Measuring digital literacy: Development and validation of an instrument for teachers


Thesis Type: Postgraduate

Institution Of The Thesis: Middle East Technical University, Faculty of Education, Department of Computer Education and Instructional Technology, Turkey

Approval Date: 2023

Thesis Language: English

Student: YUNUS PAŞALI

Principal Supervisor (For Co-Supervisor Theses): Göknur Kaplan

Co-Supervisor: Ayşe Gül Kara Aydemir

Abstract:

Digital literacy is gaining more attention as digitalization and digital transformation accelerate. Many studies attempt to define it as a concept, glean its components and to assess individuals' digital literacy levels. The field of education, and specifically teachers, as main agents of the field, are no exception. Setting off from this point, this study aims to develop and validate a scale to measure the digital literacy levels of teachers working in primary schools. Pursuing this aim, an extensive literature review is conducted by analyzing and synthesizing various studies. Based on this synthesis and in consideration with Bloom's Taxonomy, a conceptual digital literacy framework was created, consisting of 54 components gathered under three main domains, i.e. cognitive, technical, and social. Utilizing this framework, an item pool of 459 statements were created, and filtered down to a total of 67 five-point Likert-type items after four editing and revision sessions with experts. A total of 432 teachers filled out this draft scale. The collected data were used for exploratory factor analysis (EFA), which yielded to a 12-item scale that was further filled out by 125 teachers. These data were used for confirmatory factor analysis (CFA) to validate and finalize the 12-item scale which measures 11 components from two domains, i.e., cognitive and technical. The responses given to the final scale were also descriptively reported. The findings showed that all of participant teachers perceive themselves as digitally literate. They are aware of fundamental digital concepts and self-learning methods; they can extrapolate the digital innovations and use the technology effectively and efficiently in a secure way.