| { |
| "paper_id": "2020", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T01:10:04.108135Z" |
| }, |
| "title": "", |
| "authors": [ |
| { |
| "first": "Noureddine", |
| "middle": [], |
| "last": "Elouazizi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Homa", |
| "middle": [], |
| "last": "Hashemi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Trude", |
| "middle": [], |
| "last": "Heift", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yi-Ting", |
| "middle": [], |
| "last": "Huang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Academia", |
| "middle": [], |
| "last": "Sinica", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Lun-Wei", |
| "middle": [], |
| "last": "Ku", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kristopher", |
| "middle": [], |
| "last": "Kyle", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Chen", |
| "middle": [], |
| "last": "Liang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Diane", |
| "middle": [], |
| "last": "Litman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Courtney", |
| "middle": [], |
| "last": "Napoles", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Diane", |
| "middle": [], |
| "last": "Grammarly", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Refinitiv", |
| "middle": [], |
| "last": "Napolitano", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tou", |
| "middle": [], |
| "last": "Hwee", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Ng", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Huy", |
| "middle": [], |
| "last": "Nguyen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Rodney", |
| "middle": [], |
| "last": "Nielsen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marek", |
| "middle": [], |
| "last": "Rei", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Robert", |
| "middle": [], |
| "last": "Reynolds", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Alla", |
| "middle": [], |
| "last": "Rozovskaya", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Piper", |
| "middle": [], |
| "last": "Vasicek", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marcos", |
| "middle": [], |
| "last": "Zampieri", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "", |
| "pdf_parse": { |
| "paper_id": "2020", |
| "_pdf_hash": "", |
| "abstract": [], |
| "body_text": [ |
| { |
| "text": "When we sent out our call for papers this year, we never imagined that the Workshop on Innovative Use of NLP for Building Educational Applications would be held virtually. While the circumstances are far from ideal, this will be an interesting experiment. We are pleased to host a set of innovative papers -even if virtually! Our papers this year include topics related to automated writing and speech and content evaluation, writing analytics, text revision analysis, building dialog resources, tracking writing proficient, neural models for writing evaluation tasks, and educational applications for languages other than English.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": null |
| }, |
| { |
| "text": "This year we received a total of 49 submissions and accepted 8 papers as oral presentations and 13 as poster presentations, for an overall acceptance rate of 43 percent. Each paper was reviewed by three members of the Program Committee who were believed to be most appropriate for each paper. We continue to have a strong policy to deal with conflicts of interest. First, we continue to make a concerted effort to resolve conflicts of interest -specifically, we do not assign papers to a reviewer if the paper has an author from their institution. Second, organizing committee members recuse themselves from discussions about papers if there is a conflict of interest.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": null |
| }, |
| { |
| "text": "Papers are accepted on the basis of several factors, including the relevance to a core educational problem space, the novelty of the approach or domain, and the strength of the research. The accepted papers were highly diverse -an indicator of the growing variety of foci in this field. We continue to believe that the workshop framework designed to introduce work in progress and new ideas is important and we hope that the breadth and variety of research accepted for this workshop is represented.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": null |
| }, |
| { |
| "text": "The BEA15 workshop has presentations on automated writing evaluation, readability, dialog, speech and grammatical error correction, annotation and resources, and educational research that serves languages other than English.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": null |
| }, |
| { |
