Performance and achievement in a fully-online classroom is based upon the successful completion of tasks that can only be accomplished through the use technology. This often involves a two-tiered problem-solving and critical-thinking decision tree—one strand involves an understanding of the navigation and usability of the LMS, while the other concurrent strand involves an emergent understanding of course-specific content. These dual constraints add anxiety to the user’s experience. Coupled with these constraints is the user’s “lack of voice” in determining the institutional and individual selection of a particular LMS required for degree completion, as well as the LMS functionalities, heuristics, and interactivity expectations that facilitates the user’s cognitive growth. In Fall, 2009 the latest version of Blackboard LMS—9.0—was adopted at a small liberal arts college that offers one undergraduate degree fully in the distance education format as well as many additional departmentally-sponsored online offerings. At the conclusion of each semester, students are e-mailed a Student Reaction to the Effectiveness of Instruction (SREI) questionnaire centered on feedback regarding the instructor; the course materials; structure and requirements; effectiveness regarding traditional versus online delivery, all on a scale of strongly agree to strongly disagree or in the case of delivery format, from more effective to less effective. At the conclusion of the questionnaire, students are provided the opportunity to respond to four open-ended questions. These are: 1) what experiences in the course were most beneficial; 2) what would you change about the course; 3) please write any comments you have about the Blackboard course software (trouble logging on, software interruptions, disconnections, etc.); and 4. other comments about any aspect of the course or the online experience. Blackboard 9.0 LMS student users are speaking in their experiential and practical virtual voices when responding to the SREI open-ended questions. A content analysis will be used to hear what LMS students are saying and what they need to achieve success in online learning.