Mining Student Experience and Feedback in Social and Professional Issues in IT: Basis for Understanding Blended Learning

Abstract

In most organizations, surveys are conducted for copious objectives. Surveys are traditions of collecting data that has become the voice of the customer relayed and conveyed anonymously or blatantly. Various learning institutions, mostly universities at large, has made it customary to allow students answer surveys intended to collect views on their overall assessment covering their satisfaction in the entire course as the semester concludes. In Jose Rizal University, student feedback is collected in various survey formats. One of which is called the Canvas Learning Experience survey that provides opportunity to the learners to comment on the proficiency of the implementation of the blended learning course. It seeks student comments on specific areas for improvement in the teaching and learning process. The conveyance of whether these students are immensely satisfied with their learning environment and experience matters mostly to the university treating them as customers and partners. One of the significant objectives of this research is to develop a blended learning feedback mining system that empowers the educational institution administration to inspect at the reproaches of their clients’ learning experience in the blended learning course and thus upgrade them accordingly. The conceptual framework of this research centers on catching and investigating criticism information from students’ perceptions basing from their qualitative comments using text mining. In turn, the framework will give the fundamental structure in the implementation of the feedback mining system that the university may utilize for addressing the results of the Canvas Experience survey.