| "text": "Gonz\u00e1lez-L\u00f3pez et al's Assisting Undergraduate Students in Writing Spanish Methodology Sections discusses a method that provides feedback to students with regard to how they have improved the methodology section of a paper; Ghosh et al's An Exploratory Study of Argumentative Writing by Young Students: A Transformer-based Approach uses a transformer-based architecture (e.g., BERT) fine-tuned on a large corpus of critique essays from the college task to conduct a computational exploration of argument critique writing by young students; Afrin et al's Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing introduces an annotation scheme to capture the nature of sentence-level revisions of evidence use and reasoning and apply it to 5th-and 6th-grade students' argumentative essays. They show that reliable manual annotation can be achieved and that revision annotations correlate with a holistic assessment of essay improvement in line with the feedback provided. They explore the feasibility of automatically classifying revisions according to their scheme; Wang et al's Automated Scoring of Clinical Expressive Language Evaluation Tasks present a dataset consisting of non-clinically elicited responses for three related sentence formulation tasks, and propose an approach for automatically evaluating their appropriateness. They use neural machine translation to generate correctincorrect sentence pairs in order to create synthetic data to increase the amount and diversity of training data for their scoring model and show how transfer learning improves scoring accuracy,", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Automated Writing Evaluation", |
| "sec_num": null |
| }, |
| { |
| "text": "Explanations presents an empirical investigation of feature-based models, recurrent neural network models, and pre-trained transformer models on scoring content in real-world formative assessment data. They demonstrate that recent neural methods can rival or exceed the performance of featurebased methods and provide evidence that different classes of neural models take advantage of different iii learning cues, and that pre-trained transformer models may be more robust to spurious, dataset-specific learning cues, better reflecting scoring rubrics.; Cahill et al's Context-based Automated Scoring of Complex Mathematical Responses proposes a method for automatically scoring responses that contain both text and algebraic expressions. Their method not only achieves high agreement with human raters, but also links explicitly to the scoring rubric; Ehara's Interpreting Neural CWI Classifiers' Weights as Vocabulary Size studies Complex Word Identification (CWI) -a task for the identification of words that are challenging for second-language learners to read. The paper analyzes neural CWI classifiers and shows that some of their parameters can be interpreted as vocabulary size.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Automated Content Evaluation & Vocabulary Analysis Riordan et al's An Empirical Investigation of Neural Methods for Content Scoring of Science", |
| "sec_num": null |
| }, |
| { |
| "text": "Davidson et al's Tracking the Evolution of Written Language Competence in L2 Spanish Learners presents an NLP-based approach for tracking the evolution of written language competence in L2 Spanish learners using a wide range of linguistic features automatically extracted from students' written productions. The authors explore the connection between the most predictive features and the teaching curriculum, finding that their set of linguistic features often reflect the explicit instructions that students receive during each course; Hellman et al's Multiple Instance Learning for Content Feedback Localization without Annotation considers automated essay scoring as a Multiple Instance Learning (MIL) task. The authors show that such models can both predict content scores and localize content by leveraging their sentence-level score predictions; Kerz et al's Becoming Linguistically Mature: Modeling English and German Children's Writing Development Across School Grades employs a novel approach to advancing our understanding of the development of writing in English and German children across school grades using classification tasks. Their experiments show that RNN classifiers trained on complexity contours achieve higher classification accuracy than one trained on text-average complexity scores; Mayfield and Black's Should You Fine-Tune BERT for Automated Essay Scoring? investigates whether, in automated essay scoring research, transformer-based models are an appropriate technological choice. The authors conclude with a review of promising areas for research on student essays where the unique characteristics of transformers may provide benefits over classical methods to justify the costs; Mathias and Bhattacharyya's Can Neural Networks Automatically Score Essay Traits? shows how a deep-learning based system can outperform both feature-based machine learning systems and string kernel-based systems when scoring essay traits.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Writing Analytics and Feedback", |
| "sec_num": null |
| }, |
| { |
