BEA 2018 - 13th Workshop on Innovative Use of NLP for Building Educational Applications

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 domain knowledge, including writing, speaking, reading, science, and mathematics, and the related intra- (e.g., self-confidence) and inter-personal (e.g., peer collaboration) domains that support achievement in the learning domains. 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, higher education, and adult learning (in academic and workplace settings) fosters a strong interest in technologies that yield user log data that can be leveraged for analytics that support proficiency measures for complex constructs across learning domains. For writing, there is a focus on 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, for instance, for workplace interviews and simulated teaching environments. The explosive growth of mobile applications for game-based and simulation applications for instruction and assessment is another place where NLP has begun to play a large role, especially in language learning.
NLP for 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. Learning-AT-Scale is a relatively new venue for NLP research in education. MOOCs now incorporate AWE systems to manage several thousand assignments that may be received during a single MOOC course. MOOCs for Refugees have more recently popped up 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 last four years – including three shared tasks on grammatical error detection and correction alone. NLP/Education shared tasks, typically in the area of grammar-error detection, have seen new areas of research, such as the “Automated Evaluation of Scientific Writing” at BEA11 and Native Language Identification at BEA12. All of these competitions increased the visibility of, and interest in, our field. In conjunction with the International Joint Conference on Natural Language Processing (ACL-IJCNLP) 2015, the Natural Language Processing Techniques for Educational Applications (NLP-TEA) workshop had a shared task in Chinese error diagnosis, and NLP-TEA had additional shared tasks at the 2016, and a fourth workshop in 2017 co-located with IJCNLP.
The 13th 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 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; educational data mining; 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:
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 (such as, spelling and word usage)
Argumentation, discourse, sentiment, stylistic analysis, & non-literal language
Plagiarism detection
Detection of features related to interest, motivation, and values in writing tasks
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
Knowledge representation in learning systems
Concept visualization in learning systems
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
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