From Face-to-Face to Screen-to-Screen: CFL Teachers' Beliefs about Digital Teaching Competence during the Pandemic
Chun Zhang
International Journal of Chinese Language Teaching · 2020
doi:10.46451/ijclt.2020.06.03 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
As coronavirus lockdowns have moved many face-to-face language teaching activities online, the use of virtual classrooms has quickly escalated. The drastic shift in venue calls for massive changes in methods and approaches to teaching languages. This study concerns the beliefs held by language teachers about modes of online language teaching and self-assessment of digital competence. The study investigates seven teachers teaching Chinese as a foreign language (CFL) in a higher education context in Denmark. The study aims to go beyond the current prevailing research on the predicaments of teachers by making their endeavors and contributions visible and meaningful during the Covid-19 pandemic. The study employs a discovery-oriented qualitative approach, largely drawn from personal narrative and ethnographic research from a sociological perspective. The aim of this study is twofold: firstly, we provide a clear picture of what expertise is available for teaching CFL online; secondly, we investigate pedagogical competence that CFL teachers need to acquire when digital teaching modes override and replace traditional teaching modes. The findings indicate that beliefs held by teachers matter in terms of the digital tools and tasks they choose to utilize. The extent to which teachers acquire digital competence depends on whether the teachers have been allocated ample institutional time to upgrade their existing pedagogical competence and how they exert their degree of teacher agency. The results of this study are expected to provide insights into redefining overarching standards of CFL pedagogy and teacher education in an era of post-Covid-19 language education.
Abstract licence: CC BY
References25
25 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.