Using Text Mining for Improving Student Experience Management in Higher Education

Using Text Mining for Improving Student Experience Management in Higher Education

Chong Ho Yu (Arizona State University, USA), Samuel A. DiGangi (Arizona State University, USA) and Angel Jannasch-Pennell (Arizona State University, USA)
DOI: 10.4018/978-1-60960-599-5.ch012
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Abstract

The objective of this case study is to illustrate how text mining of open-ended responses from a student survey could yield valuable information for improving student experience management (SEM). The concept of student SEM was borrowed from the notion of customer experience management (CEM), which aims for ongoing improvement of customer relations through understanding of the customer’s point of view (Pine & Gilmore 1998). With the advance of text mining technology, textual data that were previously underutilized are found to be valuable in CEM. To illustrate how text mining can be applied to SEM, we discuss an example from a campus-wide survey conducted at Arizona State University. The purpose of this survey was to better understand student experiences with instructional technology in order for administrators to make data-driven decisions on its implementation. Rather than imposing the researchers’ preconceived suppositions on the students by using force-option survey items, researchers on this project chose to use open-ended questions in order to elicit a free emergence of themes from the students. The most valuable lesson learned from this study is that students perceive an ideal environment as a web of mutually supporting systems. Specifically, online access should be augmented by use of laptops and availability of course materials, whereas virtual classes should be balanced by human interactions.

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