Dec 14, 2023 · This article proposes a four-step approach using a sequential ensemble model for engagement prediction, discusses the contribution of different ...
May 13, 2024 · Abstract. Predicting student engagement can provide timely feedback and help teachers make adjustments to their practices to meet student needs ...
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The Sequential predictor adopts the structure of long short-term memory (LSTM) and learns the interaction from the engagement feature spaces and demographic ...
Predicting Student Engagement Using Sequential Ensemble Model ,Science hub Mutual Aid community.
Another study by Hussain et al. (2019) aimed to predict student outcomes using student internal assessment data from past semesters. The model is based on DL ...
[PDF] An Ensemble Method to Predict Student Performance in an Online ...
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We investigated an approach that decomposes the math con- tent structure underlying an online math learning platform, trains specialized classifiers on the ...
Missing: Engagement Sequential
Jun 20, 2024 · Abstract: This paper explores the utilization of ensemble models and learning analytics techniques to predict student academic performance.
4.2.3 Ensemble Prediction Evaluation. We study the effectiveness of our ensemble prediction model by comparing it with other baseline models mentioned above.
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In this study, we propose an ensemble model using 2-layer stacking to predict student performance in academic competition.
Two-layer ensemble prediction framework has been proposed to predict students' performance based on learning behavior and domain knowledge.