Abstract
This work has the goal to make an approximation of the evolution and general features present in scientific production disclosed in Web of Science and in Scopus, related to the study of user experience in education. The work analyzes the totality of the production registered in the indexation systems taken as a case of study, 194 records obtained from the use of terms user experience and edoucation. The study carries out a content analysis of the abstract and institutional, editorial and author information exposed in the Web of Science andScopus, in addition to the analysis of the bibliometric indicators of each identified work. Obtained data show that more than 80% of the scientific production around the topic addressed, mostly generated in scientific events, has been produced in the last 5 years, under the authorship and institutional affiliation of academic institutions and publishers from the United States. This would point out to a new academic framework, of growing interest, around the analysis of the user experience from an educational perspective, conditioned bya highly focused debate on a geographical area, which is assuming a prominent role in the first approaches that are emerging on this subject, at the scientific level.
Keywords
Education; User experience; Scientific production; Users; Scopus; Web of Science
Nota: * Del 2003 al 2014 el análisis comprende 44 casos. ** 2015 al 2018, comprende 119 casos. La nube de palabras se ha creado con WordArt. La normalización de los términos es realizada por la herramienta de forma automática. La herramienta analiza todas las palabras utilizadas, y da mayor importancia a los términos que aparecen más veces, de modo que dichos términos aparecen con mayor tamaño. Los términos compuestos los analiza como términos separados, y elimina de forma automática el uso del guion (-). Fuente: Elaboración propia (2018).
Nota: Se muestran solamente los términos que han aparecido un mínimo de 5 ocasiones en los títulos y resúmenes analizados. El gráfico se ha realizado con el programa VosViewer, que agrupa por colores los clústers de palabras y asigna el tamaño a los nodos según su presencia en la red. Fuente: Elaboración propia (2018).