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Predicting Undergraduate Student Course Success in a Lecture Capture Quantitative Methods Course

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Date Issued:
2018
Abstract/Description:
The purpose of this study was to develop a methodological approach using secondary data that researchers, faculty, and staff can utilize to assess student course performance and to identify the input and course environment factors that best predict student course success in an undergraduate lecture capture quantitative methods course. Using Astin and antonio (2012)’s Input Environment and Outcome (IEO) Model as a framework, this quantitative study examined both input variables that students bring to a course as well as the course environment factors that students experience in the course. Three secondary data sources were utilized and analyzed using descriptive and multivariate statistics. The findings revealed that students with higher levels of student course engagement and academic self-concept were more likely to achieve student course success in this lecture capture quantitative methods course. In addition, prior University GPA along with live-class attendance, discussion board posts, and course quiz and exam scores were the strongest predictors of student course success. The largest implication from this study was the methodological approach developed to identify factors that predicted student course success. This approach can be used to help faculty identify course-embedded measures for assessment as well as develop Keys for Success to help future students succeed in difficult courses. While this study added significantly to the limited research on lecture capture courses, future research should further explore qualitative aspects of the course, such as motivation and student video-viewing behaviors, as well as additional impacts on physical attendance in lecture capture courses.
Title: Predicting Undergraduate Student Course Success in a Lecture Capture Quantitative Methods Course.
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Name(s): Sweet, Jonathan A., author
DeDonno, Michael, Thesis advisor
Florida Atlantic University, Degree grantor
College of Education
Department of Educational Leadership and Research Methodology
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2018
Date Issued: 2018
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 263 p.
Language(s): English
Abstract/Description: The purpose of this study was to develop a methodological approach using secondary data that researchers, faculty, and staff can utilize to assess student course performance and to identify the input and course environment factors that best predict student course success in an undergraduate lecture capture quantitative methods course. Using Astin and antonio (2012)’s Input Environment and Outcome (IEO) Model as a framework, this quantitative study examined both input variables that students bring to a course as well as the course environment factors that students experience in the course. Three secondary data sources were utilized and analyzed using descriptive and multivariate statistics. The findings revealed that students with higher levels of student course engagement and academic self-concept were more likely to achieve student course success in this lecture capture quantitative methods course. In addition, prior University GPA along with live-class attendance, discussion board posts, and course quiz and exam scores were the strongest predictors of student course success. The largest implication from this study was the methodological approach developed to identify factors that predicted student course success. This approach can be used to help faculty identify course-embedded measures for assessment as well as develop Keys for Success to help future students succeed in difficult courses. While this study added significantly to the limited research on lecture capture courses, future research should further explore qualitative aspects of the course, such as motivation and student video-viewing behaviors, as well as additional impacts on physical attendance in lecture capture courses.
Identifier: FA00005988 (IID)
Degree granted: Dissertation (Ph.D.)--Florida Atlantic University, 2018.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Prediction of scholastic success
Undergraduates
Filmed lectures
Quantitative research
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00005988
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Owner Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.