Educational institutions seek to transform the teaching-learning conditions through the use of new pedagogical and technological models. The aim of this quantitative research is to analyze the use of flipped classroom in the teaching-learning process on descriptive statistics through data science. The participants are 49 students who took the Basic Statistics course during the 2017 school year. This study used a single group quasi-experiment to examine the research hypotheses about Flipped classroom. In the Basic Statistics course, the students have difficulties to assimilate the knowledge about mean, mode, median, range and quartiles. Therefore, this research proposes the consultation of YouTube videos before the class, use of the Mathportal application collaboratively during the class and use of the Mathportal application individually after the class. The Mathportal application is a web tool that allows checking the results of the exercises on the mean, mode, median, range and quartiles at any time. The results of machine learning (linear regression) indicate that flipped classroom positively influences the teaching-learning process on descriptive statistics. On the other hand, data science allows the identification of 3 predictive models about the consultation of the YouTube videos and use of the Mathportal application through the decision tree technique. This research recommends the use of the Mathportal application for the teaching-learning process on statistics. Even, this web application can be used in the courses of differential calculus, geometry, algebra and financial mathematics. The implications of this research are the transformation of the educational context through the use of flipped classroom and incorporation of technological tools before, during and after the face-to-face classes. Finally, flipped classroom is a pedagogical model that is transforming the organization and implementation of school activities through the use of technology inside and outside the classroom.
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | October 1, 2022 |
Submission Date | August 24, 2021 |
Published in Issue | Year 2022 Volume: 23 Issue: 4 |