Master’s Thesis Defense Meeting
Date: Wednesday, October 7, 2020
Time: 3:00pm
Location: Virtual, https://bluejeans.com/312872263
 
Advisor: Ruth Kanfer, Ph.D. (Georgia Tech)
 
Thesis Committee Members:
Ruth Kanfer, Ph.D. (Georgia Tech)
Phillip L. Ackerman, Ph.D. (Georgia Tech)
Julia Melkers, Ph.D. (Georgia Tech)
 
Title: Extending Models of Self-Regulated Learning to Working Adults: Implications for Online Advanced Skill Training  

 Abstract: Despite an increase in the prevalence of online skill training programs for working adults, little is known about the self-regulated learning (SRL) strategies by which adults manage their learning in such programs. The objective of the current project was to investigate the nature of self-regulated learning strategy use among working adults engaged in an online skill training program. 75 in-depth interviews were conducted with adults enrolled in an online Master's of Computer Science program, and these data were subjected to a qualitative thematic analysis as well as exploratory analyses concerning gender and age differences. Findings support the extension of extant SRL models to emphasize a novel set of strategies employed by online adult learners, including 1) a greater emphasis on 'macro' strategy use, 2) a priori time management tactics, and 3) reliance on a functionally diverse social network for help with management of both learning and non-learning demands. Unexpectedly, reported frequency of SRL strategy use did not vary by gender or age. Implications are discussed regarding future directions for measurement of SRL in working adults as well as the development of interventions for working adults' learning management.