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Learner profiles of attitudinal learning in a MOOC: An explanatory sequential mixed methods study
ARTICLE

, , Department of Curriculum and Instruction, United States ; , Hub for Teaching and Learning Resources, United States ; , , Department of Curriculum and Instruction, United States

Computers & Education Volume 114, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

The aims of the study were to investigate learner profiles in a MOOC focused on attitudinal learning, Science of Happiness, based on learner self-assessment of “happiness” and relationships with demographics, attitudinal learning gains and preferred instructional activities. A sequential explanatory mixed methods design was used in the attitudinal learning survey. The survey assessed cognitive, affective, and behavioral learning, and was followed by interviews with 12 participants. Latent profile analysis identified two profiles based on the differences in the levels and trends of happiness reported by learners during the 10-week course. Results indicated that MOOC learners described different preferences for exploratory or instructor-directed instructional strategies. Identified implications for the instructional design of MOOCs for attitudinal learning included recognizing that MOOC learners often view MOOCs more as entertainment as opposed to formal education. Therefore, course length, pace, scope, and difficulty should be considered in this light. Furthermore, supporting varied learner goals and interests, and instructional preferences are important. Finally, special consideration must also be paid to the design and facilitation of course discussions.

Citation

Watson, S.L., Watson, W.R., Yu, J.H., Alamri, H. & Mueller, C. (2017). Learner profiles of attitudinal learning in a MOOC: An explanatory sequential mixed methods study. Computers & Education, 114(1), 274-285. Elsevier Ltd. Retrieved November 21, 2019 from .

This record was imported from Computers & Education on January 29, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2017.07.005

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