Dataset for "Attitudes towards artificial intelligence, perseverance, and stress as predictors of self-regulated learning in Peruvian university students

This dataset contains the anonymized data used in the study “Attitudes towards artificial intelligence, perseverance, and stress as predictors of self-regulated learning in Peruvian university students.” The study employed a cross-sectional, associative-predictive design and included 1,902 Peruvian...

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Guardado en:
Autor principal: Josué Edison Turpo Chaparro
Formato: Conjunto de datos
Lenguaje:inglés
Publicado: 2025
Materias:
attitudes toward AI
student self-regulation
perseverance
grit
perceived stress
university students
Peruvian students
coping
perceived control
autonomy
consistency of interest
Grit, Self-Efficacy, and Motivation
Innovative Teaching and Learning Methods
Student Stress and Coping
Acceso en línea:Enlace permanente (DOI o Handle)
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Sumario:This dataset contains the anonymized data used in the study “Attitudes towards artificial intelligence, perseverance, and stress as predictors of self-regulated learning in Peruvian university students.” The study employed a cross-sectional, associative-predictive design and included 1,902 Peruvian university students. Data were collected using the Attitudes toward Artificial Intelligence Scale (AIAS-4), the Short Grit Scale (Grit-S), the Perceived Stress Scale (PSS-10), and the Self-Regulated Learning Scale. The dataset includes variables related to attitudes toward artificial intelligence, consistency of interests, perseverance of effort, distress, coping/perceived control, and the control and autonomy dimensions of self-regulated learning. Sociodemographic variables are also included. The data were analyzed using descriptive statistics, Pearson correlations, and structural equation modeling with the WLSMV estimator. All identifying information was removed prior to deposit.

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