Survey analyser: Effective processing of academic questionnaire data

Abstract

Many universities conduct survey research in order to evaluate and improve quality of their education processes. Surprisingly, replacing traditional paper-based questionnaires with electronic ones usually decreases response rates and thus negatively affects overall reliability of results. In the paper, this issue is addressed and an effective approach to academic surveying is described, including a recommended strategy, matrix-based questionnaire representation, methods and technical framework for data handling. A crucial part of this method is the Survey Analyser – an innovative application, which automates the processing of questionnaire results using information extraction and transformation. The proposed surveying method and the corresponding software were successfully implemented into production environments at two universities, showing good performance based on real-life results.