Evidence map›Paper›PMID 40745430›Full record

ArticleScientific data2025

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

Roberto Daza, Alvaro Becerra, Ruth Cobos, Julian Fierrez, Aythami Morales

Abstract readDataset
In one paragraph

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Roberto DazaBiometrics and Data Pattern Analytics Laboratory, Universidad Autonoma de Madrid, School of Engineering, Madrid, 28049, Spain. roberto.daza@uam.es.ORCID 0009-0005-2109-7782
Alvaro BecerraGroup for Advanced Interactive Tools, Universidad Autonoma de Madrid, School of Engineering, Madrid, 28049, Spain.
Ruth CobosGroup for Advanced Interactive Tools, Universidad Autonoma de Madrid, School of Engineering, Madrid, 28049, Spain.
Julian FierrezBiometrics and Data Pattern Analytics Laboratory, Universidad Autonoma de Madrid, School of Engineering, Madrid, 28049, Spain.
Aythami MoralesBiometrics and Data Pattern Analytics Laboratory, Universidad Autonoma de Madrid, School of Engineering, Madrid, 28049, Spain.

Funding

Comunidad de Madrid V PRICIT (Regional Programme of Research and Technological Innovation)Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness) (BIBECA) RTI2018-101248-B-I00
6 · The paper itself

Abstract

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.

Indexed as

Cell PhoneEducation, DistanceHumans

Identifiers

PMID40745430
PMCPMC12313889

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.