Abstract
Advancement in information technology has given a tremendous change in the education system. The traditional classroom education system is slowly getting transferred to the modernized system. In this conversion, the students choose to select the courses to learn in their higher education. The selection will aid the student in learning advanced technologies through theoretical and practical methods. In this research work, a data-driven educational decision-making system with the support of a course curriculum is analyzed with student’s response after the course. The educational decision-making is implemented with the help of the mobile learning technology designed and maintained by the colleges and universities. For performing the analysis, the student response dataset is given as input to the fuzzy logic system to perform the analysis. The research shows that mobile learning technology with the fuzzy logic system has provided better decision-making analysis to curriculum optimization for the student and teachers.
Highlights
In the past, teachers and school systems have collected and used data in one way or another, whether in the form of a grade book to track progress and calculate final grades or standardized test results to gauge district-wide accomplishment
Various algorithms are set in the model to optimize the current curriculum and test the results of the application of the system
This study concludes that applying the data-driven education decision-making system to the curriculum optimization of higher education is feasible
Summary
Teachers and school systems have collected and used data in one way or another, whether in the form of a grade book to track progress and calculate final grades or standardized test results to gauge district-wide accomplishment. Teachers can employ tools to monitor their students’ understanding in real-time or provide them with the outcomes of homework assignments before strategizing future studies [1]. Teachers can create or choose films with questions attached that can be assigned as homework. Tracking who watched and how well they did is done via the data analytics portion of the platform. Teachers can use this information to design their classes, group students, scaffold learning activities, and differentiate instruction [2]. As a bonus, it provides valuable information about which students would benefit from further assistance and who might be most suited to lead class discussions
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