Understanding why people accept or reject e-learning technologies has become one of the most challenging issues in education research. Thus, this study set out to determine the effects of factors that influence service-learning faculty to include e-learning technologies in their curriculum. The principal study population was 134 service-learning faculty from urban, suburban, and rural two-year and four-year colleges and universities. Of these, 108 (80.6%) were female while 26 (19.4%) were male. Half of the participants (51.5%) had more than 1 year of technical experience, followed by 29.1% with less than 1 year and 19.4% had no technical experience. The study expanded upon the Technology Acceptance Model and the Theory of Planned Behavior and added one construct from the Diffusion of Innovation Theory. Multiple linear regression analysis was done to determine the extent to which dependent variables were predicted by independent variables followed by the path analysis of the research model. Further, analyses were conducted for the hypothesized pathways using a multiple regression framework. The results of this regression analyses showed that none of the covariates (gender, age, technology experience, teaching experience, and location) nor any of the interactions with the corresponding respective variables, had a significant effect. Thus, the covariates were excluded from the path analysis. A final multiple regression analysis was conducted with six independent variables (attitude, subjective social norm, compatibility, perceived usefulness, perceived ease of use, and perceived behavioral control) and one dependent variable (behavioral intention). The main effects of attitude and compatibility were statistically significant (R[superscript 2] = 0.682, F = 45.38, p less than 0.000) indicating that they are significant predictors of faculty behavioral intention to use e-learning technologies. Once these significant predictors were established, the hypothesized model was further analyzed using PLS modeling. The main finding of the path analysis was that subjective social norm and compatibility had a strong positive effect on perceived usefulness ([beta]=0.21, p less than 0.001; [beta]=0.61, p less than 0.001; respectively) as did perceived usefulness and perceived ease of use on attitude ([beta]=0.72, p less than 0.001; [beta]=0.18, p less than 0.01, respectively). Attitude exhibited a strong positive effect on behavioral intention ([beta]=0.72, p less than 0.001). Further, the qualitative data confirmed that perceived usefulness played a role in understanding why people accept or reject technologies. According to the quantitative findings e-learning technologies are compatible with the service-learning faculty's workstyle. However, in the interviews all of the service-learning faculty mentioned that meaningful human interaction may suffer in the process. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]