ArticleScientific data2025
Experimental Dataset on Eye-tracking Activity During Self-Regulated Learning.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Network analysis of smartphone addiction, attentional control, and learning adaptation among nursing undergraduates.BMC medical education · 2026Article
- Open data, private learners: a de-identified student activity and performance dataset for learning analytics.Scientific data · 2026Article
- Experimental Dataset on Eye-tracking Activity During Self-Regulated Learning.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The cognitive processing of learning materials has been extensively studied within various cognitive theories. Self-regulated learning (SRL) is also recognized as a key factor in learning efficiency. However, evidence linking SRL to learning outcomes remains inconclusive, particularly regarding objective behavioral data during learning. This study presents an original empirical dataset on eye-tracking activity during learning, examining the effects of metacognitive prompts and multimedia content on cognitive processing and learning outcomes. A controlled laboratory experiment with a 2 × 2 mixed factorial design involved 110 university students, resulting in 84 complete recordings of eye-movement activity during learning. Participants studied scientific materials in text-only and multimedia formats, with one group receiving metacognitive prompts and the control group receiving general instructions. Learning performance was assessed via a post-test, and eye-tracking technology captured gaze patterns to provide insights into cognitive engagement and attention distribution. Applications extend to e-learning, virtual environments, and user interface design. While the dataset has some methodological limitations, it remains a robust resource for studying cognitive processes and optimizing educational technologies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.