Emerging Technologies in Language Pedagogy: Language Learners' Perceptions through the Lenses of Innovation Diffusion and User Intention Theories

Abstract

Recently, it has been admitted by many researchers that students today are "digital natives" who already utilize several different technologies everyday with different purposes. Furthermore, while there is a plethora of research about learners' perceptions in language pedagogy, there is a paucity of information and research that could move beyond generic perception studies especially regarding new technologies. Accordingly, educators are still concerned not only with how to encourage EFL learners to adopt emerging technologies that could be invaluable in their language learning processes, but also with how to keep students interested in what they are learning. Thus, an understanding beyond students' perceptions with a purposive focus on their approach to technology by also exploring factors that have an influence on their adoption of emerging technologies is the key to knowing how to motivate students to integrate new technologies, and how to keep students interested in the learning process. Therefore, the purpose of this study was three-fold: to identify language learners' approaches to technologies; to examine their attitude toward emerging technologies with a focus on their familiarity, actual use, intentions and perceptions; and finally to analyze the factors and relationships among these factors that best predict language learners' intentions and decisions to use emerging technologies. The study specifically aimed to explore the following emerging technologies: (a) social networking, (b) mobile learning, and (c) digital games as major emerging technologies of today with also a focus on other emerging technologies: (a) augmented reality, (b) wearable technologies, (c) virtual assistants, (d) massive online open courses, (e) 3D printing and (f) online language learning platforms. This mixed methods study benefitted from multiple disciplines, and presented several different perspectives to achieve its aim. The data were obtained through a survey, open-ended questions, and semi-structured interviews. The quantitative data were analyzed through descriptive and inferential statistics. In addition, structural equation modeling was utilized and path analysis was employed to draw on two complementary frameworks: innovation diffusion theory (Rogers, 2003), especially its application in technology adopter categories (TACI) (Dugas, 2005), and the decomposed theory of planned behavior (DTPB) (Taylor & Todd, 1995), which was adapted for this research. The qualitative data was analyzed through thematic content analysis, and used to triangulate and affirm what the quantitative data was showing. The findings indicated that technology adopter categories were normally distributed among EFL learners at a public and a private university in Turkey. Although most EFL learners were quite familiar and confident with major emerging technologies, they were not very familiar with minor emerging technologies. As for an awareness of the benefits of all listed emerging technologies, the study revealed that EFL learners' awareness is quite high; however, it was also found that participants' intention to use these emerging technologies and their actual use were very low. Finally, the results showed that the adapted DTPB was useful in explaining much of the variance in the intention to integrate technology into language learning processes by EFL learners, and attitude was the most important predictor and factor of behavioral intention. Given these findings, this research aims to contribute to the literature in innovation diffusion, user adoption and language pedagogy by offering several theoretical, methodological, and pedagogical implications and directions for future research and applications.