Evaluating Students Computer-Based Learning Using A Visual Data Mining Approach
Antonina Durfee, Scott Schneberger, and Donald Amoroso
Educators are increasingly using online computer-based training and assessment software—especially with large classes or in distance education settings. This technology is often criticized, however, for hampering personalized interaction with students. This paper introduces a unique approach for analyzing student characteristics influencing their adoption and use of computer-based educational technology so that instructors can better meet student learning needs. Using visual, self-organizing mapping, our data mining approach clustered students based on input data from thirty-six survey questions posed to over 400 students with experience using computer based training and assessment. The data mining technique provided clear descriptions of four different student clusters. Based on the unique characteristics of the four clusters, instructors could optimize classroom resources as well as provide individualized support once specific students are matched to their respective cluster group. In this manner, continual computer-based assessments of students can be used to maximize computer-based learning and evaluation.
Keywords: cbt, cba, training, assessment, educational technology, hybrid classes, data mining, som, self-organizing map
Antonina Durfee is an Assistant Professor at Appalachian State Univeristy in Boone, USA. She holds a Ph.D. degree from Abo Akademi University . Her currents research is in text mining, knowledge discovery, human issues in echology adoption and seeking behavior. She has been published in the International Journal of Intelligent Systems in Accounting, Finance, and Management , and the International Journal of Digital Accounting Research.
Scott Schneberger is an Associate Professor at the Walker College of Business, Appalachian State University, Boone, North Carolina. Previously, Scott taught at Georgia State University in Atlanta, Georgia, and the Richard Ivey School of Business, University of Western Ontario. Scott has taught information systems courses to undergraduate and graduate CIS students, MBAs, and executive MBAs at five schools, and conducted executive development information systems courses to corporations. Scott is also the co-editor of the ISWorld web site on Theories Used in IS Research (winner of the ISWorld 2005 web page award).
Dr. Donald L. Amoroso is Professor and Department Chair of Information Systems at Appalachian State University. Donald teaches classes in information systems, system development, and strategy formulation with executive MBA students. Prior to his appointment at ASU, he served as Associate Professor and Coordinator of Information & Decision Sciences at San Diego State University. He has published in journals such as Journal of Management Information Systems, Data Base, and Information & Management. Dr. Amoroso has consulted with over 30 organizations working with CEOs and CIOs to develop and execute a strategic plan for information technology. Donald received his Bachelors degree in accounting and finance from Old Dominion University in 1980 and his MBA and Ph.D. from the University of Georgia in 1984 and 1986, respectively.
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