21st Workshop on Innovative Use of NLP for Building Educational Applications

Quick Info
Co-located with	ACL 2026
Location	San Diego, California, United States
Dates	July 3-4, 2026
Organizers	Ekaterina Kochmar, Bashar Alhafni, Stefano Bannò, Marie Bexte, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anaïs Tack, Victoria Yaneva, Zheng Yuan
Deadline	March 23 March 30, 2026
Submission	https://softconf.com/acl2026/bea2026/
Contact	bea.nlp.workshop@gmail.com
GitHub	To share your code and data with the BEA community, feel free to use the #bea-workshop topic.

Description

The BEA Workshop is a leading venue for NLP innovation in the context of educational applications. It is one of the largest one-day workshops in the ACL community with over 100 registered attendees in the past several years. The growing interest in educational applications and a diverse community of researchers involved resulted in the creation of the Special Interest Group in Educational Applications (SIGEDU) in 2017, which currently has over 400 members.

The workshop’s continuing growth reflects how technology is increasingly fulfilling societal demands. For instance, the BEA16 workshop in 2021 hosted a panel discussion on “New Challenges for Educational Technology in the Time of the Pandemic” addressing the pressing issues around COVID-19. Additionally, NLP has evolved to aid diverse learning domains, including writing, speaking, reading, science, and mathematics, as well as the related intra-personal (e.g., self-confidence) and inter-personal (e.g., peer collaboration) skills. Within these areas, the community continues to develop and deploy innovative NLP approaches for use in educational settings.

Another significant advancement in educational applications within the Computational Linguistics (CL) community is the continuing series of shared-task competitions organized by and hosted at the BEA workshop. Over the years, this initiative has included four dedicated tasks focused solely on grammatical error detection and correction (with the latest one on Grammatical Error Correction held in 2019. Moreover, NLP/Education shared tasks have expanded into novel research areas, such as Automated Evaluation of Scientific Writing in 2016, Native Language Identification in 2017, Second Language Acquisition Modeling and Complex Word Identification in 2018, Generating AI Teacher Responses in Educational Dialogues in 2023, Automated Prediction of Item Difficulty and Item Response Time and Multilingual Lexical Simplification in 2024, and Pedagogical Ability Assessment of AI-powered Tutors in 2025. These competitions have significantly bolstered the visibility and interest in our field.

The 21st BEA will be a 2-day workshop, with one in-person workshop day and one virtual workshop day. The workshop will feature:

• oral presentation sessions and large poster sessions to facilitate the presentation of a wide array of original research.
• a panel discussion on Transitioning from Academia to the EdTech Industry
• a half-day tutorial on Theory of Mind and its Applications in Educational Contexts
• two shared tasks on Vocabulary Difficulty Prediction for English Learners and on Rubric-based Short Answer Scoring for German comprising an oral overview presentation by the shared task organizers and several poster presentations by the shared task participants

Sponsors

Gold Sponsors

Sponsoring Opportunities

We are extremely grateful to our sponsors for the past workshops. This year, we want to continue helping students to attend the workshop, including the accommodation of the student post-workshop dinner and offering grants covering best paper presentations. We are hoping to identify sponsors who might be willing to contribute $100 (Bronze), $250 (Silver) or $500 (Gold) to subsidize some of the workshop costs. Perks of sponsorship include logos on the workshop website and in the proceedings. If you would like to sponsor BEA, please send us an email.

Call for Papers

The workshop invites submissions to the main track, including both long and short papers. Accepted submissions will be considered for oral or poster presentations.

Topics of interest include, but are not limited to, the application of NLP techniques in educational settings such as:

• automated evaluation of written and spoken open-ended responses
• game-based learning and assessment methods
• educational data mining
• exploring the role and impact of generative AI in education
• intelligent tutoring systems
• collaborative and social learning platforms
• peer assessment and review tools
• grammar error detection and correction
• learner cognition modeling
• spoken dialogue systems
• multimodal educational applications
• annotation standards and linguistic schemas
• tools for teachers, learners, and assessment developers
• corpus-based educational tools and systems

Important Dates

All deadlines are 11:59pm UTC-12 (anywhere on earth). Please note that these deadlines are preliminary and may change slightly.

Event	Date
Submission Deadline	March 23 March 30, 2026
Notification of Acceptance	April 28, 2026
Camera-ready Papers Due	May 12, 2026
Pre-recorded Videos Due	June 4, 2026
Workshop	July 3-4, 2026

Shared Tasks

The workshop will host two shared tasks:

Vocabulary Difficulty Prediction for English Learners

Organizers: Mariano Felice (British Council) and Lucy Skidmore (British Council).

