Increasing the impact of ICT in language learning: Investigating the effect of teachers’ ownership of microblending CALL in the classroom within the WST model of ICT use.

Abstract

This thesis aims to address why the adoption of CALL (Computer Assisted Language Learning) within the language classroom is so varied, and its success so unclear, despite fifty years of investment and research. The huge promise of ICT (Information and Communications Technology) driven results has created an imbalance in language teaching, where initiatives are brought about from outside the classroom, with teachers held accountable for their adoption. My reading of the literature is that lack of consideration of the teacher’s role in implementation of classroom technology has led to mismatched expectations and performance. If the nature of the teacher’s contribution is recognized, I believe that this can lead to more effective use of ICT, which I have set out to show. My study, based on a survey of 319 EFL (English as a Foreign Language) teachers across the international group of 31 schools in which I work, seeks to put the teacher back into the picture by examining where their enacted beliefs in social constructivist pedagogy best align with classroom use of digital technology. I coin this emerging praxis ‘microblending’, a pedagogy rooted in Second Language Acquisition (SLA) theory and contemporary methodology, and I seek to demonstrate its relevance in this study I test the viability of measuring teacher’s microblending readiness through application of Technology Acceptance Modelling (TAM) in an EFL setting to produce a model that explains the variation in classroom use of ICT. My model is based on a critical replication of the WST (‘Will, Skill, Tool’) model, a TAM model which has so far only been used in mainstream classroom teaching. I have updated, created and piloted new instruments within the scope of the study, which are now already in use within the institution where I carried out my investigations. Using both linear regression and Structural Equation Modelling (SEM) techniques I explored how these measurements of the learning environment can explain a teacher’s application of technology. This first attempt appears to explain over 89% of the variation in classroom use of technology, which already exceeds the predictive power of several contemporary models in use in parallel fields of education. Given further work to refine and apply the model, a valuable improvement could be made in how teachers work with ICT in the language classroom for improved learning outcomes.