Artificial Intelligence Application in Teaching Trigonometry in a Rural Learning Context

Abstract

This research examined the effectiveness of Artificial Intelligence (AI) in enhancing the performance of Grade 9 students at a rural school on their trigonometry tests. A quasi-experimental design using control and treatment groups was used, where one group received traditional instruction and the other received AI-enhanced instruction. A validating 30-item, researcher-designed test was the primary instrument used to collect data for this investigation. The instrument received content validation from both mathematics educators and research experts. Reliability was established with Kuder-Richardson Formula 20 (KR-20), yielding a coefficient value of 0.84, indicating good reliability of the instrument. The findings of this study show that students receiving AI-assisted instruction showed greater improvement than those receiving traditional instruction, especially in conceptual understanding, problem solving, and engagement. The AI tools used in this study provided immediate feedback, guided explanations, and supported students in developing an understanding of abstract concepts found in trigonometry through affordances of technology (immediate feedback, guidance, support). Additionally, the findings of this study point to the fact that teacher facilitation, readiness of learners, and availability of technological resources in the rural school environment affected the success of integrating AI into instruction.This study concludes that AI-enhanced instruction may be used as a supplement to a more effective method of teaching mathematics when it is incorporated with effective pedagogy. In addition, the study highlights the importance of technology being used in context, the teacher being prepared to use the technology, and the institution being supportive of the use of technology in order for students in rural schools to benefit from AI-enabled learning.