Am I Extravert or Introvert? Considering the Personality Effect Toward e-Learning System

• Published in: Educational Technology ＆ Society Vol. 16; no. 3; pp. 14 - 27
• Main Authors: Amal Al-Dujaily, Jieun Kim, Hokyoung Ryu
• Format: Journal Article
• Language: English
• Published: Palmerston North International Forum of Educational Technology ＆ Society 01.07.2013; International Forum of Educational Technology & Society
• Subjects: Adaptive systems; Between-subjects design; Cognitive Style; Computer Assisted Instruction; Computer Science Education; Computer System Design; Computers; Courseware; Design engineering; Distance learning; Educational activities; Educational aspects; Educational technology; Electronic Learning; Experiential learning; Extraversion Introversion; Extroversion; Fisher Exact Probability Test; Foreign Countries; Full Length Articles; Human Factors Engineering; Independent variables; Individual Differences; Intermode Differences; Learning Activities; Learning experiences; Learning Style Inventory; Learning styles; Machine learning; Management; Myers Briggs Type Indicator; New Zealand; Oman; Online education; Online learning; Personality; Personality Traits; Predictor Variables; Program Validation; System effectiveness; Systems design; Teaching Methods; New Zealand; Oman; South Korea; Adaptive e-learning systems; Personality trait; Learning styles; MBTI
• ISSN: 1176-3647; 1436-4522; 1436-4522

A concern of computer-based learning system design is how to accommodate learners' individual differences during learning activities. Previous research suggests that adaptive e-learning systems can effectively address such individual differences and, consequently, they enable more directed tutoring via computer-assisted instruction. In this paper, we explore this assertion, reflecting on the outcomes of two successive experiments that were performed to empirically demonstrate that learners' personality traits might be significant in understanding differences in learning outcomes from using e-learning systems. One hundred and forty-five participants from Computer Science participated in this study. A two-by-two between-subjects factorial study was designed, where the personality traits derived from Myers-Briggs Type Indicator, and the two computer-based learning systems (adaptive vs. non-adaptive) are independent variables. The results suggested that the personality trait that could be indicative of preferred learning styles; in particular extraverted/introverted personal traits significantly influenced learning activity on adaptive e-learning system. A design guideline might be implicative of how the e-learning system suits the learner's personality trait.