发布求助
文献互助 智能选刊 最新文献

Workshop on Innovative Use of NLP for Building Educational Applications最新文献

筛选
英文 中文
Tracking the Evolution of Written Language Competence in L2 Spanish Learners 追踪二语西班牙语学习者书面语言能力的演变
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.9
Alessio Miaschi, Sam Davidson, D. Brunato, F. Dell’Orletta, K. Sagae, C. H. S. Gutierrez, Giulia Venturi
{"title":"Tracking the Evolution of Written Language Competence in L2 Spanish Learners","authors":"Alessio Miaschi, Sam Davidson, D. Brunato, F. Dell’Orletta, K. Sagae, C. H. S. Gutierrez, Giulia Venturi","doi":"10.18653/v1/2020.bea-1.9","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.9","url":null,"abstract":"In this paper we present 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. Beyond reporting classification results for different scenarios, we explore the connection between the most predictive features and the teaching curriculum, finding that our set of linguistic features often reflect the explicit instructions that students receive during each course.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123318952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An empirical investigation of neural methods for content scoring of science explanations 科学解释内容评分的神经方法实证研究
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.13
Brian Riordan, S. Bichler, Alison Bradford, J. K. Chen, Korah J. Wiley, Libby F. Gerard, M. Linn
{"title":"An empirical investigation of neural methods for content scoring of science explanations","authors":"Brian Riordan, S. Bichler, Alison Bradford, J. K. Chen, Korah J. Wiley, Libby F. Gerard, M. Linn","doi":"10.18653/v1/2020.bea-1.13","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.13","url":null,"abstract":"With the widespread adoption of the Next Generation Science Standards (NGSS), science teachers and online learning environments face the challenge of evaluating students’ integration of different dimensions of science learning. Recent advances in representation learning in natural language processing have proven effective across many natural language processing tasks, but a rigorous evaluation of the relative merits of these methods for scoring complex constructed response formative assessments has not previously been carried out. We present a detailed empirical investigation of feature-based, recurrent neural network, and pre-trained transformer models on scoring content in real-world formative assessment data. We demonstrate that recent neural methods can rival or exceed the performance of feature-based methods. We also provide evidence that different classes of neural models take advantage of different learning cues, and pre-trained transformer models may be more robust to spurious, dataset-specific learning cues, better reflecting scoring rubrics.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116032244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Becoming Linguistically Mature: Modeling English and German Children’s Writing Development Across School Grades 语言上的成熟:跨年级英语和德语儿童写作发展的模型
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.6
Elma Kerz, Y. Qiao, Daniel Wiechmann, Marcus Ströbel
{"title":"Becoming Linguistically Mature: Modeling English and German Children’s Writing Development Across School Grades","authors":"Elma Kerz, Y. Qiao, Daniel Wiechmann, Marcus Ströbel","doi":"10.18653/v1/2020.bea-1.6","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.6","url":null,"abstract":"In this paper we employ a novel approach to advancing our understanding of the development of writing in English and German children across school grades using classification tasks. The data used come from two recently compiled corpora: The English data come from the the GiC corpus (983 school children in second-, sixth-, ninth- and eleventh-grade) and the German data are from the FD-LEX corpus (930 school children in fifth- and ninth-grade). The key to this paper is the combined use of what we refer to as ‘complexity contours’, i.e. series of measurements that capture the progression of linguistic complexity within a text, and Recurrent Neural Network (RNN) classifiers that adequately capture the sequential information in those contours. Our experiments demonstrate that RNN classifiers trained on complexity contours achieve higher classification accuracy than one trained on text-average complexity scores. In a second step, we determine the relative importance of the features from four distinct categories through a Sensitivity-Based Pruning approach.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
Context-based Automated Scoring of Complex Mathematical Responses 基于上下文的复杂数学反应自动评分
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.19
A. Cahill, James H. Fife, Brian Riordan, Avijit Vajpayee, Dmytro Galochkin
{"title":"Context-based Automated Scoring of Complex Mathematical Responses","authors":"A. Cahill, James H. Fife, Brian Riordan, Avijit Vajpayee, Dmytro Galochkin","doi":"10.18653/v1/2020.bea-1.19","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.19","url":null,"abstract":"The tasks of automatically scoring either textual or algebraic responses to mathematical questions have both been well-studied, albeit separately. In this paper we propose a method for automatically scoring responses that contain both text and algebraic expressions. Our method not only achieves high agreement with human raters, but also links explicitly to the scoring rubric – essentially providing explainable models and a way to potentially provide feedback to students in the future.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115690085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction 语法纠错合成数据生成方法的比较研究
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.21
Max White, Alla Rozovskaya
{"title":"A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction","authors":"Max White, Alla Rozovskaya","doi":"10.18653/v1/2020.bea-1.21","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.21","url":null,"abstract":"Grammatical Error Correction (GEC) is concerned with correcting grammatical errors in written text. Current GEC systems, namely those leveraging statistical and neural machine translation, require large quantities of annotated training data, which can be expensive or impractical to obtain. This research compares techniques for generating synthetic data utilized by the two highest scoring submissions to the restricted and low-resource tracks in the BEA-2019 Shared Task on Grammatical Error Correction.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"2016 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121005902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
CIMA: A Large Open Access Dialogue Dataset for Tutoring CIMA:用于辅导的大型开放获取对话数据集
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.5
Katherine Stasaski, Kimberly Kao, Marti A. Hearst
{"title":"CIMA: A Large Open Access Dialogue Dataset for Tutoring","authors":"Katherine Stasaski, Kimberly Kao, Marti A. Hearst","doi":"10.18653/v1/2020.bea-1.5","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.5","url":null,"abstract":"One-to-one tutoring is often an effective means to help students learn, and recent experiments with neural conversation systems are promising. However, large open datasets of tutoring conversations are lacking. To remedy this, we propose 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. In this approach, extended conversations are obtained between crowdworkers role-playing as both students and tutors. The CIMA collection, which we make publicly available, is novel in that students are exposed to overlapping grounded concepts between exercises and multiple relevant tutoring responses are collected for the same input. CIMA contains several compelling properties from an educational perspective: student role-players complete exercises in fewer turns during the course of the conversation and tutor players adopt strategies that conform with some educational conversational norms, such as providing hints versus asking questions in appropriate contexts. The dataset enables a model to be trained to generate the next tutoring utterance in a conversation, conditioned on a provided action strategy.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125924819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Can Neural Networks Automatically Score Essay Traits? 神经网络能自动评分作文特征吗?
