Transforming Student Feedback into Institutional Action Plans: A Data-Driven Approach

Abstract

Surveys serve diverse purposes within most organizations. Floating them has evolved into a way for the voice of the customers to express themselves, whether anonymously or brazenly. Several learning institutions and universities have institutionalized data-driven processes and allow students to answer surveys to collect feedback covering their satisfaction in the entire course as the semester concludes. In Jose Rizal University, student feedback is gathered in several survey instruments. One is the Canvas Experience Survey, through which students share their views on their blended learning experience. It seeks feedback on areas where the teaching and learning process could be improved. This research seeks to develop a system that empowers an educational institution to enhance their blended learning offerings by analyzing student feedback for areas of improvement. An analysis of the student responses from Canvas experience survey is presented quantitatively and a qualitative text mining approach comprising of text pre-processing using lemmatization and n- gram, aspect extraction, sentiment analysis employing VADER, and strategic recommendatory statement action plans shall be accessed by institution's respective groups supporting them to the continuous improvement of the teaching and learning cycle implementation of blended learning courses. As aspects were extracted from responses to each question, statement action plans are accessed by the respective office to address these concerns. It expedites the University stakeholders in course improvement cycles in courses offered under the blended learning programs of the University. A concise and periodical implementation of this study is advocated to collect student feedback in a manner where actual comments from students undergo mining and thus evolved to the most important aspects which leads to recommendatory action plans.