Predicting Students’ Final Exam Scores from their Course Activities
This paper investigates whether data from peer-based online homework activities in university programming courses (University of Trento, Italy) can predict students' final exam scores. The authors build a linear regression model using features such as students' homework votes, number of tasks completed, and question difficulty level, and evaluate whether the model outperforms random-guess baselines when predicting both continuous exam scores and letter grades (A–F).
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Building the prediction model (Predicting Students’ Final Exam Scores from their Course Activities)
Model Evaluation and Random-Baseline Comparison (Predicting Students’ Final Exam Scores from their Course Activities)
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