Description: This shared task aims to advance research into vocabulary difficulty prediction for learners of English with diverse L1 backgrounds, an essential step towards custom content creation, computer-adaptive testing and personalised learning. In a context where traditional item calibration methods have become a bottleneck for the implementation of digital learning and assessment systems, we believe predictive NLP models can provide a more scalable, cost-effective solution. The goal of this shared task is to build regression models to predict the difficulty of English words given a learner’s L1. We believe this new shared task provides a novel approach to vocabulary modelling, offering a multidimensional perspective that has not been explored in previous work. To this aim, we will use the British Council’s Knowledge-based Vocabulary Lists (KVL), a multilingual dataset with psychometrically calibrated difficulty scores. We believe this unique dataset is not only an invaluable contribution to the NLP community but also a powerful resource that will enable in-depth investigations into how linguistic features, L1 background and contextual cues influence vocabulary difficulty.

For more information on how to participate and latest updates, please refer to the shared task website.

Rubric-based Short Answer Scoring for German

Organizers: Sebastian Gombert (DIPF), Zhifan Sun (DIPF), Fabian Zehner (DIPF), Jannik Lossjew (IPN), Tobias Wyrwich (IPN), Berrit Katharina Czinczel (IPN), David Bednorz (IPN), Sascha Bernholt (IPN), Knut Neumann (IPN), Ute Harms (IPN), Aiso Heinze (IPN), and Hendrik Drachsler (DIPF)

Description: Short answer scoring is a well-established task in educational natural language processing. In this shared task, we introduce and focus on rubric-based short-answer scoring, a task formulation in which models are provided with a question, a student answer, and a textual scoring rubric that specifies criteria for each possible score level. Successfully solving this task requires models to interpret the semantics of scoring rubrics and apply their criteria to previously unseen answers, closely mirroring how human raters assign scores in educational assessment. Although rubrics have been used as auxiliary information in prior work on free-text scoring and LLM-based approaches, there has been little focused investigation of rubric-based short-answer scoring as a task in its own right. This setting poses distinct challenges, including ambiguous or underspecified rubric criteria and a wide range of valid student responses. With this shared task, we aim to stimulate systematic research on rubric-based scoring, assess how well current NLP methods can reason over rubrics, and identify promising modeling strategies. Additionally, by providing a German-language dataset, the shared task contributes a new non-English benchmark to the field.

For more information on how to participate and latest updates, please refer to the shared task website.

Tutorial

The workshop will feature a half-day tutorial:

Theory of Mind and Application in Educational Context

Organizers: Effat Farhana (Auburn University), Maha Zainab (Auburn University), Qiaosi Wang (Carnegie Mellon University), Niloofar Mireshghallah (Carnegie Mellon University), Ramira van der Meulen (Leiden University), Max van Duijn (Leiden University).

Description: This tutorial examines the integration of Theory of Mind (ToM) into AI-driven online tutoring systems, focusing on how advanced technologies, such as Large Language Models (LLMs), can model learners’ cognitive and emotional states to provide adaptive, personalized feedback. Participants will learn foundational principles of ToM from cognitive science and psychology and how these concepts can be operationalized in AI systems. We will discuss mutual ToM, where both AI tutors and learners maintain models of each other’s mental states, and address challenges such as detecting learner misconceptions, modeling meta-cognition, and maintaining privacy in data-driven tutoring. The tutorial also presents hands-on demonstrations of Machine ToM applied to programming education using datasets such as CS1QA and CodeQA, which contain Java and Python samples. By combining conceptual foundations, research insights, and practical exercises, this tutorial provides a comprehensive overview of designing human-centered, ethically aware, and cognitively informed AI tutoring systems.

Panel

The workshop will feature a panel discussion on “Transitioning from Academia to the EdTech Industry.” This panel aims to share practical insights, career pathways, challenges, and lessons learned by individuals who have navigated (or actively support) the move from academic careers into industry roles within educational technology.

The panel will be of interest to graduate students, postdoctoral researchers, faculty, and academic staff considering or preparing for careers in EdTech startups, established companies, or industry research labs.

