Volume 4 • Issue 1 • PP: 25–32 • 2025
Educational Value Formation Around Intelligent Learning Tools: Student Readiness, Usage Archetypes, and Support Pathways in Higher Education
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© 2025 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Modern higher education campuses now use intelligent learning tools as standard educational resources, yet students’ learning results depend on their understanding of these tools and their implementation in academic work. The study analyzes how students prepare to use educational tools while investigating the connection between their preparedness and their judgment of educational benefits. The study uses an open student-perception dataset to conduct empirical research that includes developing constructs, profiling readiness, creating predictive models, and establishing pathways. It introduces two measurement methods: source breadth, which measures how students acquire knowledge about intelligent tools through different information channels, and an advantage score, which presents perceived benefits for educational activities. The three-profile segmentation method shows that different groups in the sample display distinct levels of preparedness and value assessment. The Random Forest model demonstrates superior performance because it achieves the highest accuracy among all tested models in the predictive stage. The selected model exhibits an accuracy rate of 0.789, a precision rate of 0.714, a recall rate of 1.000, an F1 score of 0.833, and an area under the receiver operating characteristic curve of 0.806 in hold-out evaluation. The analysis of variable importance indicates that AI knowledge, grade-point average, information breadth, and profile membership serve as the main factors that explain the results. The final stage transforms analytical results into distinct educational pathways that focus on developing essential literacy skills, implementing structured curriculum materials, providing support for governance matters, and enabling advanced collaborative learning. The results demonstrate that the educational benefits of intelligent tools depend more on students’ preparedness to use them than on their initial exposure to the tools.
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