**DEADLINE EXTENDED: Monday, April 29, 11:59pm EST**
The 14th Workshop on Innovative Use of
NLP for Building Educational Applications (BEA14)
Florence, Italy; August 2, 2019
(co-located with ACL)
https://sig-edu.org/bea/current
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 80 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
144 members.
The workshop’s continuing growth highlights the alignment between
societal needs and technological advances. 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. In the
writing and speech domains, automated writing evaluation (AWE) and
speech scoring applications, respectively, are commercially deployed in
high-stakes assessment and in instructional contexts (e.g., Massive Open
Online Courses (MOOCs) and K-12 classrooms). Commercially-deployed
plagiarism detection is also commonly used in both K-12 and higher
education settings. For writing, the focus is on innovations that
support writing tasks requiring source use, argumentative discourse, and
factual content accuracy. For speech, there is an interest in advancing
automated scoring to include the evaluation of discourse and content
features in responses to spoken assessments. General advances in speech
technology have promoted a renewed interest in spoken dialog and
multimodal systems for instruction and assessment, for instance, for
workplace interviews and simulated teaching environments. The explosive
growth of mobile applications for game-based and simulation-based
applications is another area where NLP has begun to play a large role,
especially for language learning.
NLP for educational applications has gained visibility outside of the
NLP community. First, the Hewlett Foundation reached out to the public
and private sectors and sponsored two competitions: one for automated
essay scoring, and the other for scoring of short response items. The
motivation driving these competitions was to engage the larger
scientific community in this enterprise. Learning @ Scale is a
relatively new venue for NLP research in education. MOOCs now
incorporate AWE systems to manage several thousandassignments that may
be received during a single MOOC course. MOOCs for Refugees have more
recently emerged in response to the current social situations. Courses
include language learning, and we can imagine that AWE and other NLP
capabilities could support coursework. Another breakthrough for
educational applications within the CL community is the presence of a
number of shared-task competitions over the past several years –
including three shared tasks on grammatical error detection and
correction. NLP/Education shared tasks have seen new areas of research,
such as the Automated Evaluation of Scientific Writing at BEA 11, Native
Language Identification at BEA 12, Second Language Acquisition Modelling
at BEA 13, and Complex Word Identification at BEA 13. These
competitions increased the visibility of, and interest in, our field.
The 14th BEA workshop will have oral presentation sessions and a large
poster session in order to maximize the amount of original work
presented. We expect that the workshop will continue to highlight novel
technologies and opportunities 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. Specific topics
include:
Automated scoring/evaluation for written student responses (across
multiple genres)
● Content analysis for scoring/assessment
● Detection and correction of grammatical and other types of errors
● Argumentation, discourse, sentiment, stylistic analysis, &
non-literal language
Intelligent Tutoring (IT), Collaborative Learning Environments
● Educational Data Mining: Collection of user log data from
educational applications
● Game-based learning
● Multimodal communication (including dialog systems) between
students and computers
Learner cognition
● Assessment of learners' language and cognitive skill levels
● Systems that detect and adapt to learners' cognitive or emotional
states
● Tools for learners with special needs
Use of corpora in educational tools
● Data mining of learner and other corpora for tool building
● Annotation standards and schemas / annotator agreement
Tools and applications for classroom teachers and/or test developers
● NLP tools for second and foreign language learners
● Semantic-based access to instructional materials to identify
appropriate texts
● Tools that automatically generate test questions
SUBMISSION INFORMATION
We will be using the ACL Submission Guidelines for the BEA14 Workshop
this year. Long papers may consist of up to eight (8) pages of content,
plus unlimited references; final versions of long papers will be given
one additional page of content (up to 9 pages) so that reviewers'
comments can be taken into account. Short papers may consist of up to
four (4) pages of content, plus unlimited references. Upon acceptance,
short papers will be given five (5) content pages in the proceedings.
Authors are encouraged to use this additional page to address reviewers'
comments in their final versions.
