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Predictive Analysis of Students’ Learning Performance Using Machine Learning
Technical Architect, I & I Software Inc, ²⁵⁷¹ Baglyos Circle, Suite B-³², Bethlehem, Pennsylvania, USA.
Published Online: September-October 2024
Pages: 14-18
Cite this article
↗ https://www.doi.org/10.59256/ijire.20240505002Abstract
View PDFSeveral researchers and educational institutions got attracted to the domain of predicting the performance of the students to classify the educational level of student performance. Though the educational sector uses several techniques for extracting useful information about them and the measures to be undertaken in the learning process, it is necessary to develop a student performance assessment model to assist the students as well as faculty members to improve their performance to the next level. This research work majorly concentrates to examine and identify useful rules and patterns to motivate the students for handling their education as well as career in a better way and also to improve the functioning of academics to supervise the policies for students’ benefit. Here, EDM is employed to identify the effective data which helps in applying the active learning in technical applications. Initially, a review of different DM, machine learning (ML), and meta-heuristic models to assess the performance of the students. the proposed models can be employed as an appropriate tool for mining educational data to achieve effective performance assessment of the students.
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