Educational Value Formation Around Intelligent
Learning Tools: Student Readiness, Usage Archetypes,
and Support Pathways in Higher Education
Marina Sagatovna Abdurashidova1,∗, Muhammad Eid Balbaa2
1Department of corporate economics and management, Tashkent State University of
Economics, Uzbekistan
2Tashkent State University of Economics, Uzbekistan
Emails: m.abdurashidova@tsue.uz; m.balbaa@tsue.uz
Abstract
Modern higher education campuses now use intelligent learning tools as standard ed-ucational
resources yet students learning results depend on their understanding of these tools and their
implementation in academic work. The study analyzes how students pre-pare 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 which
includes developing constructs and profiling readiness and creating predictive models and establishing
pathways. The study introduces two measurement methods which include source breadth to measure
how students acquire knowledge about intelligent tools through different information channels and an
advantage score to present 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 and a precision rate of 0.714 and a recall rate of 1.000 and 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 knowl-edge and grade-point average and information
breadth and profile membership serve as the main factors that explain the results. The final stage of
the process transforms analytical results into distinct educational pathways which focus on developing
essential literacy skills and implementing structured curriculum materials and 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.
Keywords: Education technology; Higher education; Student readiness; Intelligent learning
tools; Adoption archetypes; Educational value