The panel will address topics including:

• Motivation for transitioning from academia to EdTech
• Differences in culture, expectations, and impact between academia and industry
• Translating academic skills (research, teaching, publishing) to industry roles
• Career paths in EdTech (e.g., product, research, UX, data science, learning design)
• Advice for early-career researchers and faculty considering the transition

Panelists were selected from an open call based on several criteria, including relevant experience, diversity of perspectives, clear communication of insights, engagement with the BEA community, and ability to attend the workshop in person.

Christine Bagarino (Social AI)

Christine Bagarino, Social AI

Bio: Christine Bagarino is the founder of Social AI, an AI native startup based in Tokyo, Japan, that builds AI technology for positive social impact. A former educator, curriculum developer, and Silicon Valley product manager, Christine developed Japan’s first LLM-powered English learning chatbot approved for K12 public education. In 2023, she traveled to rural Vietnam for an EdTech pilot funded by the Asian Development Bank, which inspired her to make fun and quality English learning accessible to children all over the world.

Kai North (Cambium Assessment)

Kai North, Cambium Assessment

Bio: Dr. Kai North is a Senior Data Scientist at Cambium Assessment Inc. Kai earned his PhD in Information Technology at George Mason University, Virginia. He specializes in machine learning and natural language processing applied to educational and assessment technologies and has multiple top-tier publications at venues such as ACL, COLING, and ACM computing surveys.

Keelan Evanini (NBME)

Keelan Evanini, NBME

Bio: Keelan Evanini has been a researcher in the field of natural language processing (NLP) for educational and conversational applications for more than 15 years. He is currently a Lead NLP Scientist at the National Board of Medical Examiners, where he conducts research into using conversational AI for interactive, scenario-based learning applications for medical students. Prior to joining NBME in 2025, he served as SVP of engineering and AI at Kasisto, a New York-based startup company that provides conversational AI solutions to financial institutions. From 2009-2020, he worked at Educational Testing Service as a research scientist and research director, where he conducted research into automated scoring of non-native spoken English for language proficiency assessment and spoken dialog systems for language learning applications. Keelan received a PhD in linguistics from the University of Pennsylvania in 2009 and is a Senior Member of the IEEE. He has published over 90 peer-reviewed papers and has been awarded 11 US patents.

Mariano Felice (British Council)

Mariano Felice, British Council

Bio: Mariano leads the artificial intelligence (AI) strategy for language learning and assessment at the British Council. His role involves researching the application of natural language processing (NLP) to language assessment, providing strategic guidance for the development and adoption of AI solutions, and promoting AI literacy and responsible use of new technologies.
With over a decade of experience, Mariano has worked on a wide range of topics, including grammatical error correction, automatic error typing, system evaluation, automated cloze test generation and item difficulty prediction. He has published numerous scientific papers in top-tier NLP conferences and is a regular speaker at international conferences as well as a reviewer for workshops, journals and conferences in his field. Mariano is also a visiting scholar at the University of Reading and the University of Cambridge.

Committees

Organizing Committee

• General Chair: Ekaterina Kochmar, MBZUAI
• Program Chairs:
  • Andrea Horbach, Hildesheim University
  • Ronja Laarmann-Quante, Ruhr University Bochum
  • Marie Bexte, FernUniversität in Hagen
• Publication Chair: Anaïs Tack, KU Leuven, imec
• Shared Task & Tutorial Chairs:
  • Victoria Yaneva, National Board of Medical Examiners
  • Bashar Alhafni, MBZUAI
• Sponsorship Chair:
  • Zheng Yuan, King’s College London
  • Jill Burstein, Duolingo
• Virtual Chair: Stefano Bannò, Cambridge University

