Grades and Learning Styles: New Software for Analyzing Correlations in a Longitudinal Study Across Different Branches of Knowledge and Years

Abstract

Knowing how students engage with their materials helps educators design methodologies to enhance the learning process. To help teachers in determining students’ average learning style profiles and analyzing potential connections between learning styles and academic performance, new freely accessible software, integrated with Moodle, has been developed in this work. A comprehensive case study involving one thousand students across various subjects and degrees from several branches of knowledge in different years has been conducted using this tool. The analysis reveals low participation in the survey, with only 6 out of 19 courses having a participation rate that surpasses 50%), where respondents generally achieved higher grades compared to non-participants (on a grade scale from 0 to 10, participants scored on average one point higher than those who did not complete the questionnaire), suggesting that they were more motivated. Higher-level courses have higher participation rates, but overall participation has declined over the years. Despite slight differences in learning styles between courses, the general pattern remains similar. The correlation between learning styles and grades, analyzed through linear regression, shows that this model performs better when both learning styles and grade marks are distributed by score rather than by level.