The analyses of the generated dataset indicate that including eye-gaze features significantly increased the accuracy of the Support Vector in predicting student performance by 95%.
This paper examines the potential of developing a predictive model that incorporates student eye-gaze data to dy- namically predict their learning performance ...
This paper examines the potential of developing a predictive model that incorporates student eye-gaze data to dynamically predict their learning performance ...
Dec 9, 2024 · Therefore, this paper explores the integration of eye-gaze features to predict students' learning performance during an embodied activity. We ...
Jul 7, 2022 · Therefore, this paper explores the integration of eye-gaze features to predict students' learning performance during an embodied activity.
Therefore, this paper explores the integration of eye-gaze features to predict students' learning performance during an embodied activity. We present an in-situ ...
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Gazeformer is a novel model that outperforms existing target-detection models on standard gaze prediction for both target- present and target-absent search ...
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Therefore, this paper explores the integration of eye-gaze features to predict students' learning performance during an embodied activity. We present an in-situ ...
In this paper, we aim to predict students' learning perfor- mance by combining two-modality sensing variables, namely eye tracking that monitors learners' eye ...
Eye-gaze data collected via eye-tracking may be used as an objective, quantitative, and generalizable assessment instrument to understand students' learning of ...