Self-directed and collaborative online learning: Learning style and performance
Clifford Thomas Fitzgerald, Boston University, United States
Boston University . Awarded
The purpose of this study was to determine whether a match between a participant's learning style and type of online instruction improved learner performance on tests measuring comprehension and retention. Learning style was measured by the Self-Directed Learner Readiness Scale (SDLRS) and the Grasha-Riechmann Student Learning Style Scale (GRSLSS) and online instruction varied among online courses, recorded online courses, and computer-based tutorials. The setting for the study was a high tech machine vision company in Massachusetts and online users of its products were the participants. Three groups of learners participated in the study: employees, high school students, and customers. All three groups were comprised of engineers or engineering students. All 106 participants completed a survey that measured their preference for self-directed and collaborative learning style with the standard instruments SDLRS and GRSLSS. Participants completed 323 pre- and post-tests for 46 live online courses, recorded online courses, and computer-based tutorials during the data collection phase of the study. Those participants learning in their preferred learning style had the highest mean improvement from pre- to post-tests. Those participants with average or below average scores for self-directed and collaborative learning style showed the least improvement. The results of this study supported the hypothesis that matching the type of activity, collaborative or self-directed, to the learner's preferred learning style improved performance. The study included ten research questions.
Fitzgerald, C.T. Self-directed and collaborative online learning: Learning style and performance. Ph.D. thesis, Boston University. Retrieved March 23, 2019 from https://www.learntechlib.org/p/117846/.
Citation reproduced with permission of ProQuest LLC.
For copies of dissertations and theses: (800) 521-0600/(734) 761-4700 or https://dissexpress.umi.com