Autor segons l'article: Grimalt-Alvaro, C; Usart, M
Departament: Pedagogia
Autor/s de la URV: Grimalt Alvaro, Maria del Carme / Usart Rodríguez, Mireia
Paraules clau: Technology Review of literature Online Higher education Gender Artificial intelligence technology students review of literature polarity higher education gender feedback emotions attitudes
Resum: Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has been applied for learning assessment in online and hybrid learning contexts in higher education. Findings from this review show that there is a growing field of research on SA, although most of the papers are written from a technical perspective and published in journals related to digital technologies. Even though there are solutions involving different SA techniques that can help predicting learning performance, enhancing feedback and giving teachers visual tools, its educational applications and usability are still limited. The analysis evidence that the inclusion of variables that can affect participants’ different sentiment expression, such as gender or cultural context, remains understudied and should need to be considered in future developments.
Àrees temàtiques: Pedagogical & educational research Education & educational research Education Educació Computer science (all) Ciencias sociales
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: mireia.usart@urv.cat carme.grimalt@urv.cat
Identificador de l'autor: 0000-0003-4372-9312 0000-0002-5314-7706
Data d'alta del registre: 2024-08-03
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://link.springer.com/article/10.1007/s12528-023-09370-5
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Journal Of Computing In Higher Education.
Referència de l'ítem segons les normes APA: Grimalt-Alvaro, C; Usart, M (2023). Sentiment analysis for formative assessment in higher education: a systematic literature review. Journal Of Computing In Higher Education, (), -. DOI: 10.1007/s12528-023-09370-5
DOI de l'article: 10.1007/s12528-023-09370-5
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2023
Tipus de publicació: Journal Publications