Understanding Students’ Behavior in Learning Management Systems Through Their Personality Traits

Abstract Personalizing educational experiences based on user behavior is a complex challenge, particularly given that learners’ diverse backgrounds, learning experiences, and cognitive styles significantly influence their learning outcomes. Despite recent advancements, the relationship between students’ personality traits and their behavior within learning environments remains insufficiently understood. To address this gap, we conducted a 15-week longitudinal study with 95 undergraduate Computer Science students, examining how engagement metrics and communication frequency within a learning management system relate to their Myers-Briggs Type Indicator dimensions i.e., extroversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving. Our findings indicate that (i) extroverted students demonstrated consistently higher engagement over multiple weeks; (ii) students with judging traits negatively related to the total activities performed and (iii) students with thinking traits are positively associated with overall activity levels.

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Publication Details

Journal
Technology Knowledge and Learning
Published
2025-12-06
DOI
https://doi.org/10.1007/s10758-025-09931-w
Primary Topic
Learning Styles and Cognitive Differences
Type
article
Field-Weighted Citation Impact
0.00

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article

Understanding Students’ Behavior in Learning Management Systems Through Their Personality Traits

Technology Knowledge and Learning
Learning Styles and Cognitive Differences
article

Understanding Students’ Behavior in Learning Management Systems Through Their Personality Traits

article en

Abstract

Abstract Personalizing educational experiences based on user behavior is a complex challenge, particularly given that learners’ diverse backgrounds, learning experiences, and cognitive styles significantly influence their learning outcomes. Despite recent advancements, the relationship between students’ personality traits and their behavior within learning environments remains insufficiently understood. To address this gap, we conducted a 15-week longitudinal study with 95 undergraduate Computer Science students, examining how engagement metrics and communication frequency within a learning management system relate to their Myers-Briggs Type Indicator dimensions i.e., extroversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving. Our findings indicate that (i) extroverted students demonstrated consistently higher engagement over multiple weeks; (ii) students with judging traits negatively related to the total activities performed and (iii) students with thinking traits are positively associated with overall activity levels.

Technology Knowledge and Learning
Tampere University of Applied Sciences (FI), Tampere University (FI), University of Southampton (GB)
Tays, Engineering and Physical Sciences Research Council
Quality Education
Openalex Percentile: Top 35%
Learning Styles and Cognitive Differences
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