Exploring the fit between learner characteristics and learning environments

Chaw, Lee Yen, and Tang, Chun Meng (2021) Exploring the fit between learner characteristics and learning environments. In: Proceedings of the 20th European Conference on e-Learning. pp. 89-97. From: ECEL 2021: 20th European Conference on e-Learning, 28-29 October 2021, Berlin, Germany.

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Learner characteristics differ in many ways, e.g. learning styles, learning needs, and motivation. Such diversity means that learning methods and effectiveness are likely to vary in different learning environments. Each type of learning environment, whether it is face-to-face classroom learning, blended learning, or online learning, offers distinct design elements and features that make them more suited to some learners’ characteristics than others. Therefore, a good understanding of how learner characteristics may account for their preferences for certain learning environments is a highly relevant area of investigation for today’s educational institutions. Employing a two-stage exploratory sequential mixed methods research design, this study first conducted a qualitative study (i.e. focus group interviews) to understand learners’ different reasons for liking or disliking a learning environment. These reasons provided the basis for the subsequent analysis of learner characteristics. A follow-up quantitative study (i.e. questionnaire survey) performed a factor analysis to further categorise these reasons into four learner characteristics: desire for direct support, digital readiness, learning independence, and online hesitancy. Another cluster analysis, based on the four learner characteristics, identified three groups of learners: classroom learners, insecure learners, and online learners. Analyses also found that learner demographics largely had no effect on their characteristics and their preference for a learning environment. This study helps provide some insights into why some learners perform well in certain learning environments, but others find it challenging. In addition, the findings can be useful for educational institutions when designing their learning environments to meet diverse learning needs.

Item ID: 70064
Item Type: Conference Item (Research - E1)
ISBN: 978-1-914587-18-4
Keywords: cluster analysis, higher education, learning environments, learner characteristics, learning needs
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Copyright Information: Copyright the authors, 2021. All Rights Reserved.
Date Deposited: 23 Nov 2021 23:05
FoR Codes: 39 EDUCATION > 3901 Curriculum and pedagogy > 390102 Curriculum and pedagogy theory and development @ 60%
39 EDUCATION > 3903 Education systems > 390303 Higher education @ 10%
39 EDUCATION > 3901 Curriculum and pedagogy > 390199 Curriculum and pedagogy not elsewhere classified @ 30%
SEO Codes: 16 EDUCATION AND TRAINING > 1601 Learner and learning > 160102 Higher education @ 10%
16 EDUCATION AND TRAINING > 1603 Teaching and curriculum > 160301 Assessment, development and evaluation of curriculum @ 40%
16 EDUCATION AND TRAINING > 1603 Teaching and curriculum > 160302 Pedagogy @ 50%
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