Technology Acceptance Among Teachers: An SLR on TAM and Teachers

Abstract

owadays, the introduction of information and communication technologies in formal education contexts is still an interesting study subject for the research community. The fast technological development entails a constant change process where new information systems and devices emerge on a daily basis. This constant change demands an effort on the part of educational agents in order to adapt to the new possibilities. Teachers bear a determinant weight in technology innovation processes. Consequently, there is a rising number of studies focused on analysing the attitude of teachers towards the use of ICTs within their classrooms. Knowing the factors that lead teachers to accept ICTs is especially useful both to guide the development of educational technologies and to design teacher training initiatives. One of the most used tools to develop studies on technology adoption is the TAM (Technology Acceptance Model). This theory, which comes from the field of behavioural psychology, is widely used in spheres such as organisational sciences, electronic commerce or health technologies, on account of its parsimony and easy adaptation. In the past few decades, the application of TAM and TAM-based models has been extended to the field of education. Today, we can find studies that use these models to explore the attitudes of teachers and students. Our research is based on the development of a Systematic Literature Review (SLR) of publications related to the use of TAM or TAM-based models to conduct quantitative empirical studies on the acceptance of ICTs on the part of teachers. To this end, we have used three repositories: SCOPUS, ISI WOS, and Google Scholar, where we have introduced the terms TAM AND "technology Acceptance Model" AND "in-service teachers". We have obtained 248 results from all the repositories, to which we have applied several exclusion and inclusion criteria. Once the article selection was made, we carried out a meta-analysis by extracting data regarding different variables, such as the country of the study, the educational level, the technology under study and the model employed. The results offer an overview of the state-ofthe- art of the research in this field.