This study explored the factors that impact students' perception of technology benefits and their impact on overall university student satisfaction of 522 undergraduate students at a large Midwestern research university. The purpose of the study was to identify personal (input) and environmental measures that impact student's overall university satisfaction (output), using Astin's Input-Environment-Output (I-E-O) theory as the theoretical framework (Astin, 1993). The study followed a quantitative, non-experimental design, and used a series of constructed scales to measure perceived technology benefits and overall student satisfaction. The Student Experience in the Research University (SERU) survey was administered in 2013 at the campus studied. Results from the Technology module, along with core data provided by the institution, measured the personal and environmental predictor variables. Multiple variable regression and path analysis were used to construct the resulting path diagram. The results of the regression to predict Perceived Technology Benefits indicated a combination of variables explained 25.5% of the variance, depicting a statistically significant model with a small to medium effect size. Results show the Perceived Technology Benefits variable was significantly correlated with seven predictor variables: Instructor Technology Ability, Social Networking, Online Course Preference, Instructor Technology Usage, Engagement with Faculty, Course Specific Behaviors, and Proficiency Social Dimensions. Out of these, the first four entered into the path analysis model. The two strongest predictors were related to the environment, while the other two were input variables. The results of the regression to predict Overall Student Satisfaction indicated a combination of variables explained 32.9% of the variance, depicting a statistically significant model with a medium effect size. Overall Student Satisfaction was significantly correlated with all 13 predictors, with nine entering into the path analysis model: Instructor Technology Ability, Technology Obstacles, Course Specific Behaviors, Instructor Technology Usage, Engagement with Faculty, Socioeconomic Status, Proficiency Social Dimensions, and Online Course Preference. Year-in-school bordered on significance (p = 0.058) and was also included in the final model. This resulted in five input variables and four environmental variables impacting Overall Student Satisfaction. The second research question asked, "Does college of enrollment affect Perceived Technology Benefits and moderate the effects of the technology experience on Overall Student Satisfaction?" College was found to have a significant impact on Perceived Technology Benefits at the p < 0.05 level, but was not found to be significant for Overall Student Satisfaction. Increased emphasis and ongoing research related to technology usage, student and faculty technology satisfaction, implementation, oversight, and administration are recommended in order to properly guide U.S. postsecondary campus instructional technology investments. [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.]