Program Committee

• Rania Abdelghani (Hector Institute of Educational Sciences and Psychology, University of Tübingen)
• Tazin Afrin (NBME)
• Soroosh Akef (Leibniz-Institut für Wissensmedien)
• Syeda Sabrina Akter (George Mason University)
• Vennela Akula (Auburn University)
• Erfan Al-Hossami (University of North Carolina at Charlotte)
• Ali Al-Laith (University of Copenhagen)
• Giora Alexandron (Weizmann Institute of Science)
• David Alfter (Gothenburg University)
• Norah Almousa (University of Pittsburgh)
• Aitor Arronte Alvarez (University of Hawaii at Manoa)
• Nischal Ashok Kumar (University of Massachusetts Amherst)
• Sina Bagheri Nezhad (Independent Researcher)
• Xiaoyu Bai (University of Potsdam)
• Mohmaed Basem (MSA University)
• Michael Gringo Angelo Bayona (Trinity College Dublin)
• Lee Becker (Pearson)
• Beata Beigman Klebanov (Educational Testing Service)
• Milena Belosevic (Bielefeld University)
• Enrico Benedetti (Utrecht University)
• Luca Benedetto (Telecom SudParis, IP Paris)
• Maryam Berijanian (Michigan State University)
• Ummugul Bezirhan (Boston College, TIMSS and PIRLS International Study Center)
• Abhidip Bhattacharyya (University of Massachusetts, Amherst)
• Ted Briscoe (MBZUAI)
• Dominique Brunato (Institute of Computational Linguistics “A. Zampolli” (ILC-CNR), Pisa)
• Andrew Caines (University of Cambridge)
• Jie Cao (University of Oklahoma)
• Dumitru-Clementin Cercel (University Politehnica of Bucharest)
• Bharathi Raja Chakravarthi (University of Galway, Ireland)
• Imran Chamieh (Hochschule Ruhr West)
• Ignatios Charalampidis (University of Tuebingen)
• Andreas Chari (University of Glasgow)
• Mei-Hua Chen (Department of Foreign Languages and Literature, Tunghai University)
• Artem Chernodub (Zendesk)
• Luis Chiruzzo (Universidad de la Republica)
• Hyundong Cho (USC, Information Sciences Institute)
• Declan Clowry (Social AI)
• Longwei Cong (DIPF ; Leibniz Institute for Research and Information in Education)
• Yan Cong (Purdue University)
• Mark Core (University of Southern California)
• Steven Coyne (Tohoku University / RIKEN)
• Orphee De Clercq (LT3, Ghent University)
• Kordula De Kuthy (IWM Tübingen)
• Jasper Degraeuwe (Ghent University)
• Carrie Demmans Epp (University of Alberta)
• Yuning Ding (Leibniz Institute for Science and Mathematics Education)
• Rahul Divekar (Bentley University)
• George Duenas (Universidad Pedagogica Nacional)
• Marius Dumitran (University of Bucharest)
• Andreea Dutulescu (National University of Science and Technology Politehnica Bucharest)
• Yo Ehara (Tokyo Gakugei University)
• Walid El Hefny (Leibniz-Institut für Wissensmedien (IWM))
• Effat Farhana (Auburn University)
• Mariano Felice (British Council)
• Michael Flor (Educational Testing Service)
• Jennifer-Carmen Frey (EURAC Research)
• Momoka Furuhashi (Tohoku University / National Institute of Informatics)
• Thomas Gaillat (Rennes 2 university)
• Martina Galletti (Sony Computer Science Laboratories - Paris ; Sapienza University of Rome)
• Diana Galvan-Sosa (University of Cambridge)
• Ashwinkumar Ganesan (Amazon Alexa AI)
• Lingyu Gao (Duolingo)
• Jie Gao (McGill University)
• Rujun Gao (Texas A&M University)
• Ritik Garg (Extramarks Education Pvt. Ltd.)
• Voula Giouli (Aristotle University of Thessaloniki / ILSP, ATHENA RC)
• Aron Gohr (Independent)
• Sebastian Gombert (DIPF ; Leibniz Institute for Research and Information in Education)
• Kiel Gonzales (University of the Philippines Diliman)
• Mark Edward Gonzales (Agency for Science, Technology and Research (A*STAR), Singapore)
• Cyril Goutte (National Research Council Canada)
• Stuart Grey (University of Glasgow)
• Viktor Gulbrandsen (University of Oslo)
• Pranav Gupta (Cisco)
• Abigail Gurin Schleifer (Weizmann Institute of Science)
• Ibrahim Hallac (Østfold University of Applied Sciences)
• Ching Nam Hang (Assistant Professor, Yam Pak Charitable Foundation School of Computing and Information Sciences, Saint Francis University, Hong Kong)
• Jiangang Hao (Educational Testing Service)
