Department of English, NCCU

[Talk Announcement]

Title: What Makes a Good Test? Insights from Language Testing Research

Speaker: Dr. Jui-Teng Liao, Assistant Professor, Institute of Applied English, National Taiwan Ocean University

Host: Professor Siaw-Fong Chung, Department of English, National Chengchi University

Time: May 14 (Thu.) 10:00–12:10

Venue: Room 140208 (2F), Information Building, National Chengchi University

Host: Department of English, National Chengchi University

Advised by National Science and Technology Council

Registration: https://forms.gle/MQWtXW1AhKVwiMby7

Registration deadline: 7 May 2026

Abstract:

What makes a language test “good”? How do we know whether test scores are meaningful, fair, and truly reflect learners’ abilities? And in the age of artificial intelligence, can machines help us design better tests?

In this talk, Dr. Liao from National Taiwan Ocean University explores these questions through two empirical studies in language assessment. First, drawing on research with Taiwanese adolescent English learners, he examines which features of students’ writing, such as grammar, organization, and sentence structure, predict their performance on integrated listening-to-write tasks, and how providing vocabulary support to facilitate understanding of the source text relates to test validity. He then turns to a more recent study on AI in L2 reading assessment, investigating whether AI-generated test materials can match or even outperform those developed by human experts.

Along the way, the talk introduces common quantitative methods used in language testing, showing how data can inform test design and evaluation. Together, these studies offer insights into how we define, evaluate, and innovate language assessments in today’s rapidly evolving landscape.

Biodata:

Dr. Liao is an Assistant Professor in the Institute of Applied English at National Taiwan Ocean University. His research focuses on language assessment, including L2 integrated writing and reading, test development and validation, and score generalizability, using quantitative, qualitative, and mixed-methods approaches. His work has appeared in top-tier international journals, including Language Testing, Language Assessment Quarterly, Journal of English for Academic Purposes, and Assessing Writing. He has also conducted interdisciplinary research published in the International Journal of Science Education. His recent work explores the application of generative artificial intelligence in language assessment.