Design of an Immersive Task-Driven Mobile Interactive Platform for EFL Writing and Analysis of Language Output Complexity.
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| Title: | Design of an Immersive Task-Driven Mobile Interactive Platform for EFL Writing and Analysis of Language Output Complexity. |
|---|---|
| Authors: | Zhao, Yaling1 zhaoyaling@hevute.edu.cn, Zhao, Junxia1 zhaojunxia@hevute.edu.cn |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 6, p39-53. 15p. |
| Subjects: | Linguistic complexity, Augmented reality, Computer assisted instruction, Reinforcement learning, Communication infrastructure, Mobile learning, Active learning, English as a foreign language |
| Abstract: | The widespread adoption of mobile learning has accelerated the development of English writing support tools; however, existing applications often suffer from limited immersion, weak adaptivity, and an overreliance on post-hoc outcome-based analyses of language complexity, with insufficient capture of the writing process itself. To address these limitations, this study designs and implements an immersive task-driven mobile interactive platform for English as a foreign language (EFL) writing, integrating a multi-technology immersive writing environment with an automated language complexity analysis framework. The platform introduces three core innovations: (1) a context-aware dynamic task engine driven by situational perception, (2) a multimodal augmented reality (AR) interactive interface to enhance immersion, and (3) a full-process data pipeline specifically designed for fine-grained language complexity analysis. A mobile-cloud collaborative architecture is adopted, in which task generation is dynamically optimized through a hybrid algorithm combining rule-based logic and reinforcement learning. Results from controlled experiments indicate that, compared with the control group, learners in the experimental group achieved significantly greater improvements in both syntactic complexity--average sentence length (+22.4%), mean clause length (+19.8%), and subordinate clause density (LD) (+17.6%)--and lexical complexity, including lexical diversity (+17.7%) and academic vocabulary usage (+58.5%). All between-group differences reached a highly significant level (p < 0.001). Further analysis reveals that task immersion, feedback uptake rate, and scenario-task alignment are key predictors of language complexity gains, jointly explaining 68.3% of the variance. In addition, the platform demonstrates robust performance across heterogeneous mobile devices, achieving an AR scene recognition accuracy of at least 81.2% and a feedback generation latency of no more than 268 ms. By deeply integrating multiple technologies, this study establishes a closed-loop intervention framework encompassing "context-task-feedback-analysis," addressing a critical gap in existing research on multi-technology-enabled writing instruction. The findings provide a novel paradigm and empirical evidence for innovation in mobile technology-driven language education. [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: 192680388 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Design of an Immersive Task-Driven Mobile Interactive Platform for EFL Writing and Analysis of Language Output Complexity. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhao%2C+Yaling%22">Zhao, Yaling</searchLink><relatesTo>1</relatesTo><i> zhaoyaling@hevute.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Junxia%22">Zhao, Junxia</searchLink><relatesTo>1</relatesTo><i> zhaojunxia@hevute.edu.cn</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 6, p39-53. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Linguistic+complexity%22">Linguistic complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Augmented+reality%22">Augmented reality</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+assisted+instruction%22">Computer assisted instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Reinforcement+learning%22">Reinforcement learning</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+infrastructure%22">Communication infrastructure</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+learning%22">Mobile learning</searchLink><br /><searchLink fieldCode="DE" term="%22Active+learning%22">Active learning</searchLink><br /><searchLink fieldCode="DE" term="%22English+as+a+foreign+language%22">English as a foreign language</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The widespread adoption of mobile learning has accelerated the development of English writing support tools; however, existing applications often suffer from limited immersion, weak adaptivity, and an overreliance on post-hoc outcome-based analyses of language complexity, with insufficient capture of the writing process itself. To address these limitations, this study designs and implements an immersive task-driven mobile interactive platform for English as a foreign language (EFL) writing, integrating a multi-technology immersive writing environment with an automated language complexity analysis framework. The platform introduces three core innovations: (1) a context-aware dynamic task engine driven by situational perception, (2) a multimodal augmented reality (AR) interactive interface to enhance immersion, and (3) a full-process data pipeline specifically designed for fine-grained language complexity analysis. A mobile-cloud collaborative architecture is adopted, in which task generation is dynamically optimized through a hybrid algorithm combining rule-based logic and reinforcement learning. Results from controlled experiments indicate that, compared with the control group, learners in the experimental group achieved significantly greater improvements in both syntactic complexity--average sentence length (+22.4%), mean clause length (+19.8%), and subordinate clause density (LD) (+17.6%)--and lexical complexity, including lexical diversity (+17.7%) and academic vocabulary usage (+58.5%). All between-group differences reached a highly significant level (p < 0.001). Further analysis reveals that task immersion, feedback uptake rate, and scenario-task alignment are key predictors of language complexity gains, jointly explaining 68.3% of the variance. In addition, the platform demonstrates robust performance across heterogeneous mobile devices, achieving an AR scene recognition accuracy of at least 81.2% and a feedback generation latency of no more than 268 ms. By deeply integrating multiple technologies, this study establishes a closed-loop intervention framework encompassing "context-task-feedback-analysis," addressing a critical gap in existing research on multi-technology-enabled writing instruction. The findings provide a novel paradigm and empirical evidence for innovation in mobile technology-driven language education. [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.v20i06.60863 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 39 Subjects: – SubjectFull: Linguistic complexity Type: general – SubjectFull: Augmented reality Type: general – SubjectFull: Computer assisted instruction Type: general – SubjectFull: Reinforcement learning Type: general – SubjectFull: Communication infrastructure Type: general – SubjectFull: Mobile learning Type: general – SubjectFull: Active learning Type: general – SubjectFull: English as a foreign language Type: general Titles: – TitleFull: Design of an Immersive Task-Driven Mobile Interactive Platform for EFL Writing and Analysis of Language Output Complexity. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhao, Yaling – PersonEntity: Name: NameFull: Zhao, Junxia IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 03 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18657923 Numbering: – Type: volume Value: 20 – Type: issue Value: 6 Titles: – TitleFull: International Journal of Interactive Mobile Technologies Type: main |
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