Self-regulated learning in virtual simulations

dc.contributor.committeeChairJones, Keith S.
dc.contributor.committeeMemberSerra, Michael J.
dc.contributor.committeeMemberGorman, Jamie C.
dc.contributor.committeeMemberKlein, Martina I.
dc.contributor.committeeMemberTharanathan, Anand
dc.creatorDerby, Paul L.
dc.description.abstractVirtual simulations allow trainees to practice on their own. To effectively practice on their own, trainees should be able to self-regulate their learning. Even though there are claims that virtual simulations can foster self-regulated learning processes, there is no evidence to conclude that trainees are able to self-regulate their learning within these types of simulations as described within popular models of self-regulated learning (i.e., Zimmerman 2000, 2002, 2011; Pintrich, 2000, 2004). If trainees are not self-regulating their learning as specified by these models, it causes concern for the effectiveness of allowing trainees to practice on their own within virtual simulations. This study examined two questions: (a) Do learners self-regulate their learning within virtual simulations in accordance with the accepted models of self-regulated learning and (b) what model of self-regulated learning best fits the flow of self-regulated learning processes exhibited by the learners? The results indicated the following. First, participants self-regulated their learning. In other words, participants learned how to execute the tasks in the virtual simulation more efficiently and quickly, participants exhibited all of the self-regulated learning processes, and their learning was related to exhibiting these processes. Second, participants did not exhibit the self-regulated learning processes in the cyclical flow described by Zimmerman. Therefore, it seemed like the nature of self-regulation was dependent on the task. Taken together, these results provided some preliminary support that virtual simulations can be supplied to trainees for the purpose of self-learning.
dc.subjectSelf-regulated learning
dc.titleSelf-regulated learning in virtual simulations
dc.typeDissertation - Experimental Tech University of Philosophy


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