Artificial Intelligence-Based Tutoring to Strengthen Proportional Reasoning in First-Semester Students
DOI:
https://doi.org/10.70171/b4pxp193Keywords:
educational intervention, mathematical thinking, intelligent tutoring systemsAbstract
Justification: Deficiencies in proportional reasoning with which students enter higher education affect the understanding of more complex content; therefore, pedagogical strategies are required to help overcome these difficulties. Objective: To evaluate the effectiveness of artificial intelligence–based tutoring in strengthening proportional reasoning among first-semester students at a public university in the province of Manabí, Ecuador. Methodology: A quantitative approach with a descriptive-comparative scope was adopted, using a pre-experimental pretest–posttest design with two groups. The sample consisted of 78 students. The intervention involved tutoring supported by artificial intelligence tools, structured in two stages: prior knowledge construction and proportional problem solving. Data were collected using two performance tests designed to assess the identification, structuring, and application of proportional relationships. Results: After the pedagogical intervention, the results showed a shift toward higher performance levels in both groups, with a reduction in the low level and a significant increase in the high level. Specifically, improvements were observed in the identification, structuring, and application of proportional relationships; however, the change in identification was less pronounced. Inferential analyses revealed statistically significant differences between the pretest and posttest (p < .001), with large effect sizes. Conclusion: Artificial intelligence–based tutoring strengthened proportional reasoning among the first-semester students who participated in this study.
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