ERIC Number: ED599137
Record Type: Non-Journal
Publication Date: 2019
Pages: 190
Abstractor: As Provided
ISBN: 978-1-3921-7446-3
ISSN: EISSN-
EISSN: N/A
Available Date: N/A
The Predictive Assessment for Virtual Education: The Predictors of Online Student Success Using Dweck's Mindset Theory
Siharath, Phonekeo
ProQuest LLC, Ph.D. Dissertation, Cardinal Stritch University
The attrition rate for online education continues to be high. To mitigate or better understand attrition, different researchers have developed survey tools in order to try to predict student outcomes in the virtual setting. Roblyer and Marshall first developed The Educational Success Prediction Instrument (ESPRI) in 2002 and then updated it in 2008 (ESPRI-V2). This particular study built off of their work but adapted the approach to examine predictive instrumentation with a new survey tool using Carol Dweck's research in the growth mindset. For this study, items on the Predictive Assessment for Virtual Education (PAVE) survey tool ask for ratings on a 7-point Lickert scale. Survey items followed incremental theory and examined growth and mastery oriented mindsets. Responses to the PAVE survey were examined using multiple regression analysis. Item weights were then compared to student outcomes, which were reported in the form of course grades and grade point average. Results were mixed as the data were limited by the students willing to respond to the survey; the self-selected sample resulted in most students having perfect grades. Nonetheless, there were a few response items, particularly the scenario item, which had statistical significance and could support a survey tool to examine online learning and incremental and the growth mindset construct. In the end, just as is the case with online learning as a whole, the survey tool has promise, but it does need more work. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]
Descriptors: Prediction, Measures (Individuals), Online Courses, Academic Achievement, Mastery Learning, Grades (Scholastic), Grade Point Average, Outcomes of Education, Electronic Learning
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
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