Exploring the pedagogical efficacy of automated, AI-based diagnostic tools in self-regulated English learning
Dr Long Li1, A/Professor Mira Kim
1Unsw Sydney, , Australia
This presentation reports from a pilot study that reviews and synthesizes third-party tests and tools, especially those of an automated nature based on artificial intelligence (AI), to help international students diagnose their English language proficiency. UNSW has been offering a unique self-directed English language course titled Personalised English Language Enhancement (PELE). Based on a Personalised Autonomous pedagogical model (Kim 2014), this course guides students to identify aspects of their English language skills that they might need to further enhance and develop a personal project to improve one aspect. In this learning environment, the diagnosis assessment of students’ English is the vital first step before students could develop their personalized project but students find it a challenging task. In fact, there are very few diagnostic tools that seem readily available for self-directed learners like PELE students. While diagnostic tests based on teacher evaluation have been developed within PELE, they restrict timeliness and finance in a large cohort. On the other hand, literature indicates potential of automated diagnostic tools in improving student engagement and learning largely due to timeliness and reliability in assessing specific forms of English such as pronunciation (cf. Bingham, Holbrook and Meyers, 2010; Gleason 2014). This pilot study reviews tests and tools with a diagnostic potential and explore their validity, reliability and pedagogical efficacy in the context of PELE in 2021 at UNSW through analysing student e-portfolios and focus groups. In particular, it examines the pedagogical efficacy in introducing automated tools for students’ self-diagnosis and ongoing progress measurement.
Biography:
Mira Kim is an Associate Professor in Translation and Interpreting Studies at the School of Humanities and Languages, Faculty of Arts and Social Sciences, UNSW.
Her research interests are divided into three categories: translation studies, Systemic Functional Linguistics (SFL) and personalised language learning. The three main research fields are synergetically integrated, which empowers her to expand her research areas and share her knowledge beyond her boundary. For example, she undertook a research project entitled English Language Acquisition Support for International Students (ELASIS) funded by UNSW (SEF#2). Through the project, she developed a course called Personalised English Language Enhancement (PELE) to help students to enhance their English language skills. This credit-bearing course is offered every semester from 2017 benefiting many students, international and domestic, across faculties at UNSW.
Recently, she has published a book, Systemic Functional Linguistics and Translation Studies (2021). She now is working on another book, Korean Grammar: A Systemic-Functional Approach.
Long Li is a Lecturer in Translation & Interpreting in the School of Humanities and Languages, Faculty of Arts and Social Sciences. His research interests include systemic functional linguistics (SFL), ideology in translation, and teacher training. He is passionate about exploring innovative pedagogies and technologies to inspire and empower learners in the 21st century. He has taught students from UG level to HDR candidates, and convened a range of courses in translation and English communication.