{"id":107,"date":"2024-04-19T14:06:17","date_gmt":"2024-04-19T06:06:17","guid":{"rendered":"http:\/\/localhost:8080\/?page_id=107"},"modified":"2024-04-19T14:54:23","modified_gmt":"2024-04-19T06:54:23","slug":"panel_discussions","status":"publish","type":"page","link":"https:\/\/www.lttc.org.tw\/2024IC\/panel_discussions\/","title":{"rendered":"Panel_Discussions"},"content":{"rendered":"

This conference will feature two panel discussions (listed in order of presentation), each aiming to harness the insights of experts to delve deeper into specific issues. The focuses of the two panel discussions will be the GEPT iPrep project, which is an AI-enhanced learning and assessment platform, and student support in English education at the tertiary level in Taiwan, respectively. The format for each panel will include initial presentations of individual ideas by the panelists, followed by an interactive Q&A session. For details of the time and venue, please see the program<\/u><\/a>.<\/div>\n<\/div><\/div><\/div><\/div><\/div>
Topic<\/strong><\/u>
\nTransforming Language Learning and Testing in Taiwan: An AI-Assisted Scoring System Approach<\/strong><\/div>\n<\/div>
Abstract<\/div>\n<\/div>
The GEPT iPrep project, a three-year initiative supported by Taiwan’s National Development Council under the 2030 Bilingual Policy, is dedicated to a singular mission: the development of an AI-assisted automated scoring system tailored specifically for the General English Proficiency Test (GEPT) in Taiwan. A diverse interdisciplinary team comprising language assessors, corpus linguists, computational linguists, and information\/data scientists have provided input on the project, with the goals of enhancing the accessibility and effectiveness of English language education and enriching the English learning process by providing learners with timely and constructive feedback.<\/div>\n<\/div>
In its inaugural year, the project embarked on a series of tasks that were deemed essential, including preparation of training materials for the speaking scoring models, the development of a speech recognition system, the training of scoring models utilizing both benchmark and local learner corpora, and the creation of automatic scoring systems tailored to diverse task types and a comprehensive evaluation of the systems\u2019 effectiveness. Effort was also devoted to enhancing the writing component, including the preparation of training materials, the expansion of Taiwan’s English Learner Corpus, and the development of automatic scoring systems, complemented by error detection and correction mechanisms.<\/div>\n<\/div>
Noteworthy progress has so far been achieved in a variety of areas including the implementation of automated scoring for picture description tasks in both writing and speaking, as well as paragraph-level read-aloud tasks, coupled with personalized feedback for each individual’s performance. These innovations not only aspire to meet global standards but also maintain a keen focus on the requirements of the Taiwanese context. Furthermore, the project is poised to significantly enhance the accuracy, efficiency, and comprehensiveness of GEPT scoring practices.<\/div>\n<\/div>
This panel discussion consists of an introduction to the bilingual policy and an overview of the GEPT iPrep project, followed by three paper presentations, a synthesis by the discussant and discussion with audience. Beyond the outcomes of the first year’s work, the presentations underscore the importance of fostering the independent development of scoring technology within a specific context. By leveraging specialized resources, the project not only benefits local learners but also contributes insights into the challenges encountered during such endeavors. These challenges, along with their potential solutions, are carefully considered and discussed, further enriching the broader discourse on technology-enhanced language assessment.<\/div>\n<\/div><\/div><\/div><\/div><\/div>
Chair<\/div>\n<\/div><\/div><\/div>
<\/span><\/div>

Sherry Hsin-ying Li
\n\u674e\u6b23\u7a4e<\/strong><\/p>\n<\/div>

CEO of the Language Training & Testing Center (LTTC)
\nProfessor, Department of Foreign Languages and Literatures, National Taiwan University<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Sherry Hsin-ying Li<\/strong> is the Chief Executive Officer at the Language Testing and Training Center (LTTC) in Taipei, Taiwan, and a professor of English at National Taiwan University. She holds a Ph.D. in English from the State University of New York at Buffalo and specializes in American Literature, especially late nineteenth-century American fiction. Since taking up the post of CEO, she has been supervising the test administrations, training programs, and research projects at the LTTC, including the government-sponsored BEST Test of English Proficiency for College Students and the LTTC\u2019s AI-assisted automated scoring system.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Panelists<\/div>\n
(listed in alphabetical order)<\/div>\n<\/div><\/div><\/div>
<\/span><\/div>

