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Using Text Analysis to Assess Qualitative Student Works, Deal with Inter-rater Reliability, and Simultaneously Comply with AACSB Standard 8 and Middle States Standard V

Guy H. Gessner and Karen M. Kutt-Doner

The BRC Academy Journal of Education

Volume 5

Number 1

Print ISSN: 2152-8756 Online ISSN: 2152-8780

Date: March 15, 2016

First Page 53

Last Page 74

DOI: http://dx.doi.org/10.15239/j.brcacadje.2016.05.01.ja03

Abstract

The purpose of this research is to determine if the analytical process of text analysis or text mining can be adapted successfully as a tool to help automate assessment of student works related to ways in which they demonstrate progress in meeting institutional and accreditation standards. Student works in this case are assignments from graduate and undergraduate courses in business. An electronic library with six dictionaries was built containing Jesuit and Catholic keywords, phrases, concepts and synonyms so text analysis has the ability to identify these institutional learning goals within student work products. Conclusions from this study are that text mining can be adapted successfully as an automated solution for assessing large volumes of student works without involvement of large numbers of assessors and therefore without the problem of inter-rater reliability that comes from using multiple human assessors.

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