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.8
Sandeep Albert Mathias, P. Bhattacharyya
{"title":"Can Neural Networks Automatically Score Essay Traits?","authors":"Sandeep Albert Mathias, P. Bhattacharyya","doi":"10.18653/v1/2020.bea-1.8","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.8","url":null,"abstract":"Essay traits are attributes of an essay that can help explain how well written (or badly written) the essay is. Examples of traits include Content, Organization, Language, Sentence Fluency, Word Choice, etc. A lot of research in the last decade has dealt with automatic holistic essay scoring - where a machine rates an essay and gives a score for the essay. However, writers need feedback, especially if they want to improve their writing - which is why trait-scoring is important. In this paper, we show how a deep-learning based system can outperform feature-based machine learning systems, as well as a string kernel system in scoring essay traits.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124165818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 25
Assisting Undergraduate Students in Writing Spanish Methodology Sections 协助本科生撰写西班牙语方法论部分
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.11
Samuel González-López, Steven Bethard, A. López-López
{"title":"Assisting Undergraduate Students in Writing Spanish Methodology Sections","authors":"Samuel González-López, Steven Bethard, A. López-López","doi":"10.18653/v1/2020.bea-1.11","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.11","url":null,"abstract":"In undergraduate theses, a good methodology section should describe the series of steps that were followed in performing the research. To assist students in this task, we develop machine-learning models and an app that uses them to provide feedback while students write. We construct an annotated corpus that identifies sentences representing methodological steps and labels when a methodology contains a logical sequence of such steps. We train machine-learning models based on language modeling and lexical features that can identify sentences representing methodological steps with 0.939 f-measure, and identify methodology sections containing a logical sequence of steps with an accuracy of 87%. We incorporate these models into a Microsoft Office Add-in, and show that students who improved their methodologies according to the model feedback received better grades on their methodologies.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127385003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners 第二语言学习者多项选择填空题的干扰因素分析与选择
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.10
Lingyu Gao, Kevin Gimpel, A. Jensson
{"title":"Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners","authors":"Lingyu Gao, Kevin Gimpel, A. Jensson","doi":"10.18653/v1/2020.bea-1.10","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.10","url":null,"abstract":"We consider the problem of automatically suggesting distractors for multiple-choice cloze questions designed for second-language learners. We describe the creation of a dataset including collecting manual annotations for distractor selection. We assess the relationship between the choices of the annotators and features based on distractors and the correct answers, both with and without the surrounding passage context in the cloze questions. Simple features of the distractor and correct answer correlate with the annotations, though we find substantial benefit to additionally using large-scale pretrained models to measure the fit of the distractor in the context. Based on these analyses, we propose and train models to automatically select distractors, and measure the importance of model components quantitatively.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131337638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing 论证写作中证据的注释和分类与推理修正
Workshop on Innovative Use of NLP for Building Educational Applications Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.bea-1.7
T. Afrin, E. Wang, D. Litman, L. Matsumura, R. Correnti
{"title":"Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing","authors":"T. Afrin, E. Wang, D. Litman, L. Matsumura, R. Correnti","doi":"10.18653/v1/2020.bea-1.7","DOIUrl":"https://doi.org/10.18653/v1/2020.bea-1.7","url":null,"abstract":"Automated writing evaluation systems can improve students’ writing insofar as students attend to the feedback provided and revise their essay drafts in ways aligned with such feedback. Existing research on revision of argumentative writing in such systems, however, has focused on the types of revisions students make (e.g., surface vs. content) rather than the extent to which revisions actually respond to the feedback provided and improve the essay. We introduce an annotation scheme to capture the nature of sentence-level revisions of evidence use and reasoning (the ‘RER’ scheme) and apply it to 5th- and 6th-grade students’ argumentative essays. We 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. Furthermore, we explore the feasibility of automatically classifying revisions according to our scheme.","PeriodicalId":363390,"journal":{"name":"Workshop on Innovative Use of NLP for Building Educational Applications","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132278330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信