Thesis (M.A.)--Wheaton College Graduate School, 2002. / Abstract. Includes bibliographical references (leaves 48-50).

Thesis (M. Ed.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf 72-82).

Thesis (M. Ed.)--Memorial University of Newfoundland, 1997. / Bibliography: leaves 96-100.

Thesis (M.A.)--Wheaton College Graduate School, Wheaton, IL, 2002. / Abstract. Includes bibliographical references (leaves 48-50).

Thesis (M.Ed.)--University of Hong Kong, 1996. / Includes bibliographical references (leaves 72-82). Also available in print.

Dissertation (Ed.D.)--The University of North Carolina at Greensboro, 2009. / Directed by Diane Gill; submitted to the Dept. of Exercise and Sport Science. Title from PDF t.p. (viewed May 5, 2010). Includes bibliographical references (p. 84-90).

Thesis (M.A.)--Wheaton College Graduate School, Wheaton, IL, 2002. / Abstract. Includes bibliographical references (leaves 48-50).

Thesis (D. Ed. Min.)--Midwestern Baptist Theological Seminary, 2006. / Abstract. Includes bibliographical references (leaves 128-132).

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Identifying, examining, and understanding faculty members’ technological knowledge development and the process of technology adoption in higher education is a multifaceted process. Past studies have used Rogers (1995, 2003) diffusion of innovation theoretical framework to delineate the technology adoption process. These studies, however, have frequently reported the influencing factors based on the statistical analysis such as regression analysis-based approach, and have not focused on the emerging process of technology adoptions or the developing process of technological knowledge and pedagogical knowledge. A mixed method study was designed to see how faculty members acquire different technologies and develop technological knowledge that might help them adopt technologies in their classrooms and online using different pedagogies. A sample of STEM teaching faculty members with different ranks, tenure, teaching experience, and varied degree of experience in the use of educational technologies participated in the study. A survey was designed to identify internal and external factors affecting technology adoption and its effective use in different teaching activities. To elaborate survey results, the study also included class observations as well as pre- and post-observation interviews. Online classrooms used by the faculty via Blackboard learning management system, online flipped classrooms, or other websites such as Piazza were also examined for data triangulation. The findings of the study indicate that faculty members are influenced by their own professional motivations and student learning to improve their teaching methods and to enhance student interactions and learning through the use of different educational technologies. The adoption process was identified as spreading over a period of time and it looked at how faculty members’ developed their technological knowledge and pedagogical knowledge. With the recognition of the social, organizational, and professional motivational factors both expert faculty members, university administrators, and technologist could be made aware of the critical components necessary to construct and support a bottom-up or user-centric successful innovation adoption decision process. The bottom-up approach would use expert professors as change agents and educational designers that would encourage exchanges and meaningful dialogues about educational technology adoptions and effective uses of technology with pedagogy within each discipline and department.