Using Artificial Intelligence to Promote Adolescents' Learning Motivation. A Longitudinal Intervention From the Self‐Determination Theory

ABSTRACT Background With the integration of artificial intelligence into educational processes, its impact remains to be discovered. Objective The aim of the present study was to determine whether, after a 7‐month intervention in which a subject of artificial intelligence was taught, students improved their psychological needs for competence, autonomy and relatedness, potentially leading to an increase in their intrinsic motivation towards learning. Additionally, the study examined the impact of students' use of ICT and the influence of gender along the intervention. Methods This longitudinal study included a total of 50 adolescents from Secondary Education, who responded to a series of scales to measure the main constructs of perceived competence, autonomy, relatedness and intrinsic motivation at two different times (T1 and T2). Results The results showed that, regardless of gender and the frequency of academic or non‐academic use of ICT, statistically significant improvements were observed only in the need for relatedness. Likewise, an analysis of structural equation models revealed that students' initial competence (T1) was the main predictor of their initial motivation (T1), and having this initial motivation was essential for further improving motivation after the intervention (T2). Similarly, each basic psychological need at its initial time point (T1) significantly predicted that same psychological need at its final time point (T2), with considerably high explained variances. Conclusions These results shed some light on the potential effect that AI‐based interventions can have on the basic psychological needs of secondary education students.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2025-03-16
DOI
https://doi.org/10.1111/jcal.70020
Citations
9
Primary Topic
Motivation and Self-Concept in Sports
Type
article
Field-Weighted Citation Impact
21.95
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article

Using Artificial Intelligence to Promote Adolescents' Learning Motivation. A Longitudinal Intervention From the Self‐Determination Theory

Lucía Campo, María Victoria Urruzola, Nahia Delgado, José María Etxabe Urbieta et al.
9 citations
Journal of Computer Assisted Learning
Motivation and Self-Concept in Sports
21.95
article

Using Artificial Intelligence to Promote Adolescents' Learning Motivation. A Longitudinal Intervention From the Self‐Determination Theory

Lucía Campo, María Victoria Urruzola, Nahia Delgado, José María Etxabe Urbieta, Héctor Galindo‐Domínguez
article en
9 citations

Abstract

ABSTRACT Background With the integration of artificial intelligence into educational processes, its impact remains to be discovered. Objective The aim of the present study was to determine whether, after a 7‐month intervention in which a subject of artificial intelligence was taught, students improved their psychological needs for competence, autonomy and relatedness, potentially leading to an increase in their intrinsic motivation towards learning. Additionally, the study examined the impact of students' use of ICT and the influence of gender along the intervention. Methods This longitudinal study included a total of 50 adolescents from Secondary Education, who responded to a series of scales to measure the main constructs of perceived competence, autonomy, relatedness and intrinsic motivation at two different times (T1 and T2). Results The results showed that, regardless of gender and the frequency of academic or non‐academic use of ICT, statistically significant improvements were observed only in the need for relatedness. Likewise, an analysis of structural equation models revealed that students' initial competence (T1) was the main predictor of their initial motivation (T1), and having this initial motivation was essential for further improving motivation after the intervention (T2). Similarly, each basic psychological need at its initial time point (T1) significantly predicted that same psychological need at its final time point (T2), with considerably high explained variances. Conclusions These results shed some light on the potential effect that AI‐based interventions can have on the basic psychological needs of secondary education students.

Journal of Computer Assisted LearningVol. 41(2)
University of the Basque Country (ES)
Openalex Percentile: Top 1%
Motivation and Self-Concept in Sports
21.95
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