An Analysis of Correlation Between Learning Style and Online Learning Performance During COVID-19: A Case Study of a Computer Programming Course

Learning styles are crucial for online learning because they help understand how individuals best absorb and process information. By considering these, online educators can tailor their instructional approaches to better align with their diverse needs. This study aims to analyze the correlation between learning style and online learning performance under the assumption that each student has multiple learning styles. Students answered the modified online questionnaire based on the Grasha-Riechmann Learning Styles model. There were 348 first-year undergraduate students at Mae Fah Luang University who enrolled in a computer programming course during the COVID-19 pandemic. Basic descriptive statistics and correlation analysis using the Pearson’s or Spearman’s correlation coefficient were performed. After an overall analysis, respondents were divided into two groups based on their online learning performance for further analysis. Overall, online learning performance was found to be positively correlated with a participant style and negatively correlated with an avoidant style. The results of this additional investigation revealed that the participant style was common among students from both groups. Even though these correlations appeared weak, this represented that the needs of this common style should be met first when making changes to online course design, such as employing gamification strategies.