Keywords:
Artificial Intelligence
Chatbot
Climate Change
Physics Digital Modules
Student Learning Assistants

  • Abstract

    Student learning assistants play a crucial role for students in enhancing the learning experience and understanding to support the achievement of better academic outcomes and prepare for challenges in the real world. Artificial intelligence (AI) assists students in independently discovering concepts based on their interests. However, learning physics concepts related to climate change has primarily concentrated on the outcome aspect, neglecting the process and concept discovery itself. Furthermore, there are still a limited number of empirical studies that discuss the integration of AI with Physics Digital Modules, highlighting potential challenges and weaknesses. The research aims to Develoment of Integrating Artificial Intelligence Chatbot for Climate Change (AIC3) with Physics Digital Modules (PDM) for Student Learning Assistants (SLA). Applied the experimental research method to AIC3 with PDM, which involved 124 undergraduate students enrolled in the environmental physics course as learning assistants. The findings show that AIC3 with PDM is an effective intelligent student assistant for learning basic content in a responsive, interactive and simple manner. According to the research results AIC3 with PDM is an engaging and responsive conversational learning tool for teaching fundamental concepts and providing learning resources for education on Chatbot Climate Change. The highlights the effectiveness of integrating the Artificial Intelligence Chatbot for Climate Change with Physics Digital Modules as a valuable tool for student learning assistants. Present the research findings and discuss the opportunities for further studies, as well as the implications of using AIC3 with PDM to support inclusive learning.

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Wibowo, F. C., Hasbey , H., Aziz , T. A., Darman , D. R., Kusuma, A. F. A. K., Ihsan, I., & Bunyamin , M. A. H. (2025). Integrating Artificial Intelligence Chatbot Climate Change with Physics Digital Modules for Student Learning Assistants. Multidisciplinary Science Journal, (| Accepted Articles). Retrieved from https://malque.pub/ojs/index.php/msj/article/view/6722
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