E-learning university evaluation through sentiment analysis centered on user experience dimensions

被引:0
|
作者
Sanchis-Font, Rosario [1 ]
Castro-Bleda, Maria-Jose [2 ]
Jorda-Albinana, Begona [3 ]
Lopez-Cuerva, Luis [4 ]
机构
[1] Univ Politecn Valencia, Escuela Doctorado, Camino Vera S-N, Valencia 46022, Spain
[2] Univ Politecn Valencia, Inst Univ Valenciano Invest Inteligencia Artifici, Camino Vera S-N, Valencia 46022, Spain
[3] Univ Politecn Valencia, Ctr Invest Tecnol Graf, Dept Ingn Graf, Camino Vera S-N, Valencia 46022, Spain
[4] Univ Miguel Hernandez Elche, Dept Ingn Comunicac, Avda Univ S-N,Edificio Innova,Modulo 3, Alicante 03202, Spain
来源
DYNA | 2023年 / 98卷 / 02期
关键词
user experience; UX; e-learning; virtual learning; sentiment analysis; data mining; MeaningCloud; natural language processing; university online learning; user centered design; UCD; NLP; VLE;
D O I
10.6036/10603
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
center dot The COVID-19 crisis increased the number of users of university online teaching, enhancing the importance of this learning format. Additionally, ISO 9241-210:2019 standard sets the international standards for the design of products, services and interaction systems from usability, accessibility, and user experience (User eXperience -UX) perspective. Then, in order to design interfaces and learning experiences that include motivations, feelings and needs of end users, it is necessary to previously evaluate the UX of these environments, with less general and/or laborious methods than those that currently exist. Therefore, this work aims to establish the basis of a method that allows automatically to evaluate the UX of online teaching platforms by analyzing the users' sentiment about specific aspects of their virtual learning experience. To do this, 2,035 users were surveyed about their online learning experience with a questionnaire and an open text field to give their opinion. The population surveyed were online postgraduate students of the Universitat de Valencia and the Universidad Rey Juan Carlos, and university students of massive open online courses of the Universitat Politecnica de Valencia. The opinions collected in Spanish from 476 students were processed with the commercial sentiment analysis and natural language processing tool MeaningCloud, to analyze the sentiment (positive, negative, or neutral) about aspects of their experience. The results present a new model that, on the one hand, ontologically classifies categories and aspects of online education with sentiment analysis techniques, and on the other hand, the model groups these categories according to UX criteria, presenting its own classification to facilitate the evaluation of online learning experiences in a concrete and automatic way.
引用
收藏
页码:147 / 153
页数:7
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