• Hasnain Heickal (University of Massachusetts Amherst)
• Nicolas Hernandez (Nantes University)
• Jingying Hu (Purdue University)
• Chung-Chi Huang (Frostburg State University)
• Aiden Huang (Acton-Boxborough Regional High School)
• Phoebe Huang (University of Florida)
• Anna Huelsing (CAU)
• Catherine Ikae (Applied Machine Intelligence, Bern University of Applied Sciences, Switzerland)
• Fareya Ikram (University of Massachusetts Amherst)
• Joseph Marvin Imperial (University of Bath)
• Radu Tudor Ionescu (University of Bucharest)
• Md. Rakibul Islam (Ahsanullah University of Science and Technology)
• Elsayed Issa (Purdue University)
• Raunak Jain (Intuit)
• Abhishek Jariwala (Auburn University)
• Helen Jin (University of Pennsylvania)
• Léane Jourdan (Nantes University)
• Indika Kahanda (University of North Florida)
• Tomoyuki Kajiwara (Ehime University / The University of Osaka)
• Anisia Katinskaia (Swiss Data Science Center)
• Fatemeh Kazemi Vanhari (McMaster University)
• Elma Kerz (Exaia Technologies)
• Samin Khan (Stanford University)
• Sachiko Kimura (Rikkyo University, Dokkyo University)
• Mamoru Komachi (Hitotsubashi University)
• Maxim Konca (Goethe University Frankfurt)
• Katsunori Kotani (Kansai Gaidai University)
• Joni Kruijsbergen (LT3, Ghent University)
• Andrei Kucharavy (HES-SO Valais-Wallis)
• Aayush Kucheria (Aalto University)
• Roland Kuhn (National Research Council of Canada)
• Gaurav Kumar (University of California San Diego)
• Ravi Kumar (Florida International University (FIU))
• Alexander Kwako (University of California, Los Angeles)
• Antonio Laverghetta Jr. (Pennsylvania State University)
• Jaewook Lee (UMass Amherst)
• Seolhwa Lee (Technical University of Darmstadt)
• Bernardo Leite (Faculty of Engineering - University of Porto)
• Arun Balajiee Lekshmi Narayanan (University of Pittsburgh)
• Hannah Levin (Stanford University)
• Jiazheng Li (King’s College London)
• Xu Li (Southwest Petroleum University)
• Junhong Liang (MBZUAI)
• Wen Liang (Columbia University)
• Chuan-Jie Lin (National Taiwan Ocean University)
• Yudong Liu (Western Washington University)
• Zhexiong Liu (University of Pittsburgh)
• Denise Loefflad (Leibniz-Institut fuer Wissensmedien Tuebingen)
• Julian Lohmann (Christian Albrechts Universität Kiel)
• Benny Longwill (Educational Testing Service)
• Anastassia Loukina (Grammarly Inc)
• Wanning Lu (Stanford University)
• Li Lucy (University of Washington)
• Sarah Löber (University of Tübingen)
• Jakub Macina (ETH Zurich)
• Nitin Madnani (Duolingo)
• S.M Afridi Mahmud (Bangladesh University of Engineering and Technology)
• Maria Monica Manlises (De La Salle University)
• Zhenjiang Mao (University of Florida)
• Jacek Marciniak (Adam Mickiewicz University)
• Arianna Masciolini (Språkbanken Text; Department of Swedish, Multilingualism, Language Technology; University of Gothenburg)
• Sandeep Mathias (Presidency University)
• Hunter McNichols (University of Massachusetts Amherst)
• Detmar Meurers (Leibniz-Institut für Wissensmedien (IWM))
• Daniel Mora Melanchthon (CAU Kiel / Leibniz Institute for Science and Mathematics Education)
• Phoebe Mulcaire (Duolingo)
• Laura Musto (Universidad de la Republica)
• Farah Nadeem (LUMS)
• Sungjin Nam (ACT, Inc)
• Diane Napolitano (The Washington Post)
• Léo Nebel (LIP6 - Sorbonne Université)
• Seyed Parsa Neshaei (EPFL)
• Duy Anh Nguyen (Independent Researcher)
• Huy Nguyen (Oracle)
• S Jaya Nirmala (National Institute of Technology Tiruchirappalli)
• Sergiu Nisioi (Human Language Technologies Research Center, University of Bucharest)
• Adam Nohejl (RIKEN)
• Kai North (Cambium Assessment Inc.)
• Similoluwa Okunowo (AIMS South Africa)
• Kostiantyn Omelianchuk (Grammarly)
• Amin Omidvar (PhD student at the Department of Electrical Engineering and Computer Science, York University)
• Daniel Oyeniran (University of Alabama)
• Alonso Palomino (DFKI (German Center for Artificial Intelligence Research))
• Nisarg Parikh (University of Massachussetts, Amherst)
