About EngageME

Online learning has become increasingly prevalent during the pandemic, yet assessing student cognitive engagement in these settings poses significant challenges. Traditional methods often rely on potentially biased and logistically complex self-reporting, which may not accurately reflect true cognitive engagement. To address this issue, we introduce the EngageME dataset, a novel approach to attention assessment using clinical models of attention. This method measures cognitive engagement in digital education by finely assigning attention weights to capture subtle variations, a Nuanced Attention Labeling method. We correlated established clinical models of attention with pedagogical approaches in digital education to identify three critical types of attention: selective, sustained, and alternating. Subsequently, we used three neuropsychological assessments, Stroop, Continuous Performance Test (CPT) and Trail Making Test (TMT), to evaluate attention among 98 participants. All students participated in an online data collection experiment from their homes. Participants submitted webcam recordings and cognitive task responses in CSV format. Participant performance was annotated using CSV data, and features were extracted from each video segment. We analysed reaction times, accuracy, and total time across these tests. In the Stroop and CPT, accuracy metrics were used to assess attention, with higher scores indicating better performance. Response times served as the metric for the TMT. Annotations were based on these tests’ reaction times and accuracy metrics, with scores standardised and normalised to provide clear indicators of attention performance.

Paper Link : EngageME: Exploring Neuropsychological Tests for Assessing Attention in Online Learning

Data Collection Pipeline

Download Instructions

Please follow these steps to access the dataset:

1. Download and print the End User License Agreement (EULA).
2. Sign the EULA and scan the signed copy.
3. Fill out the form and upload the scanned EULA using the form.

Once we receive the signed EULA, we will provide you with the link to the dataset.

Acknowledgements

We sincerely thank the participants who generously contributed their time and effort to this study. Your involvement in the neuropsychological assessments was crucial to developing this dataset. We deeply appreciate your patience and support in contributing to this research.