An NLP-Driven Interactive Guidance System for English Writing.
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| Title: | An NLP-Driven Interactive Guidance System for English Writing. |
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| Authors: | Cai, Jingyi1 caijingyi1984@163.com |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 10, p97-111. 15p. |
| Subjects: | English language writing, Natural language processing, Academic discourse, Education software, Mobile learning |
| Abstract: | Academic English writing on mobile platforms has been constrained by limited screen-based interaction, insufficient adaptation to fragmented learning contexts, and feedback mechanisms that lack pedagogical depth and individual specificity. To address these challenges, a mobile-native interactive English writing guidance system integrating natural language processing (NLP) was designed. Three core innovations were introduced. First, a touchoptimized interaction paradigm was constructed to enable direct interaction between text and feedback. Second, an ontology-based explainable feedback mechanism was proposed to enhance feedback precision and instructional value. Third, a dynamic assessment-driven progressive feedback generation algorithm was developed to adaptively support learners at varying proficiency levels. The system with a multi-agent collaborative architecture integrates a lightweight academic writing ontology knowledge base with mobile-adapted NLP model optimization strategies. Experimental results demonstrated that the proposed system significantly outperformed mainstream baseline approaches in interaction efficiency, feedback quality, and writing performance improvement. Task completion time was reduced by 21.6%-24.1% compared with the control group, feedback precision reached 89.7%, and a 2.1-point improvement was observed in three-dimensional writing quality scores. Correlation analysis revealed a significant negative relationship between interaction efficiency and user dissatisfaction, while a significant positive relationship was identified between feedback explainability and error correction rates. Ablation experiments further confirmed the critical contribution of the three proposed modules to overall system performance. This study establishes a novel paradigm for intelligent writing guidance in mobile contexts and advances the deep integration of digital education and mobile artificial intelligence (AI). [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 194196192 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An NLP-Driven Interactive Guidance System for English Writing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cai%2C+Jingyi%22">Cai, Jingyi</searchLink><relatesTo>1</relatesTo><i> caijingyi1984@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Interactive+Mobile+Technologies%22">International Journal of Interactive Mobile Technologies</searchLink>. 2026, Vol. 20 Issue 10, p97-111. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22English+language+writing%22">English language writing</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+discourse%22">Academic discourse</searchLink><br /><searchLink fieldCode="DE" term="%22Education+software%22">Education software</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+learning%22">Mobile learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Academic English writing on mobile platforms has been constrained by limited screen-based interaction, insufficient adaptation to fragmented learning contexts, and feedback mechanisms that lack pedagogical depth and individual specificity. To address these challenges, a mobile-native interactive English writing guidance system integrating natural language processing (NLP) was designed. Three core innovations were introduced. First, a touchoptimized interaction paradigm was constructed to enable direct interaction between text and feedback. Second, an ontology-based explainable feedback mechanism was proposed to enhance feedback precision and instructional value. Third, a dynamic assessment-driven progressive feedback generation algorithm was developed to adaptively support learners at varying proficiency levels. The system with a multi-agent collaborative architecture integrates a lightweight academic writing ontology knowledge base with mobile-adapted NLP model optimization strategies. Experimental results demonstrated that the proposed system significantly outperformed mainstream baseline approaches in interaction efficiency, feedback quality, and writing performance improvement. Task completion time was reduced by 21.6%-24.1% compared with the control group, feedback precision reached 89.7%, and a 2.1-point improvement was observed in three-dimensional writing quality scores. Correlation analysis revealed a significant negative relationship between interaction efficiency and user dissatisfaction, while a significant positive relationship was identified between feedback explainability and error correction rates. Ablation experiments further confirmed the critical contribution of the three proposed modules to overall system performance. This study establishes a novel paradigm for intelligent writing guidance in mobile contexts and advances the deep integration of digital education and mobile artificial intelligence (AI). [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3991/ijim.v20i10.61925 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 97 Subjects: – SubjectFull: English language writing Type: general – SubjectFull: Natural language processing Type: general – SubjectFull: Academic discourse Type: general – SubjectFull: Education software Type: general – SubjectFull: Mobile learning Type: general Titles: – TitleFull: An NLP-Driven Interactive Guidance System for English Writing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cai, Jingyi IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18657923 Numbering: – Type: volume Value: 20 – Type: issue Value: 10 Titles: – TitleFull: International Journal of Interactive Mobile Technologies Type: main |
| ResultId | 1 |