• Jeiyoon Park (Smilegate)
• Kseniia Petukhova (MBZUAI)
• Tomasz Pilka (Adam Mickiewicz University in Poznan)
• Pagnarith Pit (University of Melbourne)
• Lucie Polakova (Charles University)
• Long Qin (Alibaba)
• Mengyang Qiu (Saint Elizabeth University)
• Chatrine Qwaider (MBZUAI)
• Md. Abdur Rahman (Islamic University of Technology (IUT), OIC)
• Pranil Raichura (Independent Researcher)
• Anmol Rao (Arizona State University)
• pranshu rastogi (Independent Researcher)
• Sparsh Rastogi (Thapar Institute of Engineering and Technology)
• Manav Rathod (University of California, Berkeley)
• Hanumant Redkar (Goa University, Goa)
• Saed Rezayi (National Board of Medical Examiners)
• Luisa Ribeiro-Flucht (University of Tuebingen)
• Frankie Robertson (University of Jyväskylä)
• Shadman Rohan (Center for Computational & Data Sciences, IUB)
• Aiala Rosá (Instituto de Computación, Facultad de Ingeniería, Universidad de la República)
• Mahule Roy (University of Oxford)
• Alla Rozovskaya (Queens College, City University of New York)
• Josef Ruppenhofer (Fernuniviersität in Hagen)
• Mariam Saeed (Applied Innovation Center)
• Pravish Sainath (Vanier College, Université de Montréal)
• Jonathan Sakunkoo (University of Oxford)
• Alexander Scarlatos (University of Massachusetts Amherst)
• Nils-Jonathan Schaller (Leibniz Institute for Science and Mathematics Education)
• Stephanie Schoch (University of Virginia)
• Dhruv Shah (Sardar Patel Institute of Technology)
• Natarajan Balaji Shankar (University of California Los Angeles)
• Matthew Shardlow (Manchester Metropolitan University)
• Qian Shen (University of Florida)
• Gyu-Ho Shin (University of Illinois Chicago)
• Hyo Jeong Shin (Sogang University)
• Ziqi Shu (Stanford University)
• Astha Singh (Iowa State University)
• Li Siyan (Columbia University)
• Lucy Skidmore (British Council)
• Anastasia Smirnova (San Francisco State University)
• Mariia Soliar (Leibniz-Institut für Wissensmedien (IWM))
• Alexey Sorokin (Moscow State University)
• Shankhalika Srikanth (Independent Researcher)
• Felix Stahlberg (Google Research)
• Katherine Stasaski (Google DeepMind)
• Helmer Strik (Centre for Language and Speech Technology (CLST), Centre for Language Studies (CLS), Radboud University Nijmegen)
• Parisa Suchdev (University of Vermont)
• Hakyung Sung (Rochester Institute of Technology)
• Andreas Säuberli (LMU Munich)
• Kyosuke Takami (Osaka Kyoiku University)
• Wenjia Tan (University of Macau)
• CheeWei Tan (NanyangTechnologicalUniversity)
• Takehito Utsuro (University of Tsukuba)
• Martin Vainikko (University of Tartu)
• Sowmya Vajjala (National Research Council)
• Piper Vasicek (Brigham Young University)
• Justin Vasselli (Nara Institute of Science and Technology)
• Hariram Veeramani (UCLA)
• Giulia Venturi (Institute of Computational Linguistics “Antonio Zampolli” (ILC-CNR))
• Anthony Verardi (Duolingo)
• Elena Volodina (University of Gothenburg)
• Anh-Duc Vu (University of Helsinki)
• Deliang Wang (The University of Hong Kong)
• Nikhil Wani (OpenThreads AI / University of Southern California)
• Taro Watanabe (Nara Institute of Science and Technology)
• Alistair Willis (The Open University)
• Yiheng Wu (University of Helsinki)
• Bushi Xiao (University of Florida)
• Hiroaki Yamada (Tokyo Metropolitan University)
• Bi-Cheng Yan (National Taiwan Normal University)
• Haiyin Yang (University of Florida)
• Roman Yangarber (University of Helsinki)
• Sahar Yarmohammadtoosky (NBME)
• Tahreem Yasir (North Carolina State University)
• Su-Youn Yoon (EduLab)
• Marcos Zampieri (George Mason University)
• Fabian Zehner (DIPF ; Leibniz Institute for Research and Information in Education)
• Torsten Zesch (Computational Linguistics, FernUniversität in Hagen)
• Jing Zhang (Emory University)
• Yiling Zhao (Stanford University)
• Yang Zhong (University of Pittsburgh)
• Ej Zhou (University of Cambridge)
• Yiyun Zhou (NBME)
• Jessica Zipf (University of Konstanz)
• Michael Zock (CNRS-LIS)
• Robert Östling (Department of Linguistics, Stockholm University)