Papers which describe systems are also invited to give a demo of their
system. If you would like to present a demo in addition to presenting
the paper, please make sure to select either "full paper + demo" or
"short paper + demo" under "Submission Category" in the START submission
page.
Previously published papers cannot be accepted. The submissions will be
reviewed by the program committee. As reviewing will be blind, please
ensure that papers are anonymous. Self-references that reveal the
author's identity, e.g., "We previously showed (Smith, 1991) ...",
should be avoided. Instead, use citations such as "Smith previously
showed (Smith, 1991) ...".
We have also included conflict of interest in the submission form. You
should mark all potential reviewers who have been authors on the paper,
are from the same research group or institution, or who have seen
versions of this paper or discussed it with you.
We will be using the START conference system to manage submissions:
https://www.softconf.com/acl2019/bea/
IMPORTANT DATES
EXTENDED Submission Deadline: Monday, April 29, 2019, 11:59pm EST
Notification of Acceptance: Friday, May 24, 2019
Camera-ready Papers Due: Monday, June 3, 2019
Workshop: Friday, August 2, 2019
ORGANIZING COMMITTEE
● Helen Yannakoudakis, University of Cambridge (primary contact)
● Ekaterina Kochmar, University of Cambridge
● Claudia Leacock, Grammarly
● Nitin Madnani, Educational Testing Service
● Ildikó Pilán, Develop Diverse
● Torsten Zesch, University of Duisburg-Essen
Workshop contact email address: bea.nlp.works...@gmail.com
PROGRAM COMMITTEE
● Tazin Afrin, University of Pittsburgh
● David Alfter, University of Gothenburg
● Dimitrios Alikaniotis, Grammarly
● Rajendra Banjade, Audible Inc. (an Amazon company)
● Timo Baumann, Carnegie Mellon University
● Lee Becker, Pearson
● Beata Beigman Klebanov, ETS
● Kay Berkling, Cooperation State university Karlsruhe Germany
● Suma Bhat, University of Illinois at Urbana-Champaign
● Sameer Bhatnagar, Polytechnique Montreal
● Joachim Bingel, University of Copenhagen
● Karim Bouzoubaa, Mohammed V University in Rabat
● Chris Brew, Facebook
● Ted Briscoe, University of Cambridge
● Julian Brooke, University of British Columbia
● Dominique Brunato, Institute for Computational Linguistics,
ILC-CNR, Pisa, Italy
● Christopher Bryant, University of Cambridge
● Paula Buttery, University of Cambridge
● Andrew Caines, University of Cambridge
● Mei-Hua Chen, Department of Foreign Languages and Literature,
Tunghai University
● Martin Chodorow, ETS & City University of New York
● Shamil Chollampatt, National University of Singapore
● Mark Core, University of Southern California
● Vidas Daudaravicius, UAB VTEX
● Kordula De Kuthy, University of Tübingen
● Carrie Demmans Epp, University of Alberta
● Yo Ehara, Faculty of Informatics, Shizuoka Institute of Science
and Technology
● Keelan Evanini, Educational Testing Service
● Mariano Felice, University of Cambridge
● Michael Flor, Educational Testing Service
● Thomas François, Université catholique de Louvain
● Michael Gamon, Microsoft Research
● Dipesh Gautam, The University of Memphis
● Sian Gooding, University of Cambridge
● Jonathan Gordon, Vassar College
● Cyril Goutte, National Research Council Canada
● Iryna Gurevych, UKP Lab, TU Darmstadt
● Na-Rae Han, University of Pittsburgh
● Jiangang Hao, Educational Testing Service
● Homa Hashemi, Microsoft
● Trude Heift, Simon Fraser University
● Derrick Higgins, American Family Insurance
● Heiko Holz, LEAD Graduate School & Research Network at the
University of Tuebingen