| "text": "Deutsch et al's Linguistic Features for Readability Assessment combines linguistically-motivated machine learning and deep learning methods to improve overall readability model performance; Xue et al's Predicting the Difficulty and Response Time of Multiple Choice Questions Using Transfer Learning investigates whether transfer learning can improve the prediction of the difficulty and response time parameters for 18,000 multiple-choice questions from a high-stakes medical exam. The results indicate that, for their sample, transfer learning can improve the prediction of item difficulty; Gao et al's Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners considers the problem of automatically suggesting distractors for multiple-choice cloze questions designed for second-language learners. Based on their analyses, they train models to automatically select distractors, and measure the importance of model components quantitatively.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Readability & Item Difficulty/Selection", |
| "sec_num": null |
| }, |
| { |
| "text": "Loukina et al's Using PRMSE to Evaluate Automated Scoring Systems in the Presence of Label Noise discusses the effect that noisy labels have on system evaluation and propose the use of a new educational measurement metric (PRMSE) to help address this issue; Raina et al's Complementary Systems for Off-topic Spoken Response Detection examines one form of spoken language assessment; whether the response from the candidate is relevant to the prompt provided. The work focuses on the scenario when the prompt, and associated responses have not been seen in the training data, enabling the system to be applied to new test scripts without the need to collect data or retrain the model; Maxwell-Smith et al's Applications of Natural Language Processing in Bilingual Language Teaching: An Indonesian-English Case Study discusses methodological considerations for using automated speech recognition to build a corpus of teacher speech in an Indonesian language classroom; Stasaki et al's Construction of a Large Open Access Dialogue Dataset for Tutoring proposes a novel asynchronous method for collecting tutoring dialogue via crowdworkers that is both amenable to the needs of deep learning algorithms and reflective of pedagogical concerns. The CIMA dataset produced from this work is publicly available.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Evaluation, Resources, Speech & Dialog", |
| "sec_num": null |
| }, |
| { |
| "text": "Omilianchuk et al's GECToR -Grammatical Error Correction: Tag, Not Rewrite presents a simple and efficient GEC sequence tagger using a transformer encoder; White & Rozovskaya's A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction compares techniques for generating synthetic data utilized by the two highest scoring submissions to the restricted and lowresource tracks in the BEA-2019 Shared Task on Grammatical Error Correction.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Grammatical Error Correction", |
| "sec_num": null |
| }, |
| { |
| "text": "We wish to thank everyone who showed interest and submitted a paper, all of the authors for their contributions, the members of the Program Committee for their thoughtful reviews, and everyone who is attending this workshop, virtually! We would especially like to thank our Gold Level sponsor, the National Board of Medical Examiners.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Grammatical Error Correction", |
| "sec_num": null |
| }, |
| { |
| "text": "Finally, our special thanks go to the emergency reviewers who stepped in to provide their expertise and help ensure the highest level of feedback: we acknowledge the help of Beata Beigman Klebanov, Christopher Bryant, Andrew Caines, Mariano Felice, Yoko Futagi, Ananya Ganesh, Anastassia Loukina, and Marek Rei. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Grammatical Error Correction", |
| "sec_num": null |
| } |
| ], |
| "back_matter": [], |
| "bib_entries": { |
| "BIBREF1": { |
| "ref_id": "b1", |
| "title": "Using PRMSE to evaluate automated scoring systems in the presence of label noise Anastassia Loukina", |
| "authors": [ |
| { |
| "first": "Nitin", |
| "middle": [], |
| "last": "Madnani", |
| "suffix": "" |
| }, |
| { |
| "first": "Aoife", |
| "middle": [], |
| "last": "Cahill", |
| "suffix": "" |
| }, |
| { |
| "first": "Lili", |
| "middle": [], |
| "last": "Yao", |
| "suffix": "" |
| }, |
| { |
| "first": "Matthew", |
| "middle": [ |
| "S" |
| ], |
| "last": "Johnson", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Using PRMSE to evaluate automated scoring systems in the presence of label noise Anastassia Loukina, Nitin Madnani, Aoife Cahill, Lili Yao, Matthew S. Johnson, Brian Riordan and", |
| "links": null |
| }, |
| "BIBREF3": { |
| "ref_id": "b3", |
| "title": "Multiple Instance Learning for Content Feedback Localization without Annotation", |
| "authors": [ |
| { |
| "first": "Scott", |
| "middle": [], |
| "last": "Hellman", |
| "suffix": "" |
| }, |
| { |
| "first": "William", |
| "middle": [], |
| "last": "Murray", |
| "suffix": "" |
| }, |
| { |
| "first": "Adam", |
| "middle": [], |
| "last": "Wiemerslage", |
| "suffix": "" |
| }, |
| { |
| "first": "Mark", |
| "middle": [], |
| "last": "Rosenstein", |
| "suffix": "" |
| }, |
| { |
| "first": "Peter", |
| "middle": [], |
| "last": "Foltz", |
