Theses and Dissertations

Date of Award

5-2023

Document Type

Dissertation

Degree Name

Ph.D.

Department

Instructional Design and Development

Committee Chair

James P. Van Haneghan, Ph.D.

Advisor(s)

Lisa LaCross, Joe Gaston, and Joel Billingsley

Abstract

Based on the Technology Acceptance Model (TAM) (Davis et al., 1989), this research examines the variables of perceived usefulness and perceived ease of use as predictors of video creation usage after software training. To gain a comprehensive understanding of the technology adoption process, the study also employed the Learning Adoption Trajectory Model (LATM) (Sherry et al., 2000), to explore how faculty and staff progress through different stages of technology adoption. Furthermore, the study examined whether the barrier of time, value to the department, and priority played a role in predicting the technology's usage.

The study employed a mixed-design approach, with a quantitatively dominant design and a concurrent, sequential collection of qualitative data. The qualitative section used a nonexperimental cross-sectional design based on responses to open-ended questions in the survey questionnaire and interviews. Following a four-week training course in Camtasia, a video-editing software technology, participants were surveyed to assess their utilization of the software subsequent to the training. Because training cohorts ranged from March 2021 to September 2022, participants were surveyed anywhere from four to eighteen months after their training. A total of 63 participants completed the survey for this study. In addition, data from partially completed surveys were included in the analyses, resulting n a total of 78 responses. Furthermore, I conducted seven interviews to supplement the survey data.

The findings of the study suggest that perceived usefulness significantly predicted participant usage of the software, while perceived ease of use did not after controlling for usefulness. Moreover, out of the three barriers, the results indicated that value to the department was the most significant predictor of participants' future intention to use Camtasia, compared to the barrier of time and priority. The LATM model offered insights into the different stages of adoption, revealing that most faculty and staff were in the early stages of adoption. The analysis also indicated that the stage was a predictor of the number of projects created per semester, but not necessarily future intention of use. this suggested that participants in higher stages of adoption created more projects, but it did not necessarily have an effect on the future intention to use Camtasia.

To summarize, this study offers valuable insights into the predictors of technology usage among higher education faculty and staff. Specifically, the findings underscore the significance of a person's perception of usefulness and the departmental perceived value of technology, in relation to their intention to use it in the future. Furthermore, LATM offered a useful framework for understanding the different stages of adoption and the predictors of project creation. This information can be used to inform instructional design and training strategies that effectively support faculty and staff in adopting technology.

This study offers practical implications for enhancing the adoption of technology in higher education settings. By understanding the factors that influence technology adoption, instructional designers and trainers can develop effective strategies to facilitated technology adoption and improve teaching and learning outcomes.

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