19th Workshop on Innovative Use of NLP for Building Educational Applications


Quick Info
Co-located with NAACL 2024
Location Mexico City, Mexico
Deadline March 10, 2024
Date June 20 or 21, 2024
Organizers Ekaterina Kochmar, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anaïs Tack, Victoria Yaneva, and Zheng Yuan
Contact bea.nlp.workshop@gmail.com

Workshop 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 300 members.

The workshop’s continuing growth highlights the alignment between societal needs and technological advances: for instance, BEA16 in 2021 hosted a panel discussion on New Challenges for Educational Technology in the Time of the Pandemic addressing the pressing issues around COVID19. NLP capabilities can now support an array of 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 breakthrough for educational applications within the CL community is the presence of a number of shared-task competitions organized by the BEA workshop over the past several years, including four shared tasks on grammatical error detection and correction alone. NLP/Education shared tasks have also seen new areas of research, such as the Automated Evaluation of Scientific Writing at BEA11, Native Language Identification at BEA12, Second Language Acquisition Modelling at BEA13, Complex Word Identification at BEA13, and Generating AI Teacher Responses in Educational Dialogues at BEA18. These competitions increased the visibility of, and interest in, our field.

The 19th BEA workshop will follow the format of BEA in 2023 and will be hybrid. We will have three invited talks, a shared task on generation of teacher responses in educational dialogues, oral presentation sessions, and a large poster session to maximize the amount of original work presented. We expect that the workshop will continue to highlight novel technologies and opportunities, including the use of state-of-the-art large language models in educational applications, and challenges around responsible AI for educational NLP, in English as well as other languages. The workshop will solicit both full papers and short papers for either oral or poster presentation. We will solicit papers that incorporate NLP methods, including, but not limited to: automated scoring of open-ended textual and spoken responses; game-based instruction and assessment; educational data mining; intelligent tutoring; peer review; grammatical error detection and correction; learner cognition; spoken dialog; multimodal applications; tools for teachers and test developers; and use of corpora. We will solicit papers that incorporate NLP methods, including, but not limited to:

  • automated scoring of open-ended textual and spoken responses;
  • automated scoring/evaluation for written student responses (across multiple genres);
  • game-based instruction and assessment;
  • educational data mining;
  • intelligent tutoring;
  • collaborative learning environments;
  • peer review;
  • grammatical error detection and correction;
  • learner cognition;
  • spoken dialog;
  • multimodal applications;
  • annotation standards and schemas;
  • tools and applications for classroom teachers, learners and/or test developers; and
  • use of corpora in educational tools.

Workshop Program

Shared Tasks

The workshop will host two shared tasks: a shared task on Automated Prediction of Item Difficulty and Item Response Time, starting on January 15, 2024, and a shared Task on Multilingual Lexical Simplification Pipeline, starting on February 16, 2024. For more information and latest updates, please refer to the shared task websites.

Important Dates

All deadlines are 11:59pm UTC-12 (anywhere on earth).

Event Date
Submission Deadline March 10, 2024
Notification of Acceptance April 14, 2024
Camera-ready Papers Due April 24, 2024
Pre-recorded Videos Due May 1, 2024
Workshop June 20 or 21, 2024

Submission Information

To streamline the submission process, we rely on the ACL submission guidelines and the START conference system, accessible at https://softconf.com/naacl2024/BEA2024. All submissions undergo review by the program committee.

