engleski

Development of the students’ performance predictive model based on didactic methods used for teaching in higher education

With the start of the pandemic, a new chapter was opened in the creation of the teaching process based on combinations of a classic classroom with a lecturer, online lectures or tutorials, and the introduction of a special form defined as a flipped classroom. In this paper, we have connected those three forms of teaching with the time that students spend in the realization of the planned program. In this regard, we conducted a survey among carefully selected three groups of students. The first group attended classes in the classic classrooms with a lecturer and a given schedule of classes, during at least one whole semester in the previous year. The second group of students was comprised of students who were taught online for at least one semester and where the class was held by a lecturer in any form of hybrid teaching. The third group consists of students who had at least part of the teaching of the entire semester in the form of an flipped classroom. These students were also invited to provide their targeted evaluation for the flipped classroom lectures. We divided the time required for the realization of the learning process into three parts: attendance at classes, study of the proposed materials in the form of videos or presentations, and independent learning. From the higher education institution database (Zagreb University of Applied Sciences - TVZ), we extracted the average grades for the observed semesters. Furthermore, we used statistical methods to analyze the relations between abovementioned variables. After conducting an analysis and linking the different forms of learning, learning time and success (expressed in the form of an average grade), we identified the underlying rules that link the observed variables. Finally, we used mathematical methods to determine the functional regularity between the given variables of forecasting the required time and the method of performance to predict the success of students.

predictive model ; didactics ; higher education ; flipped classroom ; hybrid teaching ; online teaching

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