● Andrea Horbach, University Duisburg-Essen
● Chung-Chi Huang, Frostburg State University
● Yi-Ting Huang, Academia Sinica
● Radu Tudor Ionescu, University of Bucharest
● Lifeng Jin, The Ohio State University
● Pamela Jordan, University of Pittsburgh
● Taraka Kasicheyanula, University of Oslo
● Elma Kerz, RWTH Aachen
● Fazel Keshtkar, St. John's University
● Mamoru Komachi, Tokyo Metropolitan University
● Lun-Wei Ku, Academia Sinica
● Ji-Ung Lee, UKP Lab, Technische Universität Darmstadt
● John Lee, City University of Hong Kong
● Lung-Hao Lee, National Central University
● Ben Leong, Educational Testing Service
● James Lester, North Carolina State University
● Chen Liang, Facebook
● Diane Litman, University of pittsburgh
● Yang Liu, Laix
● Peter Ljunglöf, University of Gothenburg
● Anastassia Loukina, ETS
● Xiaofei Lu, Pennsylvania State University
● Luca Lugini, University of Pittsburgh
● Nabin Maharjan, University of Memphis
● Jean Maillard, University of Cambridge
● Shervin Malmasi, Harvard Medical School
● Montse Maritxalar, University of the Basque Country
● Ditty Mathew, IIT Madras
● Julie Medero, Harvey Mudd College
● Beata Megyesi, Uppsala University
● Detmar Meurers, Universität Tübingen
● Elham Mohammadi, CLaC Laboratory, Concordia University
● Maria Moritz, University of Goettingen
● William Murray, Pearson
● Courtney Napoles, Grammarly
● Diane Napolitano, Educational Testing Service
● Hwee Tou Ng, National University of Singapore
● Huy Nguyen, LingoChamp
● Rodney Nielsen, University of North Texas
● Nobal Niraula, Boeing Research and Technology
● Yoo Rhee Oh, Electronics and Telecommunications Research
Institute (ETRI)
● Constantin Orasan, University of Wolverhampton
● Ulrike Pado, HFT Stuttgart
● Alexis Palmer, University of North Texas
● Martí Quixal, University of Tübingen
● Zahra Rahimi, University of Pittsburgh
● Lakshmi Ramachandran, Amazon Search
● Hanumant Redkar, Indian Institute of Technology Bombay
● Marek Rei, University of Cambridge
● Robert Reynolds, Brigham Young University
● Brian Riordan, ETS
● Kat Robb, University of Leeds
● Andrew Rosenberg, Google
● Mark Rosenstein, Pearson
● Alla Rozovskaya, City University of New York
● C. Anton Rytting, University of Maryland
● Keisuke Sakaguchi, Allen Institute for Artificial Intelligence
● Allen Schmaltz, Harvard University
● Mat Schulze, San Diego State University
● Burr Settles, Duolingo
● Serge Sharoff, University of Leeds
● Swapna Somasundaran, ETS
● Richard Sproat, Google
● Helmer Strik, Centre for Language and Speech Technology (CLST),
Centre for Language Studies (CLS), Radboud University Nijmegen
● Jan Švec, NTIS, University of West Bohemia
● Anaïs Tack, UCLouvain & KU Leuven
● Yuen-Hsien Tseng, National Taiwan Normal University
● Giulia Venturi, Institute for Computational Linguistics "A.
Zampolli", Italy
● Aline Villavicencio, Federal University of Rio Grande do Sul
(Brazil) and University of Essex (UK)
● Carl Vogel, Trinity College Dublin
● Elena Volodina, University of Gothenburg
● Shuting Wang, Facebook Inc
● Michael White, The Ohio State University
● Michael Wojatzki, LTL, University of Duisburg-Essen
● Magdalena Wolska, Eberhard Karls Universität Tübingen
● Huichao Xue, LinkedIn
● Victoria Yaneva, National Board of Medical Examiners / University
of Wolverhampton
● Zheng Yuan, University of Cambridge
● Marcos Zampieri, University of Wolverhampton (UK)
● Klaus Zechner, ETS
● Fan Zhang, Google
● Haoran Zhang, University of Pittsburgh
● Ramon Ziai, University of Tübingen
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