Short Texts Analysis for Teacher Assistance during Live Interactive Classroom Presentations

TitleShort Texts Analysis for Teacher Assistance during Live Interactive Classroom Presentations
Publication TypeConference Paper
Year of Publication2018
AuthorsMichal Hucko, Peter Gaspar, Matus Pikuliak, Vasileios Triglianos, Cesare Pautasso, and Maria Bielikova
Conference NameWorld Symposium on Digital Intelligence for Systems and Machines (DISA2018)
MonthAugust
PublisherIEEE
Conference LocationKošice, Slovakia
KeywordsASQ, clustering
Abstract

We aim to improve the communication process of a teacher with students during lectures using question answering. Our work is focused on the analysis of students’ answers to support the teacher in his or her lecturing. We work with students’ answers to open questions, where it is impossible to identify finite number of solutions. In large classes it is impossible to react in real time to such answers since their evaluation is time consuming. We propose our own approach that helps the teacher by grouping similar answers. These groups are created based on proposed method employing text classification and clustering. Proposed method automatically estimates a number of clusters in answers using combination of k-Nearest Neighbors (KNN) algorithm and affinity propagation. We evaluated the method on real data in Slovak language collected from the course Principles of Software Engineering using real time presentation system ASQ.

Citation Key2018:asq:disa
Refereed DesignationRefereed