| "suffix": "" |
| }, |
| { |
| "first": "Lee", |
| "middle": [], |
| "last": "Becker", |
| "suffix": "" |
| }, |
| { |
| "first": "Marcia", |
| "middle": [], |
| "last": "Derr", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Multiple Instance Learning for Content Feedback Localization without Annotation Scott Hellman, William Murray, Adam Wiemerslage, Mark Rosenstein, Peter Foltz, Lee Becker and Marcia Derr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30", |
| "links": null |
| }, |
| "BIBREF4": { |
| "ref_id": "b4", |
| "title": "CIMA: A Large Open Access Dialogue Dataset for Tutoring Katherine Stasaski", |
| "authors": [ |
| { |
| "first": "Kate", |
| "middle": [], |
| "last": "Knill", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| ". ." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "Complementary Systems for Off-Topic Spoken Response Detection Vatsal Raina, Mark Gales and", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Complementary Systems for Off-Topic Spoken Response Detection Vatsal Raina, Mark Gales and Kate Knill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 CIMA: A Large Open Access Dialogue Dataset for Tutoring Katherine Stasaski, Kimberly Kao and Marti A. Hearst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52", |
| "links": null |
| }, |
| "BIBREF5": { |
| "ref_id": "b5", |
| "title": "Becoming Linguistically Mature: Modeling English and German Children's Writing Development Across School Grades Elma Kerz", |
| "authors": [ |
| { |
| "first": "Yu", |
| "middle": [], |
| "last": "Qiao", |
| "suffix": "" |
| }, |
| { |
| "first": "Daniel", |
| "middle": [], |
| "last": "Wiechmann", |
| "suffix": "" |
| }, |
| { |
| "first": "Marcus", |
| "middle": [], |
| "last": "Str\u00f6bel", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Becoming Linguistically Mature: Modeling English and German Children's Writing Development Across School Grades Elma Kerz, Yu Qiao, Daniel Wiechmann and Marcus Str\u00f6bel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65", |
| "links": null |
| }, |
| "BIBREF6": { |
| "ref_id": "b6", |
| "title": "Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing Tazin Afrin", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing Tazin Afrin, Elaine Lin Wang, Diane Litman, Lindsay Clare Matsumura and Richard Correnti . . 75", |
| "links": null |
| }, |
| "BIBREF7": { |
| "ref_id": "b7", |
| "title": "Can Neural Networks Automatically Score Essay Traits? Sandeep Mathias and", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Can Neural Networks Automatically Score Essay Traits? Sandeep Mathias and Pushpak Bhattacharyya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85", |
| "links": null |
| }, |
| "BIBREF8": { |
| "ref_id": "b8", |
| "title": "Tracking the Evolution of Written Language Competence in L2 Spanish Learners Alessio Miaschi", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Tracking the Evolution of Written Language Competence in L2 Spanish Learners Alessio Miaschi, Sam Davidson, Dominique Brunato, Felice Dell'Orletta, Kenji Sagae, Claudia", |
| "links": null |
| }, |
| "BIBREF10": { |
| "ref_id": "b10", |
| "title": "Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners Lingyu Gao, Kevin Gimpel and", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners Lingyu Gao, Kevin Gimpel and Arnar Jensson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102", |
| "links": null |
| }, |
| "BIBREF11": { |
| "ref_id": "b11", |
| "title": "Assisting Undergraduate Students in Writing Spanish Methodology Sections Samuel Gonz\u00e1lez-L\u00f3pez", |
| "authors": [ |
| { |
| "first": "Steven", |
| "middle": [], |
| "last": "Bethard", |
| "suffix": "" |
| }, |
| { |
| "first": "Aurelio", |
| "middle": [], |
| "last": "Lopez-Lopez", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Assisting Undergraduate Students in Writing Spanish Methodology Sections Samuel Gonz\u00e1lez-L\u00f3pez, Steven Bethard and Aurelio Lopez-Lopez . . . . . . . . . . . . . . . . . . . . . . . . 115", |
| "links": null |
| }, |
| "BIBREF12": { |
| "ref_id": "b12", |
| "title": "Applications of Natural Language Processing in Bilingual Language Teaching: An Indonesian-English Case Study Zara Maxwelll-Smith", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Sim\u00f3n Gonz\u00e1lez", |
| "suffix": "" |
| }, |
| { |
| "first": "Ben", |
| "middle": [], |
| "last": "Ochoa", |
| "suffix": "" |
| }, |
| { |
| "first": "Hanna", |
| "middle": [], |
| "last": "Foley", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". . . . . ." |
| ], |
| "last": "Suominen", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Applications of Natural Language Processing in Bilingual Language Teaching: An Indonesian-English Case Study Zara Maxwelll-Smith, Sim\u00f3n Gonz\u00e1lez Ochoa, Ben Foley and Hanna Suominen . . . . . . . . . . . . . 124", |
| "links": null |
| }, |
| "BIBREF13": { |
| "ref_id": "b13", |
| "title": "An empirical investigation of neural methods for content scoring of science explanations Brian", |
| "authors": [ |
| { |
| "first": "Sarah", |
| "middle": [], |
