Identifying and Evaluating Language-Learning Technology Tools

Abstract

Digitization and the globalization of English have made it possible to incorporate different forms of digital technology into the infrastructure of English language programs. However, there are no clear criteria in the existing literature to identify and evaluate appropriate language-learning technology tools. To fill the gap, this project proposed empirically supported guidelines in a rubric called the ULTIA Rubric to facilitate and accelerate the process of identifying and evaluating technology-supported language-learning tools. The ULTIA Rubric has its basis in the major components of the five concepts of universal design for learning (UDL), learning science (LS), technology acceptance model (TAM), intelligent tutoring system (ITS), and automatic speech recognition (ASR). The rubric can function as a practical solution for program administrators, instructors, and English language learners (ELLs) who are seeking a reliable roadmap to evaluate language-learning software.