Automatic Classification of Learning Material Styles
DOI:
https://doi.org/10.5753/rbie.2023.3431Keywords:
Video Lesson Styles, Learning Material Styles, Instructional Media Design, Automatic ClassificationAbstract
Although video lessons are often used in diverse areas, the lack of a common approach to defining and classifying their styles results in using many different models for these purposes. There is a need to build a framework through which these styles can be defined and classified. Much has been done to investigate the effects of these styles on student engagement and learning outcomes. These studies suggest that video lesson styles affect academic performance and that students learn better through a certain video lesson style. Based on this, we propose a unified model for classifying video lesson styles based on the nomenclatures and definitions used in the literature.
Furthermore, we present an approach for automatically classifying four popular video lesson styles. The automatic classification is useful for recommendation systems to suggest materials more consistent with student preferences and their intended learning outcomes.
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Copyright (c) 2023 Bernadete Aquino, Jairo Francisco de Souza, Eduardo Barrére
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
