Publicacións en colaboración con investigadores/as de Universidad Nacional de Educación a Distancia (93)

2023

  1. "Replication data for": Comparison of learning content representations to improve L2 vocabulary acquisition using m-learning

    Harvard Dataverse

  2. A Model to Measure University Students’ Learning Efficacy and Satisfaction During the COVID-19 Pandemic

    Croatian Journal of Education, Vol. 25, Núm. 4, pp. 1191-1223

  3. Academic and Social Behaviour Profile of the Primary School Students who Possess and Play Video Games

    Child Indicators Research, Vol. 16, Núm. 1, pp. 227-245

  4. Analysis of predisposition in levels of individual digital competence among Spanish university students

    Contemporary Educational Technology, Vol. 15, Núm. 4

  5. CUESTIONARIO PROFESORADO GAMIFICACIÓN EDUCACIÓN PRIMARIA

    Harvard Dataverse

  6. ChatGPT Database comparison

    Harvard Dataverse

  7. ChatGPT: The brightest student in the class

    Thinking Skills and Creativity, Vol. 49

  8. Comparison of Learning Content Representations to Improve L2 Vocabulary Acquisition Using m-learning

    SAGE Open, Vol. 13, Núm. 4

  9. Gamifying Machine Teaching: Human-in-the-Loop Approach for Diphthong and Hiatus Identification in Spanish Language

    Procedia Computer Science

  10. Influence of age, gender and years of experience on teachers in promoting strategies for digital sustainability and data protection

    NAER: Journal of New Approaches in Educational Research, Vol. 12, Núm. 2, pp. 307-322

  11. La supervisión de la práctica docente y de la función directiva en centros educativos no universitarios

    Creación y experiencias de conocimientos en ámbitos educativos (Dykinson), pp. 37-52

  12. Latent factors on the design and adoption of gamified apps in primary education

    Education and Information Technologies, Vol. 28, Núm. 11, pp. 15093-15123

  13. References on innovative methodologies for adult training

    Studies in the Education of Adults, Vol. 55, Núm. 1, pp. 259-281

  14. Teacher vs machine correction

    Harvard Dataverse