Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review

Artificial intelligence (AI) has recently erupted into the field of education, offering novel opportunities, particularly in the analysis of student behaviour. There is a lack of knowledge on the use of AI in assessing attention; hence, a <b>scoping review (ScR)</b> is proposed. The aim...

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Main Authors: Rosabel Roig-Vila, Paz Prendes-Espinosa, Miguel Cazorla
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/11/5990
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author Rosabel Roig-Vila
Paz Prendes-Espinosa
Miguel Cazorla
author_facet Rosabel Roig-Vila
Paz Prendes-Espinosa
Miguel Cazorla
author_sort Rosabel Roig-Vila
collection DOAJ
description Artificial intelligence (AI) has recently erupted into the field of education, offering novel opportunities, particularly in the analysis of student behaviour. There is a lack of knowledge on the use of AI in assessing attention; hence, a <b>scoping review (ScR)</b> is proposed. The aim is to explore and analyse the scientific literature related to such implementations in educational settings. We included empirical studies published in English between 2017 and 2023, focusing on the application of AI in formal learning environments. Theoretical reviews and studies conducted outside the field of education were excluded. The databases consulted were Scopus, Web of Science, and APA PsycInfo. The studies were selected by three independent reviewers using Rayyan, and the data were organised with predefined forms and analysed using VOSviewer. A total of 26 studies were identified. Research conducted in Asia (China) was predominant, although we found significant contributions from Europe and America. The methodological approaches were primarily experimental, focusing on mechanical observation and AI-based analytical techniques. The approaches adopted and the elements common to AI applications are discussed, highlighting implications for researchers, professionals and teachers.
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spelling doaj-art-369f2af441204eb5be67daa82da3d4de2025-08-20T02:23:44ZengMDPI AGApplied Sciences2076-34172025-05-011511599010.3390/app15115990Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping ReviewRosabel Roig-Vila0Paz Prendes-Espinosa1Miguel Cazorla2Department of General Teaching and Specific Teaching Methods, University of Alicante, 03690 Alicante, SpainDepartment of Teaching and School Organisation, University of Murcia, 30100 Murcia, SpainDepartment of Computer Science and Artificial Intelligence, University of Alicante, 03690 Alicante, SpainArtificial intelligence (AI) has recently erupted into the field of education, offering novel opportunities, particularly in the analysis of student behaviour. There is a lack of knowledge on the use of AI in assessing attention; hence, a <b>scoping review (ScR)</b> is proposed. The aim is to explore and analyse the scientific literature related to such implementations in educational settings. We included empirical studies published in English between 2017 and 2023, focusing on the application of AI in formal learning environments. Theoretical reviews and studies conducted outside the field of education were excluded. The databases consulted were Scopus, Web of Science, and APA PsycInfo. The studies were selected by three independent reviewers using Rayyan, and the data were organised with predefined forms and analysed using VOSviewer. A total of 26 studies were identified. Research conducted in Asia (China) was predominant, although we found significant contributions from Europe and America. The methodological approaches were primarily experimental, focusing on mechanical observation and AI-based analytical techniques. The approaches adopted and the elements common to AI applications are discussed, highlighting implications for researchers, professionals and teachers.https://www.mdpi.com/2076-3417/15/11/5990artificial intelligenceeducationattention levelstudent concentration
spellingShingle Rosabel Roig-Vila
Paz Prendes-Espinosa
Miguel Cazorla
Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
Applied Sciences
artificial intelligence
education
attention level
student concentration
title Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
title_full Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
title_fullStr Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
title_full_unstemmed Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
title_short Implementation of Artificial Intelligence Technologies for the Assessment of Students’ Attentional State: A Scoping Review
title_sort implementation of artificial intelligence technologies for the assessment of students attentional state a scoping review
topic artificial intelligence
education
attention level
student concentration
url https://www.mdpi.com/2076-3417/15/11/5990
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AT miguelcazorla implementationofartificialintelligencetechnologiesfortheassessmentofstudentsattentionalstateascopingreview