Perception of students on blended learning considering data science and machine learning

Ricardo A. Salas-Rueda


This quantitative research aims to analyze the impact of audiovisual contents, discussion forums and online evaluations in the Blended learning modality through data science and machine learning. The sample is composed of 106 students from the careers of Administration, Commerce, Accounting, Marketing and Systems. The results of machine learning (linear regression) indicate that audiovisual contents, discussion forums and online evaluations in the Blended learning modality positively influence the teaching-learning process. On the other hand, data science identified 3 predictive models on the use of Blended learning by means of the decision tree technique. This research recommends the incorporation of the Blended learning modality during the planning and organization of school courses in order to develop the competencies of the students. Finally, Blended learning represents an alternative to improve teaching-learning conditions in the 21st century through the performance of synchronous and asynchronous school activities. 

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