Sentiment Analysis to Evaluate Teaching Performance

Abstract

[Abstract]: The aim of the present work is to review a specific learning analytics method - sentiment analysis - in the field of Higher Education, showing how it is employed to monitor student satisfaction on different platforms, and to propose an architecture of Sentiment Analysis for Higher Education purposes, which trace and unify what emerges from the literature review. First, an in-depth literature review is carried out, which proves the widespread and increasing interest of the communities, of both scholars and practitioners, in the use of sentiment analysis in the field of Higher Education. The analysis, focused on three different e-learning domains (i.e., learning diaries, Twitter and MOOCs), identifies weaknesses and gaps, and in particular the lack of a unifying approach which is able to deal with the different domains. Secondly, a prototype architecture – LADEL (Learning Analytics Dashboard for E-Learning) - is introduced, which is able to deal with the different e-learning domains. Some preliminary experiments are carried out, highlighting some limitations and open issues, as stimulus to continue the development of the platform.