Improving Science Conceptual Understanding and Attitudes in Elementary Science Classes through the Development and Application of a Rule-Based AI Chatbot

Abstract

Abstract This study aimed to develop a specialized rule-based AI chatbot tailored for a sixth-grade optics unit and to evaluate the impact of the implementation of the chatbot on students’ cognitive and affective outcomes related to science within the classroom setting. Specifically, this study explored how factors such as gender and achievement levels have an impact on student attitudes. The development of the rule-based chatbot adhered to the network-based instructional systems design framework, which involves the application of the analyze, design, develop, implement, and evaluate model to the e-learning design and development process. The participants were 192 sixth-grade students, with 81 in the experimental group and 111 in the control group. The results revealed a positive effect on students’ science achievement and interest, with a particularly significant impact on those with lower achievement levels. Notably, the chatbot played a crucial role in elevating the interest of female students in science. These findings highlight the need for continued research into the integration of rule-based AI chatbots in science education.