Long, Short, and Demo Papers
Authors can choose to submit long papers (up to eight (8) pages) or short papers (up to four (4) pages), alongside unlimited references. After peer review, all accepted papers will be allotted an additional page of content (up to nine for long papers, five for short papers), allowing authors to address reviewer comments. Authors are strongly urged to present a live demonstration for papers that elaborate on systems. If opting for this, authors should choose either “long paper + demo” or “short paper + demo” under the “Submission Category” on the submission page.
LaTeX and Word Templates
Authors must ensure their paper submissions adhere to the general paper formatting guidelines for “*ACL” conferences, found here, and use the official ACL style templates, downloadable here. Do not modify these style files or use templates intended for other conferences. Submissions failing to meet required styles, including paper size, margin width, and font size restrictions, will be rejected without review.
Authors are required to discuss the limitations of their work in a dedicated section titled “Limitations”. This section should be included at the end of the paper, before the references, and it will not count toward the page limit. This includes both, long and short papers. Note, prior to the December 2023 cycle, this was optional.
Ethics Policy
Authors are required to honour the ethical code set out in the ACL Code of Ethics. The consideration of the ethical impact of our research, use of data, and potential applications of our work has always been an important consideration, and as artificial intelligence is becoming more mainstream, these issues are increasingly pertinent. We ask that all authors read the code, and ensure that their work is conformant to this code. Authors are encouraged to devote a section of their paper to concerns about the ethical impact of the work and to a discussion of broader impacts of the work, which will be taken into account in the review process. This discussion may extend into a 5th page (short papers) or 9th page (long papers).
Given the blind review process, it is essential to ensure that papers remain anonymous. Authors should avoid self-references that disclose their identity (e.g., “We previously showed (Smith, 1991)”), opting instead for citations like “Smith previously showed (Smith, 1991)”.
Conflicts of Interest
Authors are required to mark potential reviewers who have co-authored the paper, belong to the same research group or institution, or have had prior exposure to the paper, ensuring transparency in the review process.
Double Submissions
We adhere to the official ACL double-submission policy. If papers are submitted to both BEA and another conference or workshop, authors must specify the other event on the title page (as a footnote on the abstract). Additionally, the title page should state that if the paper is accepted for presentation at BEA, it will be withdrawn from other conferences and workshops.
Previously published papers will not be accepted.


Sponsoring Opportunities
We are extremely grateful to our sponsors for the past workshops: in the recent years, we have been supported by Duolingo, Grammarly, NBME, iLexIR, Educational Testing Service, and Newsela. This year, we want to continue helping students to attend the workshop, including the accommodation of the student post-workshop dinner (in case the workshop runs offline) and offering student grants covering the BEA registration fees. We are hoping to identify sponsors who might be willing to contribute $100 (Bronze), $250 (Silver) or $500 (Gold sponsorship) 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 the BEA, please send us an email.

