What question did this study set out to answer?

To measure and predict student academic performance using activity data from the Moodle Learning Management System through machine learning techniques.

December 15, 2024Journal of Applied Engineering and Technological Science (JAETS)Open Access

Students’ Activeness Measure in Moodle Learning Management System Using Machine Learning

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Authors

CTChandrakumar ThangavelGovernment Medical College SVS E ValliammaiAlagappa University APAmritha P. PTechnology Information, Forecasting and Assessment Council

Discussion

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Implication

Predictive modeling analysis finds student activity metrics in Moodle forecast academic performance in university students, indicating early warnings could help prevent course failure.

Key Points

To measure and predict student academic performance using activity data from the Moodle Learning Management System through machine learning techniques.
Collected student activity logs across both theory and laboratory courses at a higher learning institute in Tamil Nadu.
Applied linear regression models to evaluate online engagement metrics and forecast final course outcomes.
Linear regression analysis effectively mapped student engagement and activity levels in Moodle to final course performance.
The predictive model enabled early identification of students at risk of course failure, providing faculty actionable data to modify instructional methods and deliver targeted interventions.

Cite This Study

Thangavel et al. (2024) studied this question.

synapsesocial.com/papers/6a7ef0e3cda104a52269a119 https://doi.org/10.37385/jaets.v6i1.6128

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Implication

Predictive modeling analysis finds student activity metrics in Moodle forecast academic performance in university students, indicating early warnings could help prevent course failure.

Students’ Activeness Measure in Moodle Learning Management System Using Machine Learning

Discussion

Member takes

Implication

Key Points

Cite This Study

Students’ Activeness Measure in Moodle Learning Management System Using Machine Learning

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider