Date of Award
Doctor of Philosophy (PhD)
Teaching & Learning
Over the last two decades, educational technology (ET) integration has become an increasingly important aspect of higher education, particularly with the growth of online, distance and hybrid courses and degree programs. Furthermore, accrediting agencies such as the Higher Learning Commission (HLC) are paying close attention to online and hybrid courses and degree programs, making effective use of ET even more important to colleges and universities. Even in traditional, on-campus classrooms, some instructors are not using ET effectively to augment teaching and learning.
The main purpose of this research study was to examine a holistic view of educational technology integration into teaching and learning among community college instructors. Additionally, the study aimed to identify some positive and negative factors of educational technology integration and the ways in which those factors affect technology integration among faculty. The study concentrated on identifying facilitative conditions that influence ET integration among instructors at five community colleges. Elyâs (1999) Conditions of Educational Technology Implementation (CETI) theory served as a theoretical framework for this research study. Ely's (1999) CETI framework is based on the comprehensive perspective of ET integration and implementation. Elyâs (1999) theoretical framework includes eight conditions of educational technology implementation (CETI): Availability of time, Existence of knowledge and skills, Leadership, Participation, Availability of resources, Commitment, Rewards, Dissatisfaction with the status quo.
The research study used and applied quantitative research methods of data collection. The data was collected from 307 instructors who were teaching at five Midwestern state community colleges at the time of survey completion. Data collection was accomplished through the use of an electronic survey. There were two sections in the survey questionnaires. The first was a personal demographic questionnaire to collect demographic information from participants of the study. The second was the educational technology integration questionnaire, which included 60 questions and used six-point Likert-like scale items (1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = slightly agree, 5 = agree and 6 = strongly agree) for data collection purposes. An open-ended question was also included at the end of the survey to collect additional comments about instructorsâ self-perceptions of educational technology integration and facilitative factors that influence them to integrate educational technology.
The research study specifically investigated the effects of these predictor variables (degree program, gender, academic rank, education level and facilitative conditions) by addressing the following research questions through null hypothesis:
1. Are there differences in instructorsâ beliefs about educational technology integration into teaching and learning based on discipline (degree program)? There was a statistically significant difference between English, Education, and Humanities disciplines and Engineering, Technology, and Energy disciplines. The ANOVA showed statistical significance with the following F (9,297) = 1.93, p =.047) values. Therefore, H-null:1 was rejected due to the differences in between disciplines.
2. Are there differences in the factors related to educational technology integration into teaching and learning between male and female instructors? There was no statistically significant difference in means and standard deviation scores between male and female instructors based, on the sample t-test analysis. The t-test examination revealed the following results: (t 305 =1.074; p=.284 >0.05). Therefore, H-null: 2 was retained due to no statistical differences between male and female instructors in terms of educational technology integration.
3. Are there differences in competencies in educational technology integration among instructors based on academic ranks (professor, associate professor, assistant professor, instructor, lecturer, and other)? Overall, there were small differences in mean scores between instructor ranks in terms of educational technology (ET) integration. However, the ANOVA test showed no statistically significant differences between faculty ranks. The one-way ANOVA was equal to F (5,301) = .793, p =.555). Therefore, H-null: 3 was retained, due to no statistical differences between instructors based on faculty ranks.
4. Are there differences in technology integration into teaching and learning based on the facilitative conditions (time, skills, leadership, participation, resources, commitment, rewards, and dissatisfaction with the status quo)? Based on ANOVA results, there were statistically significant differences between community colleges in terms of facilitative factors. The one-way ANOVA had a F value of (4,302) = 3.817, p =.005). Therefore, H-null: 4 was rejected due to statistical difference between community colleges in terms of facilitative conditions.
5. Are there differences in educational technology training needs of instructors based on educational level (trade/technical/vocational training, associate degree, bachelorâs degree, masterâs degree, professional degree, or doctorate degree)? Based on the ANOVA result, there was a statistically significant difference between groups in terms of technology training needs. The ANOVA test had an F value of (2,304) = 5.929, p =.003). Therefore, H-null: 5 was rejected due to statistical differences between instructors based on the educational level.
Turayev, Oybek, "Educational Technology Integration Among Community College Instructors" (2018). Theses and Dissertations. 2368.