Doctor of Philosophy (PhD)
First Committee Member
Number of Pages
As the mystery and intrigue surrounding technology use in higher education dissipates, the time has come to bring technological initiatives, such as distance education, into the fold with the rest of campus in terms of assessment, accountability, and policy. Although online education shows promise for setting the collegiate learning experience free from the confines of the lecture hall, new challenges are emerging. For example, attrition rates for courses delivered via the Internet are higher than average, typically ten percentage points higher in online courses than in the traditional campus classroom. In an era of declining resources and renewed interest in accountability of higher education, high attrition rates are troublesome; Funding sources continue to press for accountability and higher education administrators require tools for evaluating campus programs. Since learning communities, as a course design strategy, have proven successful in confronting the challenges associated with attrition and retention, faculty may be able to meet these challenges by building learning communities within their online courses. This study chronicles a five-stage research project for designing a valid and reliable measure of an "Online Learning Community." Using exploratory factor analysis, a three-element theoretical construct emerged. Data from this study is used to create a student exit survey for use by faculty leaders and program administrators to evaluate their own online courses and distance programs. Information from this survey can also be used as a data point in a comprehensive institutional assessment formula used to inform stakeholders, including policy makers.
Community; Distance Education; Exit; Exit Survey; Framework; Learning; Learning Community; Online; Qualitative; Students; Survey; Virtual
Education, Higher; Educational technology
University of Nevada, Las Vegas
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DiRamio, David C, "Virtual learning community: A student exit survey and qualitative framework" (2004). UNLV Retrospective Theses & Dissertations. 2607.
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