI custom chatbots: Effects on learning performance, cognitive load, and affective variables |
| title_sort | augmenting learning environments using ai custom chatbots effects on learning performance cognitive load and affective variables |
| url | http://doi.org/10.1103/PhysRevPhysEducRes.21.010147 |
| work_keys_str_mv | AT julialademann augmentinglearningenvironmentsusingaicustomchatbotseffectsonlearningperformancecognitiveloadandaffectivevariables AT jannikhenze augmentinglearningenvironmentsusingaicustomchatbotseffectsonlearningperformancecognitiveloadandaffectivevariables AT sebastianbeckergenschow augmentinglearningenvironmentsusingaicustomchatbotseffectsonlearningperformancecognitiveloadandaffectivevariables |