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Unveiling Learning Patterns and Early Detection of At-Risk Students: Integrating Bloom's Taxonomy with Data-Driven Student Analytics and Educational Data Mining.

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Title: Unveiling Learning Patterns and Early Detection of At-Risk Students: Integrating Bloom's Taxonomy with Data-Driven Student Analytics and Educational Data Mining.
Authors: Deshpande, Sudhindra B.1, sbdsudhi@gmail.com, Mathad, K. S.2, ksmathad@git.edu, Karekar, N. V.3, nkarekar@git.edu, Kadkol, R. J.4, rjkadkolr@git.edu, Tangod, Kiran K.1, kirankt@gmail.com, Jadhav, Raghavendra1, ryjadhav@git.edu
Source: IAENG International Journal of Computer Science; Mar2026, Vol. 53 Issue 3, p1166-1188, 23p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Unveiling Learning Patterns and Early Detection of At-Risk Students: Integrating Bloom's Taxonomy with Data-Driven Student Analytics and Educational Data Mining.
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  Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Computer+Science%22">IAENG International Journal of Computer Science</searchLink>; Mar2026, Vol. 53 Issue 3, p1166-1188, 23p
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      – TitleFull: Unveiling Learning Patterns and Early Detection of At-Risk Students: Integrating Bloom's Taxonomy with Data-Driven Student Analytics and Educational Data Mining.
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              Text: Mar2026
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