Sentiment Analysis to Evaluate Teaching Performance

Author:

Adinolfi Paola1,D'Avanzo Ernesto1,Lytras Miltiadis D.2,Novo-Corti Isabel3,Picatoste Jose4

Affiliation:

1. University of Salerno, Fisciano, Italy

2. The American College of Greece, Greece

3. University of A Coruna, A Coruna, Spain

4. University Autonoma of Madrid, A Coruna, Spain

Abstract

The aim of this 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, a 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, 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.

Publisher

IGI Global

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Novel Hybrid Machine Learning Model for Analyzing E-Learning Users’ Satisfaction;International Journal of Human–Computer Interaction;2023-05-28

2. Text-Based Sentiment Analysis of Students' Satisfaction: An Input to Strategic Plan;2022 2nd International Conference in Information and Computing Research (iCORE);2022-12

3. Analysis of scientific dissemination posts on Facebook from a social media approach;2022 17th Iberian Conference on Information Systems and Technologies (CISTI);2022-06-22

4. What Factors Influence Students Satisfaction in Massive Open Online Courses? Findings from User-Generated Content Using Educational Data Mining;Education and Information Technologies;2022-03-30

5. Polarities Inconsistency of MOOC Courses Reviews Based on Users and Sentiment Analysis Methods;Lecture Notes in Electrical Engineering;2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3