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001 3256191438
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022 |a 2363-5169 
024 7 |a 10.1186/s40862-025-00351-y  |2 doi 
035 |a 3256191438 
045 2 |b d20251201  |b d20251231 
100 1 |a Tay, Dennis  |u Nanyang Technological University, Division of Linguistics and Multilingual Studies, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); Shenzhen Polytechnic University, School of Foreign Languages and Business, Shenzhen, China (GRID:grid.464445.3) (ISNI:0000 0004 1790 3863) 
245 1 |a Fingerprints of EFL writing: an AI deep learning approach 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a Standard methods for assessing English as a Foreign Language (EFL) writing often prioritize top-down criteria that may overlook subtle patterns and styles employed by different learners. We demonstrate a systematic and replicable three-phase approach to capture EFL writing styles using AI and data analytics, highlighting attendant insights and implications. Our approach involves (i) training a deep learning Variational Autoencoder to extract latent stylistic ‘fingerprints’ that are independent of the topic and content of writing, (ii) cluster analysis to identify emergent clusters as styles based on these fingerprints, and (iii) qualitative analysis of exemplars to interpret the styles. A case study application to EFL essays across argumentative, narrative, and reflective genres (N = 892) revealed four writing styles: 'error-prone ambition' (characterized by performative displays of advanced but contextually inappropriate vocabulary), 'striking a balance' (a more controlled approach at balancing vocabulary and grammar), 'safe and secure' (prioritizing clarity with minimal risks), and 'inconsistent expression' (deliberate or inadvertent inconsistency in stylistic choices). The clusters defining these styles have different sizes and variances, with overlapping essays hinting at underexplored developmental trajectories in EFL writing. They affirm a broader perspective where writing styles reflect not only linguistic features but also learning attitudes and strategies. Furthermore, our approach further minimizes emphasis on lexical and grammatical errors, focusing instead on stylistic regularities that can facilitate less punitive, and more nuanced and affirming ways to teach EFL writing. 
653 |a Language 
653 |a Qualitative research 
653 |a Pedagogy 
653 |a Deep learning 
653 |a Case studies 
653 |a Student writing 
653 |a Stylistics 
653 |a Cluster analysis 
653 |a Teachers 
653 |a Second language writing 
653 |a Linguistics 
653 |a English as a second language instruction 
653 |a Sprinkler systems 
653 |a Errors 
653 |a Writing 
653 |a Ambition 
653 |a Learning 
653 |a Inconsistency 
653 |a English as a second language 
653 |a Foreign languages 
653 |a Fingerprinting 
653 |a English language 
653 |a Vocabulary 
653 |a Scholarship 
653 |a Inappropriateness 
653 |a Prioritizing 
653 |a Artificial intelligence 
653 |a Foreign language learning 
653 |a Multivariate Analysis 
653 |a Semantics 
653 |a Reading Skills 
653 |a Interference (Language) 
653 |a Learning Processes 
653 |a Psychotherapy 
653 |a English (Second Language) 
653 |a Native Language 
653 |a Modeling (Psychology) 
653 |a Language Patterns 
653 |a Discourse Analysis 
653 |a Language Aptitude 
653 |a Emergent Literacy 
653 |a Essays 
653 |a Educational Assessment 
653 |a Creativity 
653 |a English Learners 
653 |a Cultural Influences 
653 |a Educational Experience 
653 |a English 
653 |a Literary Genres 
653 |a Educational Background 
653 |a Algorithms 
700 1 |a Xie, Dandan  |u Nanyang Technological University, Division of Linguistics and Multilingual Studies, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); Shenzhen Polytechnic University, School of Foreign Languages and Business, Shenzhen, China (GRID:grid.464445.3) (ISNI:0000 0004 1790 3863) 
773 0 |t Asian-Pacific Journal of Second and Foreign Language Education  |g vol. 10, no. 1 (Dec 2025), p. 43 
786 0 |d ProQuest  |t Education Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3256191438/abstract/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3256191438/fulltext/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3256191438/fulltextPDF/embedded/J7RWLIQ9I3C9JK51?source=fedsrch