Connie Hui-chuan Chang
\n\u5f35\u60e0\u5a1f<\/strong><\/p>\n<\/div>

Director General, Department of Overall Planning, National Development Council<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Connie Hui-chuan Chang<\/strong> is the Director General of Department of Overall Planning at the National Development Council, R.O.C. (Taiwan). Her major responsibilities include formation of the economy\u2019s development plans, and international affairs covering bilateral cooperation with the U.S., EU, Australia, Japan, etc., and participation in international organizations such as APEC. Major tasks which she has been orchestrating include the Ministerial-level Digital Economy Forum (Dialogue) with the U.S. and EU, Taiwan\u2019s latest engagement with Central and Eastern Europe, particularly Lithuania, Czech, Slovakia and Poland for economic cooperation, as well as Taiwan\u2019s Bilingual 2030 policy and the cross-ministerial coordination of Just Transition strategy in Taiwan\u2019s Pathway to Net Zero by 2050.<\/div>\n
Connie was the chief negotiator for Taiwan\u2019s negotiation with the United States Trade Representative on the Good Regulatory Practice Chapter in the Taiwan-U.S. Initiative on 21st-Century Trade.<\/div>\n
Previously, Connie was the Executive Director of the Regulatory Reform Center of the National Development Council, which main responsibility was cross-ministerial coordination of regulatory reforms on issues raised by foreign Chambers of Commerce in Taiwan. She was also engaged in the task for planning Taiwan\u2019s regulator adjustment to the digital economy.<\/div>\n
Connie also worked with the Ministry of Economic Affairs in her first 11 years in the government, with main responsibility of facilitating foreign investment into Taiwan.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div>
<\/span><\/div>

Jason S. Chang
\n\u5f35\u4fca\u76db<\/strong><\/p>\n<\/div>

Department of Computer Science, National Tsing Hua University<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Jason S. Chang<\/strong> received his Ph.D. in Computer Science from New York University, and has been with the Department of Computer Science at National Tsing Hua University since 1986. Professor Chang founded Linggle Language Technology, a startup specializing in Large Language Models and Generative AI. His scholarly pursuits encompass diverse areas, including AI-Assisted Language Learning, Automated Essay Scoring, Grammatical Error Correction, and Computational Lexicography. Professor Chang is known for leading the development of the Linggle linguistic search engine and making it freely available to the public.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div>
<\/span><\/div>

Berlin Chen
\n\u9673\u67cf\u7433<\/strong><\/p>\n<\/div>

Department of Computer Science and Information Engineering, National Taiwan Normal University<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Berlin Chen<\/strong> is a Professor of the Computer Science and Information Engineering Department at National Taiwan Normal University (NTNU), Taipei, Taiwan. He received his Ph.D. degree in computer science and information engineering from National Taiwan University (NTU) in June 2001, and then joined NTNU as an Assistant Professor in August 2002. He became a Professor in February 2010. Prof. Chen\u2019s research interests generally lie in the areas of speech recognition and natural language processing, multimedia information retrieval, computer-assisted language learning, and artificial intelligence.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div>
<\/span><\/div>

Zhao-Ming Gao
\n\u9ad8\u7167\u660e<\/strong><\/p>\n<\/div>

Department of Foreign Languages and Literatures at National Taiwan University<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Zhao-Ming Gao<\/strong> earned his Ph.D. in Language Engineering from the University of Manchester Institute of Science and Technology (UMIST) in 1998. He joined the Department of Foreign Languages and Literatures at National Taiwan University in 1999, where he now serves as a professor. Dr. Gao has contributed as a reviewer for various conferences and journals, including COLING, PACLIC, Lexical Resources and Evaluations, and Computer-Assisted Language Learning. Dr. Gao specializes in developing corpus-based computational tools and has published extensively in the fields of corpus linguistics, computer-assisted translation, and intelligent computer-assisted language learning.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div>
<\/span><\/div>

Jessica R. W. Wu
\n\u5433\u82e5\u8559<\/strong><\/p>\n<\/div>

Director General for R&D, Language Training & Testing Center (LTTC)<\/div>\n<\/div>

<\/i><\/i><\/span>Bio<\/span><\/a><\/h4><\/div>
\n
Jessica R. W. Wu<\/strong> holds a PhD in Language Testing and serves as Director General for R&D at the Language Testing & Training Center (LTTC) in Taipei, Taiwan. Her major projects have included overseeing the creation of the General English Proficiency Test (GEPT). Widely recognized in the testing community, Dr. Wu received the Alan Davies Lecture Award in 2022, becoming the first East Asian scholar and non-native English-speaking recipient to do so. She currently oversees the government-sponsored BEST Test of English Proficiency for College Students, as well as EAP, EMI, and CLIL training programs for teachers.<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Topic<\/strong><\/u>
\nEnhancing Student Support in the University in the Tertiary Level, Taiwan<\/strong><\/div>\n<\/div>
Abstract<\/div>\n<\/div>
The Program on Bilingual Education for Students in College (BEST program), launched by the Ministry of Education (MOE) in 2021, focuses on elevating students’ English proficiency for effective international communication, such as in EMI contexts. This initiative underscores the necessity of developing comprehensive support mechanisms to enhance students’ general, academic, and professional English skills.<\/div>\n<\/div>
Motivated by this policy, Taiwanese higher education institutions have established and executed various student support programs. Currently, it is crucial to assess the outcomes of these efforts, with particular emphasis on the transition from general English to English for Academic Purposes (EAP), which is integral for students engaged in English Medium Instruction (EMI) courses. Additionally, given the varied English proficiency levels among Taiwanese students, special consideration is required for students with lower motivation and proficiency. The advent of digital and AI technologies plays a significant role in facilitating personalized learning experiences, offering timely, individualized support.<\/div>\n<\/div>
This panel discussion will critically evaluate the student support initiatives influenced by the BEST policy. Esteemed international and domestic scholars and experts will deliberate on the planning and execution of these initiatives at the tertiary level. Discussion points include:<\/div>\n<\/div>
\n