aceDesign and Evaluation of an Artificial Intelligence–Based Model for Predicting Twelfth-Grade Students’ Mathematics Performance Based on Individual, Educational, and Learning Technology Factors
Purpose: This study aimed to design and evaluate an artificial intelligence–based model for predicting the mathematics performance of twelfth-grade experimental sciences students based on individual, educational, and learning technology factors. Methods and Materials: This applied, quantitative, cross-sectional, and predictive study was conducted among twelfth-grade experimental sciences students in Isfahan, Iran. A total of 187 questionnaires were distributed, and after removing incomplete, inconsistent, and in…
A gradient boosting model combining prior achievement, psychological, instructional and learning-technology factors predicted twelfth-grade math scores with acceptable accuracy.
The final analysis rests on only 84 students from one city's twelfth-grade experimental sciences cohort, and validation was internal, which limits how far the findings generalize.
Evidence
- Peer-reviewedInternational Journal of Education and Cognitive Sciences2026-11-01
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Truvace Impact Record TRV-2026-1363, v1: “Design and Evaluation of an Artificial Intelligence–Based Model for Predicting Twelfth-Grade Students’ Mathematics Performance Based on Individual, Educational, and Learning Technology Factors.” Truvace, 2026-10-14. /record/TRV-2026-1363 (accessed at citation time). sha256 2dfc8018ebdeeb53…
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