An Example of Utilizing Students' Reflections in e-Portfolios for Program Evaluation: A Qualitative Content Analysis
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As the growth of online programs in higher education accelerated across the nation, concerns have been addressed regarding the quality of online programs. The evaluation of programs for quality assurance has become an important component of successful online programs (Kindgren, Nilsson, and Wiklund, 2012, Martinez, Liu, Watson, and Bichelmeyer, 2006). Deggs and Weaver (2009) stated that student perception is "essential to improving the quality of instruction in higher education" (p. 41). In the online program evaluation literature, majority of evaluation studies commonly collected students' perceptions of their learning outcomes and their learning experiences through survey questionnaires. Few studies had been conducted on using students' reflections in e-portfolios for program evaluation in higher education. The purpose of this study was to explore how students' reflections in their e-portfolio can be used as a mechanism for program evaluation. This study employed a qualitative content analysis method. Seventy students' reflections in their e-portfolios of an online master's program were collected. Three types of reflections in e-portfolios have been reviewed and analyzed: (1) students' reflections on their previous approaches to the five tasks of instructional design including design, development, utilization, management, and evaluation; (2) the students' reflections on their current approaches to these five instructional design tasks; and (3) the perceptions on their learning experiences in this online master's program. Two overarching themes emerged from the students' reflections including students' perceptions on their learning outcomes and their learning experiences in the program. The results of the study indicated that students' reflections in their e-portfolios provide another dimension of qualitative information for program evaluation with respect to students' perceptions, and this qualitative data can be used in conjunction with other methods of data collection to conduct a comprehensive evaluation of online programs.
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