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Characterization of Meaningful Learning Associated with Feedback in a Digital Transformation

  • Universidad Tecnológica del Perú
  • Universidad Nacional "San Luis Gonzaga" de Ica

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

Teaching-learning at the higher university level has radically changed in universities, from face-to-face teaching to virtual teaching, which, forced by circumstances, originates the use of digital tools and connectivity through the internet as fundamental sources in the process. of student learning, since by not being in contact in a face-to-face way, the teacher must generate significant learning situations, ranging from promoting successful study practices with innovative approaches to an effective and constructive feedback process, which answers the questions of the student What did I do right? What can i improve? How can I improve? which we will analyze in this article. The methodology used is quasi-experimental with a descriptive-explanatory correlational design, whose study objective was the association of formative feedback related to meaningful learning, in which the application of technology allowed the development of abilities, aptitudes and skills in students. The study sample was made up of students of the Academic Mention of Primary Education, of the Faculty of Education Sciences and Humanities of the public university of the city of Ica-Peru. Data collection was applied through the observation card instrument, using the Hattie and Timperley feedback model. The results of the analysis have shown that there is a significant relationship between the association of feedback and the characterization of meaningful learning in students at the university level.

Idioma originalInglés
Título de la publicación alojadaICDLT 2021 - 2021 5th International Conference on Deep Learning Technologies
EditorialAssociation for Computing Machinery
Páginas128-131
Número de páginas4
ISBN (versión digital)9781450390163
DOI
EstadoPublicada - 23 jul. 2021
Evento5th International Conference on Deep Learning Technologies, ICDLT 2021 - Virtual, Online, China
Duración: 23 jul. 2021 → 25 jul. 2021

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia5th International Conference on Deep Learning Technologies, ICDLT 2021
País/TerritorioChina
CiudadVirtual, Online
Período23/07/21 → 25/07/21

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