Portraying University Instructors Based on their Cybercultural Competence

Abstract

This paper presents the progress made in the research project Development of digital and cybercultural competences through techno-educational innovations (PRIMAR-UNC Project 2020–2022), which aims to assess the types and levels of digital and cybercultural competences among teaching staff in order to promote innovation in teaching. The results of the development of an assessment tool for self-perceived cybercultural competences amongst teaching staff at the National University of Córdoba (UNC) in Argentina are presented. To this end, various instruments from the Transmedia Literacy (Scolari, 2018) and Ikanos (Ferrari, 2013) projects were combined and adapted to form an ad hoc questionnaire, which was administered to 528 UNC teaching staff in 2021; they completed the questionnaire voluntarily, constituting a non-probability sample. The study utilised 13 dimensions of cybercultural competences defined on the basis of the conceptual frameworks developed in the aforementioned projects, which were adapted to the university context. The teaching staff was then classified according to their level of competence, with the aim of implementing innovative initiatives to support student learning, such as training programmes, collaborative work and the production of teaching materials. The data were analyzed using latent profile analysis (LPA), a person-centered statistical technique that identifies subgroups of individuals with similar response patterns. Six latent classes were identified, ranked from the most basic to the most advanced levels of cybercultural competences. Given the heterogeneity of the teaching staff, the results provide guidance for designing training proposals that are more relevant and tailored to the identified profiles.