mlsanityData to 14 Oct 2026

A multimodal dataset for understanding the impact of mobile phones on remote online virtual education

arXiv 2412.14195 ↗First posted 13 Dec 2024cs.HC cs.CVcited by 12

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Abstract (arXiv)

This work presents the IMPROVE dataset, a multimodal resource designed to evaluate the effects of mobile phone usage on learners during online education. It includes behavioral, biometric, physiological, and academic performance data collected from 120 learners divided into three groups with different levels of phone interaction, enabling the analysis of the impact of mobile phone usage and related phenomena such as nomophobia. A setup involving 16 synchronized sensors-including EEG, eye tracking, video cameras, smartwatches, and keystroke dynamics-was used to monitor learner activity during 30-minute sessions involving educational videos, document reading, and multiple-choice tests. Mobile phone usage events, including both controlled interventions and uncontrolled interactions, were labeled by supervisors and refined through a semi-supervised re-labeling process. Technical validation confirmed signal quality, and statistical analyses revealed biometric changes associated with phone usage. The dataset is publicly available for research through GitHub and Science Data Bank, with synchronized recordings from three platforms (edBB, edX, and LOGGE), provided in standard formats (.csv, .mp4, .wav, and .tsv), and accompanied by a detailed guide.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 22 of its 71 references that are in the map. First posted on arXiv 13 Dec 2024.

Builds on

22 of 71 references.

References · 22

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10 more
  1. 2021A multimodal sensor dataset for continuous stress detection of nurses in a hospitalcited by 14
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 7; 2026: 5.

12 papers.

  1. 2025Is My Text in Your AI Model? Gradient-based Membership Inference Test applied to LLMscited by 10
  2. 2025SMARTe-VR: Student Monitoring and Adaptive Response Technology for e-Learning in Virtual Realitycited by 6
  3. 2025AI-based Multimodal Biometrics for Detecting Smartphone Distractions: Application to Online Learningcited by 6
  4. 2025MOSAIC-F: A Framework for Enhancing Students' Oral Presentation Skills through Personalized Feedbackcited by 5
  5. 2026EduEVAL-DB: A Role-Based Dataset for Pedagogical Risk Evaluation in Educational Explanationscited by 4
  6. 2025M2LADS Demo: A System for Generating Multimodal Learning Analytics Dashboardscited by 3
  7. 2025Is It Really You? Exploring Biometric Verification Scenarios in Photorealistic Talking-Head Avatar Videoscited by 3
  8. 2025Enhancing Online Learning by Integrating Biosensors and Multimodal Learning Analytics for Detecting and Predicting Student Behavior: A Reviewcited by 3
  9. 2026A Multimodal Dataset of Student Oral Presentations with Sensors and Evaluation Datacited by 2
  10. 2026AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanationscited by 0
  11. 2026VideoRun2D Demo: Markerless Body Tracking for Biomechanical Analysis of Runningcited by 0
  12. 2026inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMscited by 0