| "last": "Riordan", |
| "suffix": "" |
| }, |
| { |
| "first": "Allison", |
| "middle": [], |
| "last": "Bichler", |
| "suffix": "" |
| }, |
| { |
| "first": "Jennifer", |
| "middle": [ |
| "King" |
| ], |
| "last": "Bradford", |
| "suffix": "" |
| }, |
| { |
| "first": "Korah", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "Libby", |
| "middle": [], |
| "last": "Wiley", |
| "suffix": "" |
| }, |
| { |
| "first": "Marcia", |
| "middle": [ |
| "C" |
| ], |
| "last": "Gerard", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "Linn", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "An empirical investigation of neural methods for content scoring of science explanations Brian Riordan, Sarah Bichler, Allison Bradford, Jennifer King Chen, Korah Wiley, Libby Gerard and Marcia C. Linn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135", |
| "links": null |
| }, |
| "BIBREF14": { |
| "ref_id": "b14", |
| "title": "An Exploratory Study of Argumentative Writing by Young Students: A transformer-based Approach Debanjan Ghosh, Beata Beigman Klebanov and Yi Song", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "An Exploratory Study of Argumentative Writing by Young Students: A transformer-based Approach Debanjan Ghosh, Beata Beigman Klebanov and Yi Song . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145", |
| "links": null |
| }, |
| "BIBREF15": { |
| "ref_id": "b15", |
| "title": "151 xi GECToR -Grammatical Error Correction: Tag", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Alan", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". ." |
| ], |
| "last": "Black", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "Tune BERT for Automated Essay Scoring? Elijah Mayfield and", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Should You Fine-Tune BERT for Automated Essay Scoring? Elijah Mayfield and Alan W Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 xi GECToR -Grammatical Error Correction: Tag, Not Rewrite Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub and Oleksandr Skurzhanskyi . 163", |
| "links": null |
| }, |
| "BIBREF16": { |
| "ref_id": "b16", |
| "title": "Interpreting Neural CWI Classifiers' Weights as Vocabulary Size Yo Ehara", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Interpreting Neural CWI Classifiers' Weights as Vocabulary Size Yo Ehara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171", |
| "links": null |
| }, |
| "BIBREF17": { |
| "ref_id": "b17", |
| "title": "Automated Scoring of Clinical Expressive Language Evaluation Tasks Yiyi Wang, Emily Prud'hommeaux, Meysam Asgari and Jill Dolata", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Automated Scoring of Clinical Expressive Language Evaluation Tasks Yiyi Wang, Emily Prud'hommeaux, Meysam Asgari and Jill Dolata . . . . . . . . . . . . . . . . . . . . . . . . 177", |
| "links": null |
| }, |
| "BIBREF18": { |
| "ref_id": "b18", |
| "title": "Context-based Automated Scoring of Complex Mathematical Responses Aoife Cahill", |
| "authors": [ |
| { |
| "first": "H", |
| "middle": [], |
| "last": "James", |
| "suffix": "" |
| }, |
| { |
| "first": "Brian", |
| "middle": [], |
| "last": "Fife", |
| "suffix": "" |
| }, |
| { |
| "first": "Avijit", |
| "middle": [], |
| "last": "Riordan", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Vajpayee", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". . . . ." |
| ], |
| "last": "Dmytro Galochkin", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Context-based Automated Scoring of Complex Mathematical Responses Aoife Cahill, James H Fife, Brian Riordan, Avijit Vajpayee and Dmytro Galochkin . . . . . . . . . . . 186", |
| "links": null |
| }, |
| "BIBREF19": { |
| "ref_id": "b19", |
| "title": "Predicting the Difficulty and Response Time of Multiple Choice Questions Using Transfer Learning Kang Xue", |
| "authors": [ |
| { |
| "first": "Victoria", |
| "middle": [], |
| "last": "Yaneva", |
| "suffix": "" |
| }, |
| { |
| "first": "Christopher", |
| "middle": [], |
| "last": "Runyon", |
| "suffix": "" |
| }, |
| { |
| "first": "Peter", |
| "middle": [], |
| "last": "Baldwin", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Predicting the Difficulty and Response Time of Multiple Choice Questions Using Transfer Learning Kang Xue, Victoria Yaneva, Christopher Runyon and Peter Baldwin . . . . . . . . . . . . . . . . . . . . . . . . 193", |
| "links": null |
| }, |
| "BIBREF20": { |
| "ref_id": "b20", |
| "title": "A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction", |
| "authors": [], |
| "year": 2020, |
| "venue": "", |
| "volume": "10", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction Max White and Alla Rozovskaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 xii Conference Program July, 10, 2020 08:30-09:00 Loading in of Oral Presentations 06:00-06:10 Opening Remarks 06:10-07:30 Session 1 07:30-08:00 Break 08:00-09:10 Poster Session 1 09:10-10:10 Break 10:10-11:30 Session 2 11:30-12:00 Break 12:00-13:00 Poster Session 2 13:00-13:10 Closing Remarks xiii", |
| "links": null |
| } |
| }, |
| "ref_entries": {} |
| } |
| } |
