Visualization analysis of OSPTE comments
Reddy, Muskula Sai Deep
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Reddy, M. S. D. 2021. Visualization analysis of OSPTE comments -- In Proceedings: 17th Annual Symposium on Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University
The teaching evaluation instrument used by Wichita State University for Face-to-Face classes is called SPTE (Student Perception Teaching Evaluation). When WSU moved to online teaching, the social science lab at WSU developed the OSPTE (O stands for Online classes) that was administered online. Students rated the teachers and typed in their comments, as opposed to writing them by hand with SPTE. The typed comments are a source of data that can be analyzed and visualized to give faculty feedback on their teaching. We developed an online app that can do just that. Once we receive the paper packet of OPSTE evaluations for a course, we scan the comments pages as an image into a PDF file. We then take the PDF file and convert it to a Word document using an online tool (we provide a tutorial on how to do that safely). We then strip the file of all headers, footers, titles, and question statements i.e., we just keep the student comments then save the file as a TEXT file. We go to the online application and drag/drop the text file to the appropriate box or use the Select Files option to browse and upload the file. A sentiment analysis of the comments is performed in the background and the faculty will get a visualization dashboard displayed on the webpage. This includes a word cloud, count of popular words in comments, and count of positive and negative words in the comments. This app is built using python which takes the text file that contains students comments as input and uses available packages in python such as nltk package to remove stop words, to generate output visualization we use word cloud, ploty and matplotlib packages and finally dash and flask packages are used to display output on dashboard. The app design and functionality will be discussed, as well as future work.
Presented to the 17th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held online, Wichita State University, April 2, 2021.
Research completed in the Department of Electrical Engineering and Computer Science, College of Engineering; Department of Finance, Real Estate, & Decision Sciences, W. Frank Barton School of Business