Type of Document	Dissertation
Author	Trahan, Mitzi (Maritza) Pamela
URN	etd-04102008-084519
Title	A Structural Equation Modeling Approach to Factors that Contribute to the Impact MyMathLab Has on Commitment and Integration of Technology.
Degree	Doctor of Philosophy (Ph.D.)
Department	Educational Theory, Policy, & Practice
Advisory Committee	Advisor Name Title Andrew Schwarz Committee Co-Chair Roland Mitchell Committee Co-Chair Jan Hinson Committee Member Rita Culross Committee Member Robert Lipton Dean's Representative
Keywords	structural equation modeling educational technology partial least squares computer-mediated instruction
Date of Defense	2008-04-07
Availability	unrestricted
Abstract Learning with educational technology in higher education is rapidly increasing and shows promise of providing cost effective instructional delivery to a wide audience. Information technology scholars have begun to explore multiple antecedent variables leading to successful learning with technology. Yet, the ideal conditions or barriers have not been fully explored. The current study attempted to link certain personality characteristics and technology acceptance constructs within a nomological network that could predict factors that might influence student integration and commitment to educational technology. Data were gathered using a survey collection approach at a large southern Research I university. Students are required to actively engage in a computer-mediated learning environment that consists of an interactive software program, MyMathLab, and a math lab that provides faculty and peer support. Students responded to two surveys designed to capture their initial perceptions of the value of educational technology and measures of stable personality constructs. A second survey collected attitudinal responses directly related to their learning experiences with MyMathLab. Data were analyzed using Partial Least Squares (PLS) Structural Equation Modeling approach. The researcher specifies a predictive model of variables and, subsequently, examines the measurement and structural components of the model. The overall strength and statistical significance of the path relationships within the constructs are given by R2 and t-test statistics. The results suggest that affective measures of computer self-efficacy impact a student’s willingness to experiment with technology. In addition, students who feel comfortable with the level of complexity within MyMathLab, and who see the advantages to using the program, are more likely to integrate the system into their normal school routine. Another finding relates to the connection between integration and commitment. At the level of commitment, students moved beyond basic acceptance to a willingness to explore the technology further. Overall, the variables of the model explained 43.5% of the total variance in Commitment. An exploratory study of this nature can help educators gain a better understanding of potential curricular and instructional interventions that could be incorporated into computer-mediated learning environments.
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