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April 12, 2026Frontiers in Education0 citationsOpen Access

Automated motivational support and academic self-regulation: evidence from a large-scale cross-sectional study

JJJuan Juárez-DíazUniversidad Nacional de San MartínLPLloy PinedoJNJorge Raul Navarro-CabreraUniversidad Nacional de San Martín

Key Points

  • The research aims to explore motivational patterns among university students through Self-Determination Theory.
  • Cross-sectional design involving 723 undergraduate students from a public university in Peru.
  • Data collected using the Academic Situational Motivation Scale (EMSA).
  • Statistical analysis included descriptive statistics, one-way ANOVA, Pearson correlations, multiple regression, and cluster analysis.
  • High levels of intrinsic and extrinsic motivation were observed, with low levels of amotivation.
  • Significant differences in extrinsic and intrinsic motivation across academic fields were found.
  • Extrinsic motivation positively predicted intrinsic motivation, while amotivation negatively impacted it.
  • Three motivational profiles were identified: highly motivated, moderately motivated, and vulnerable.

Abstract

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.

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Cite This Study

Juárez-Díaz et al. (2026) studied this question.

synapsesocial.com/papers/69db361c4fe01fead37c454fhttps://doi.org/10.3389/feduc.2026.1784602
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