WORKSHOP DESCRIPTION

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The BEA Workshop is a leading venue for NLP innovation for educational applications. It is one of the largest one-day workshops in the ACL community. The workshop’s continuous growth illustrates an alignment between societal need and technology advances. NLP capabilities now support an array of learning domains, including writing, speaking, reading, science, and mathematics. Within these domains, 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 instructional contexts (including Massive Open Online Courses (MOOCs), and K-12 settings). Commercially-deployed plagiarism detection in K-12 and higher education settings is also prevalent. The current educational and assessment landscape in K-12 and higher education fosters a strong interest in technologies that yield analytics to support proficiency measures for complex constructs across learning domains. For writing, there is a focus innovation that supports 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. The explosive growth of mobile applications for game-based and simulation applications for instruction and assessment is another place where NLP can play a large role. 

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The use of NLP in educational applications has gained visibility outside of the NLP community. First, the Hewlett Foundation reached out to 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. MOOCs are now also beginning to incorporate AWE systems to manage the thousands of assignments that may be received during a single MOOC course. Learning @ Scale is a relatively new venue for NLP research in education. Another breakthrough for educational applications within the CL community is the presence of a number of shared-task competitions over the last four years – including three shared tasks on grammatical error correction alone. In 2014 alone, there were four shared tasks in NLP/Education related areas. Most recently, the 2015 ACL-IJCNLP Workshop on Natural Language Processing Techniques for Educational Applications workshop had a shared task in Chinese error diagnosis. All of these competitions increased the visibility of, and interest in, our field. 

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The workshop will have oral presentation sessions and a large poster session in order to maximize the amount of original work presented. This year, we are planning an invited Industry Panel comprised of representatives of companies that work in the NLP and Education space. We expect that the workshop will continue to expose the NLP community to technologies that identify novel opportunities for the use of NLP in education in English, and languages other than English. 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; intelligent tutoring; peer review, grammatical error detection; learner cognition; spoken dialog; multimodal applications; tools for teachers and test developers; and use of corpora. Research that incorporates NLP methods for use with mobile and game-based platforms will be of special interest. Specific topics include:

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• Automated scoring/evaluation for written student responses

  • Content analysis for scoring/assessment 

  • Analysis of the structure of argumentation

  • Grammatical error detection and correction 

  • Discourse and stylistic analysis 

  • Plagiarism detection 

  • Machine translation for assessment, instruction and curriculum development 

  • Detection of non-literal language (e.g., metaphor)

  • Sentiment analysis

  • Non-traditional genres (beyond essay scoring)

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• Intelligent Tutoring (IT) and Game-based assessment that incorporates NLP

  • Dialogue systems in education 

  • Hypothesis formation and testing 

  • Multi-modal communication between students and computers 

  • Generation of tutorial responses 

  • Knowledge representation in learning systems 

  • Concept visualization in learning systems

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• 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

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• Use of corpora in educational tools

  • Data mining of learner and other corpora for tool building 

  • Annotation standards and schemas / annotator agreement

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• 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 

  • Processing of and access to lecture materials across topics and genres 

  • Adaptation of instructional text to individual learners' grade levels 

  • Tools for text-based curriculum development 

  • E-learning tools for personalized course content 

  • Language-based educational games

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• Descriptions and proposals for shared tasks 

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• Retrospective or survey papers on a particular NLP/Edu topic or field 

• Vision papers about ideas discussing how the field should develop