abstract: Students' ability to regulate and control their behaviors during learning has been shown to be a critical skill for academic success. However, researchers often struggle with ways to capture the nuances of this ability, often solely relying on self-report measures. This thesis proposal employs a novel approach to investigating variations in students' ability to self-regulate by using process data from the game-based Intelligent Tutoring System (ITS) iSTART-ME. This approach affords a nuanced examination of how students' regulate their interactions with game-based features at both a coarse-grained and fine-grain levels and the ultimate impact that those behaviors have on in-system performance and learning outcomes (i.e., self-explanation quality). This thesis is comprised of two submitted manuscripts that examined how a group of 40 high school students chose to engage with game-based features and how those interactions influenced their target skill performance. Findings suggest that in-system log data has the potential to provide stealth assessments of students' self-regulation while learning. / Dissertation/Thesis / M.A. Psychology 2014
| Identifer | oai:union.ndltd.org:asu.edu/item:25175 |
| Date | January 2014 |
| Contributors | Snow, Erica Linn (Author), Mcnamara, Danielle S (Advisor), Glenburg, Arthur M (Committee member), Duran, Nicholas (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 93 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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