Organizing Committee

Program Committee

Tazin Afrin (Educational Testing Service); Erfan Al-Hossami (UNC Charlotte); Desislava Aleksandrova (CBC/Radio-Canada); Giora Alexandron (Weizmann Institute of Science); David Alfter (University of Gothenburg); Jatin Ambasana (Unitedworld School of Computational Intelligence); Alejandro Andrade (Pearson); Nischal Ashok Kumar (University of Massachusetts Amherst); Berk Atil (Penn State University); Shiva Baghel (Data Scientist); Rabin Banjade (University of Memphis); Michael Gringo Angelo Bayona (Trinity College Dublin); Lee Becker (Pearson); Lisa Beinborn (VU Amsterdam); Luca Benedetto (University of Cambridge); Jeanette Bewersdorff (FernUniversität in Hagen); Abhidip Bhattacharyya (CICS UMass); Serge Bibauw (UCLouvain); Ted Briscoe (MBZUAI); Jie Cao (University of Colorado Boulder); Dumitru-Clementin Cercel (University POLITEHNICA of Bucharest); Jeevan Chapagain (University of Memphis); Mei-Hua Chen (Department of Foreign Languages and Literature, Tunghai University); Mark Core (University of Southern California); Steven Coyne (Tohoku University); Sam Davidson (UC Davis); Orphee De Clercq (LT3, Ghent University); Kordula De Kuthy (University of Tübingen); Jasper Degraeuwe (Ghent University); Yo Ehara (Tokyo Gakugei University); Yang Deng (Singapore); Chris Develder (Ghent University - imec, Belgium); Yuning Ding (FernUniversität in Hagen); Rahul Divekar (Bentley University); George Dueñas (Universidad Pedagogica Nacional); Mariano Felice (British Council); Nigel Fernandez (University of Massachusetts Amherst); Michael Flor (Educational Testing Service); Jennifer Frey (Institute for Applied Linguistics, Eurac Research); Kotaro Funakoshi (Tokyo Institute of Technology); Thomas Gaillat (Université Rennes 2); Diana Galvan-Sosa (Tohoku University); Ashwinkumar Ganesan (UMBC, Amazon); Rujun Gao (Texas A&M University); Ritik Garg (IIITD); Christian Gold (FernUniversität in Hagen); Sebastian Gombert (DIPF, Leibniz Institute for Research and Information in Education); Cyril Goutte (National Research Council Canada); Abigail Gurin Schleifer (The Weizmann Institute of Science); Handoko Handoko (Universitas Andalas); Ching Nam Hang (Department of Computer Science, City University of Hong Kong); Jiangang Hao (Educational Testing Service); Nicolas Hernandez (Nantes University - LS2N); Heiko Holz (Ludwigsburg University of Education); Chieh-Yang Huang (Penn State University); Chung-Chi Huang (Frostburg State University); Anna Huelsing (Universität Hildesheim); Joseph Marvin Imperial (University of Bath, National University); Radu Tudor Ionescu (University of Bucharest); Qinjin Jia (North Carolina State University); Helen Jin (University of Pennsylvania); Ioana Jivet (Goethe University Frankfurt); Léane Jourdan (University of Nantes); Anisia Katinskaia (University of Helsinki); Elma Kerz (RWTH Aachen Univeristy); Fazel Keshtkar (St. John’s University, NY); Mamoru Komachi (Hitotsubashi University); Roland Kuhn (National Research Council of Canada (NRC)); Alexander Kwako (University of California, Los Angeles); Kristopher Kyle (University of Oregon); Antonio Laverghetta Jr. (University of South Florida); Seolhwa Lee (Technical University of Darmstadt); Arun Balajiee Lekshmi Narayanan (University of Pittsburgh); Yudong Liu (Western Washington University); Zhexiong Liu (University of Pittsburgh); Julian Lohmann (Christian-Albrechts-Universität zu Kiel); Anastassia Loukina (Grammarly Inc.); Jiaying Lu (Emory University); Crisron Rudolf Lucas (UCD); Jakub Macina (ETH Zurich); Nitin Madnani (ETS); Arianna Masciolini (Språkbanken Text, Department of Swedish, Multilingualism, Language Technology, University of Gothenburg); Sandeep Mathias (Presidency University, Bangalore); Hunter McNichols (University of Massachusetts Amherst); Amit Kumar Mishra (Amity University Madhya Pradesh); Masato Mita (CyberAgent); Phoebe Mulcaire (Duolingo); Laura Musto (Facultad de Información y Comunicación, Universidad de la República); Farah Nadeem (The World Bank); Sungjin Nam (ACT, Inc); Diane Napolitano (Associated Press); Arun Balajiee Lekshmi Narayanan (University of Pittsburgh); Tanya Nazaretsky (EPFL); Kamel Nebhi (Education First); Hwee Tou Ng (National University of Singapore); Huy Nguyen (Amazon); Gebregziabihier Nigusie (Mizan-Tepi University); Christina Niklaus (University of St.Gallen); S Jaya Nirmala (NIT Trichy India); Eda Okur (Intel Labs); Kostiantyn Omelianchuk (Grammarly); Amin Omidvar (York University); Ulrike Pado (Hochschule für Technik Stuttgart); Chanjun Park (Upstage); Udita Patel (Amazon); Long Qin (Alibaba Cloud); Mengyang Qiu (University at Buffalo); Martí Quixal (University of Tübingen); Manav Rathod (Glean); Hanumant Redkar (Goa University); Robert Reynolds (Brigham Young University); Frankie Robertson (University of Jyväskylä); Aiala Rosá (Universidad de la República); Alla Rozovskaya (City University of New York); Josef Ruppenhofer (Fernuniversität in Hagen); Omer Salem; Nicy Scaria (Indian Institute of Science); Nils-Jonathan Schaller (Christian-Albrechts-Universität zu Kiel); Gyu-Ho Shin (University of Illinois Chicago); Mayank Soni (ADAPT Center, Trinity College Dublin); Katherine Stasaski (Salesforce AI Research); Helmer Strik (Radboud University Nijmegen); Hakyung Sung (University of Oregon); Abhijit Suresh (Reddit Inc.); Chee Wei Tan (Nanyang Technological University); Zhongwei Teng (Duolingo); Xiaoyi Tian (University of Florida); Sowmya Vajjala (National Research Council, Canada); Giulia Venturi (Institute for Computational Linguistics “A. Zampolli”); Anthony Verardi (Duolingo English Test); Elena Volodina (University of Gothenburg, Sweden); Taro Watanabe (Nara Institute of Science and Technology); Michael White (The Ohio State University); Alistair Willis (The Open University, UK); Man Fai Wong (City University of Hong Kong); Simon Woodhead (Eedi); Changrong Xiao (Tsinghua University); Roman Yangarber (University of Helsinki); Su-Youn Yoon (EduLab); Marcos Zampieri (George Mason University); Fabian Zehner (DIPF, Leibniz Institute for Research and Information in Education); Torsten Zesch (FernUniversität in Hagen); Jing Zhang (Emory University); Yiyun Zhou (NBME); Jessica Zipf (University of Konstanz); Michael Zock (CNRS, (LIF) University of Aix-Marseille); Bowei Zou (Institute for Infocomm Research (I2R), A*STAR, Singapore).