Universities are using standardized tests more and more as part of their accountability and assessment of student learning efforts. For the results of these tests to be useful in improving practices that lead to greater learning, they must be meaningful and specific to institutions. The researcher sought to determine how student characteristics, motivation to perform well on the test, and various academic experiences were related to performance on the Collegiate Learning Assessment (CLA) and how much variance in CLA scores was explained by the factors examined. In 2005, 276 incoming freshmen agreed to participate in a four-year longitudinal study using the CLA at the University of Wyoming. Students were asked to take a nearly three-hour version of the CLA in fall 2005, spring 2007, and spring 2009. In addition to completing the test, students were administered a CLA Participant Survey to determine their motivation to perform well on the CLA. These data were combined with additional data from student transcripts to evaluate academic experiences and accompanying performance. This study was a quantitative study employing several statistical methods. The researcher used correlational analysis to determine the relationships between the variables examined and CLA scores. Factor analysis and regression analyses were used to determine how much variance in CLA scores was explained by the different student characteristic, motivation, and academic experience variables included in the study. Results were presented for two study phases: Phase 1 from 2005 to 2007 and Phase 2 from 2005 to 2009. Of the variables and factors examined in this study, incoming ability as measured by ACT composite score, time-on-task, motivation, and grade point averages were most correlated with CLA scale scores for both phases of the study. Time-on-task was the best predictor of CLA scores for both phases of the study followed by ACT composite score and motivation. Two academic factors, the number of English, math, and humanities-social sciences credits earned and overall academic performance, were predictors of CLA scale scores in Phase 1 of the study but not for Phase 2. Finally, far more of the variance in CLA scale scores was explained the factors examined compared to CLA value-added scores for both phases of the study. Only time-on-task and the number of science credits earned explained any of the variance in value-added scores in either phase of the study. The results of this study have implications for institutions, test developers, and policy makers. Institutions need to address motivation in low-stakes testing environments and explore other possible factors contributing to performance on such assessments. Test developers need to continue to respond to the needs of institutions for more specific information regarding results. Policy makers need to be educated on the results so they are used appropriately and in context. Further study is recommended, including but not limited to, trying different testing protocols and environments to increase motivation and aligning the administration the CLA with other ongoing assessments such as the National Survey of Student Engagement. [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://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]