Integration of Symbolab AI in Problem-Based Learning: Analysis of Students’ Mathematical Reasoning
Abstract
This study aims to determine mathematical reasoning abilities through problem-based learning with the assistance of AI Symbolab on the topic of systems of linear inequalities in two variables. The subjects of the study were class X students at SMA Negeri 1 Palembang. This research is a qualitative descriptive study that uses observation, test, and interview data collection techniques. In analyzing observation data, the researcher will create a brief description based on the results of interviews or field notes. For test data analysis, the researcher will describe the subjects' abilities in mathematical reasoning, and for interview data analysis, the researcher will transcribe the interview results into written form. The research results show that the implementation of problem-based learning on the material of systems of linear inequalities in two variables, assisted by AI Symbolab, can develop students' mathematical reasoning abilities. This is evident from the students' ability to present mathematical statements in writing through mathematical models, propose several conjectures in their answers, conduct mathematical manipulations using AI Symbolab, compile evidence or reasons for the correctness of the solutions to the conjectures put forward, and draw conclusions from the steps they have taken.
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