A STUDY ON EFFECIENCY OF TEACHING PROBABILITY AND STATISTICS COMBINING WITH PROGRAMMING LANGUAGE R FOR STUDENTS IN UNIVERSITY OF INFORMATION AND COMMUNICATION TECHNOLOGY, THAI NGUYEN UNIVERSITY

Abstract

This study investigates the impact of teaching methodologies with probabilistic programming language R on student performance across various topics in probability theory and statistics. Integrative teaching strategies has shown impressive efficiency in enhancing student’s critical thinking skills, creativity, and ability to solve complex problems. Here, two distinct groups of students, one (group B) have been taught these topics with traditional methodology and the other (group A) have been taught with R, were exposed to different instructional approaches. The performance of 1000 students from each group in University of Information and Communication Technology – Thai Nguyen University, was evaluated across Bloom's Taxonomy 6 levels, encompassing fundamental to advanced cognitive skills. Employing statistical analyses such as statistical descriptions, MANOVA and machine learning classification, we compared the performance of the two groups and conducted post-hoc analyses to identify specific factors contributing to performance disparities. Results indicate the superior performance of group A across multiple cognitive levels, underscoring the efficacy of methodology A. This research contributes to the ongoing discourse on optimizing teaching methodologies to enhance student learning outcomes in probability and statistics. Especially, it encourages to combine the teaching methodology of these subjects with a probabilistic programming language, such as R.