Automated motivational support and academic self-regulation
Evidence from a large-scale cross-sectional study
Bibliographic Data
| ID | 22164680 |
|---|---|
| Authors | Juan Juárez-Díaz (Universidad Nacional de San Martín), Lloy Pinedo (0000-0002-5569-8739, Universidad Norbert Wiener), Jorge Raul Navarro-Cabrera (Universidad Nacional de San Martín), Cristian García-Estrella (0000-0002-5687-8694, Universidad Nacional de San Martín), Herbert Hugo Arévalo-Bartra (Universidad Nacional de San Martín), Anne Needa Diaz-Buendia (Universidad Tecnológica del Perú), María García-Paredes (Universidad Nacional de San Martín) |
| Year | 2026 |
| Volume | 11 |
| Publication date | 2026-04-08 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Education (JOURNAL) |
| Journal identifiers | ISSN: 2504-284X • E-ISSN: 2504-284X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/feduc.2026.1784602 |
| OpenAlex | W7152132152 |
| Language | EN |
| References cited | 40 |
This study examined motivational patterns among university students using the framework of Self-Determination Theory, focusing on the relationships between extrinsic motivation (EM), intrinsic motivation (IM), and amotivation (A). A quantitative cross-sectional design was applied to a sample of 723 undergraduate students from different academic fields at a public university in Peru. Data were collected using the Academic Situational Motivation Scale (EMSA) and analyzed using descriptive statistics, one-way ANOVA, Pearson correlations, multiple regression, and cluster analysis. The results revealed generally high levels of intrinsic and extrinsic motivation, accompanied by low levels of amotivation. ANOVA showed statistically significant differences in EM [F(4, 723) = 4.517, p = 0.001, η 2 = 0.024] and IM [F(4, 723) = 7.029, p < 0.001, η 2 = 0.037] across academic fields, while amotivation showed no significant differences across the fields. Correlation and regression analyses indicated that extrinsic motivation positively predicted intrinsic motivation, whereas amotivation negatively predicted it. Cluster analysis identified three motivational profiles: highly motivated, moderately motivated, and vulnerable groups. These findings highlight the heterogeneous nature of student motivation and suggest that universities may benefit from implementing scalable digital and pedagogical strategies aimed at strengthening adaptive motivational patterns and reducing motivational vulnerability in higher-education contexts
Amotivation · Descriptive statistics · Intrinsic motivation · Public university · Self-determination theory · Situational ethics · Education, Achievement, and Giftedness · Innovations in Education and Learning Technologies · Motivation and Self-Concept in Sports
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| Highly cited | No |
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