Personality and its effects on learning performance: Design guidelines for an adaptive e-learning system based on a user model

An increasingly widespread interest in developing fully adaptable e-learning systems (e.g., intelligent tutoring systems) has led to the development of a wide range of adaptive processes and techniques. In particular, advances in these systems are based on optimization for each user’s learning style and characteristics, to enable a personalized learning experience. Current techniques are aimed at using a learner’s personality traits and its effect on learning preferences to improve both the initial learning experience and the information retained (e.g., top-down or bottom-up learning organization). This study empirically tested the relationship between a learner’s personality traits, analyzed the effects of these traits on learning preferences, and suggested design guidelines for adaptive learning systems. Two controlled experiments were carried out in a computer-based learning session. Our first experiment showed a significant difference in the learning performance of participants who were identified as introverts vs. those who were identified as being extroverts, according to the MBTI scale. As the distinction between extroverted personality types vs. introverted personality types showed the strongest correlation in terms of different learning styles, we used this criteria in our second experiment to determine whether design guidelines for appropriate content organization could reinforce the aforementioned correlation between personality type and learning experience. Relevance to industry: The findings from this article provide how one can practically apply personality traits to the design of e-learning systems. The structure and level of extraversion could be the features to be examined in this regard. 2013 Elsevier B.V. All rights reserved.