Can Natural Language Processing Become Natural Language Coaching?

Hearst, Marti A.

doi:10.3115/v1/p15-1120

Cited by 8 publications

(3 citation statements)

References 36 publications

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“…Chatbots are a promising tool to address this. Speech recognition and natural language processesing (NLP) advances have significantly improved chatbot technology, especially in targeted domains [20]. Chatbots can also help simulate the process of talking to another human in a more natural way than synthesized voices and potentially could offer additional benefits such as enhanced distributed cognition and social interaction abilities [35].…”

Section: Introductionmentioning

confidence: 99%

EnglishBot: An AI-Powered Conversational System for Second Language Learning

Ruan

Jiang

et al. 2021

26th International Conference on Intelligent User Interfaces

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Today, many students learn to speak a foreign language by listening to and repeating pre-recorded materials due to the lack of practice opportunities with human partners. Leveraging recent advancements in AI, Speech, and NLP, we developed EnglishBot, a language learning chatbot that converses with students interactively on college-related topics and provides adaptive feedback. We evaluated EnglishBot against a traditional listen-and-repeat interface with 56 Chinese college students through two six-day user studies under both voluntary and fixed-usage conditions. Students' fluency improved more with EnglishBot as evaluated by the IELTS grading standard for voluntary learning. EnglishBot users also showed higher engagement and voluntarily spent 2.1 times more time interacting with EnglishBot. Our results suggest that conversational interfaces may benefit foreign learners' oral language learning, particularly under casual learning settings. CCS CONCEPTS• Applied computing → Education; • Human-centered computing → Natural language interfaces; Empirical studies in HCI .

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Section: Introductionmentioning

confidence: 99%

EnglishBot: An AI-Powered Conversational System for Second Language Learning

Ruan

Jiang

et al. 2021

26th International Conference on Intelligent User Interfaces

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“…Researches have pointed out that supplying suggestions while writing is more helpful than suggesting after the fact (Hearst, 2015). Grammarly tries to correct grammatical errors and provides the explanation while the user is writing.…”

Section: Regexmentioning

confidence: 99%

Level-Up: Learning to Improve Proficiency Level of Essays

Han¹,

Chen

Yang

et al. 2019

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

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We introduce a method for generating suggestions on a given sentence for improving the proficiency level. In our approach, the sentence is transformed into a sequence of grammatical elements aimed at providing suggestions of more advanced grammar elements based on originals. The method involves parsing the sentence, identifying grammatical elements, and ranking related elements to recommend a higher level of grammatical element. We present a prototype coaching system, Level-Up, that applies the method to English learners' essays in order to assist them in writing and reading. Evaluation on a set of essays shows that our method does assist user in writing.

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“…Research issues in this direction have gained more and more attention (Hearst, 2015). Examples include the workshops on Innovative Use of NLP for Building Educational Applications (BEA) since 2003 1 and the workshops on Natural Language Processing Techniques for Educational Applications (NLPTEA) since 2014 2 , where the former was held in North America mainly for English or western languages, while the latter was held in Asia mainly for Chinese or oriental languages.…”

Section: Introductionmentioning

confidence: 99%

Multilingual Short Text Responses Clustering for Mobile Educational Activities: a Preliminary Exploration

Tseng

Lee

Chien

et al. 2018

Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications

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Text clustering is a powerful technique to detect topics from document corpora, so as to provide information browsing, analysis, and organization. On the other hand, the Instant Response System (IRS) has been widely used in recent years to enhance student engagement in class and thus improve their learning effectiveness. However, the lack of functions to process short text responses from the IRS prevents the further application of IRS in classes. Therefore, this study aims to propose a proper short text clustering module for the IRS, and demonstrate our implemented techniques through real-world examples, so as to provide experiences and insights for further study. In particular, we have compared three clustering methods and the result shows that theoretically better methods need not lead to better results, as there are various factors that may affect the final performance.

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Can Natural Language Processing Become Natural Language Coaching?

Cited by 8 publications

References 36 publications

EnglishBot: An AI-Powered Conversational System for Second Language Learning

EnglishBot: An AI-Powered Conversational System for Second Language Learning

Level-Up: Learning to Improve Proficiency Level of Essays

Multilingual Short Text Responses Clustering for Mobile Educational Activities: a Preliminary Exploration

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