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Michael Suhan

Dados Biográficos

ID8903258
NOMEMichael Suhan
PRENOMESMichael
SOBRENOMESuhan
ASSINATURASUHAN M
AFILIAÇÕESETS, USA
ORCID0000-0002-4734-3794
VERIFICADOSim
TOTAL DE OBRAS4
TOTAL DE CITAÇÕES0
OBRAS COMO AUTOR4
OBRAS COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2026
ANO MAIS RECENTE DE PUBLICAÇÃO2026
ÍNDICE H0
  • Young L2 students’ use of an AI-assisted writing assessment and feedback tool

    Open Access•Mikyung Kim Wolf, Michael Suhan et al.•ARTICLE•Assessing Writing•2026

  • Stealth assessment of oral reading fluency during interactive book reading

    Zuowei Wang, Tenaha O’reilly et al.•ARTICLE•Journal of Research on Technology…•2026

    Oral reading fluency (ORF) assessments are widely used to predict students’ reading proficiency and signal the need for additional instruction. Standardized ORF assessments require substantial resources to develop and take time from instruction to administer; they may also increase test anxiety. To address these concerns, we explored stealth assessment of ORF during book reading. Eighty students (grades 4–5) engaged in interactive book reading th…

  • Exploring linguistic characteristics across Cefr writing levels and their relationships with student backgrounds

    Open Access•Mikyung Kim Wolf, Stefan D Keller et al.•ARTICLE•Journal of Second Language Writing•2026

    This study attempted to identify significant linguistic features that distinguish across CEFR writing levels. The sample included essays from 959 German-speaking EFL students on two tasks: an Independent argumentative task and an Integrated summarizing task. Using natural language processing tools, 19 linguistic features encompassing fluency, lexical, syntactic, and cohesion dimensions were extracted and analyzed through ANOVAs and post-hoc tests…

  • A comparative study of the human, automated scoring model, and GPT-4 ratings of young EFL students’ writing

    Open Access•Michael Suhan, Mikyung Kim Wolf•ARTICLE•Language Testing•2026

    Large language models, such as OpenAI’s GPT-4, have the potential to revolutionize automated writing evaluation (AWE). The present study examines the performance of the GPT-4 model in evaluating the writing of young English as a foreign language learners. Responses to three constructed response tasks ( n = 1908) on Educational Testing Service’s (ETS’s) TOEFL Junior ® Writing test were scored using two different GPT-4 prompting methods. Scores pre…

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  • Young L2 students’ use of an AI-assisted writing assessment and feedback tool

    Open Access•Mikyung Kim Wolf, Michael Suhan et al.•ARTICLE•Assessing Writing•2026

  • Stealth assessment of oral reading fluency during interactive book reading

    Zuowei Wang, Tenaha O’reilly et al.•ARTICLE•Journal of Research on Technology…•2026

    Oral reading fluency (ORF) assessments are widely used to predict students’ reading proficiency and signal the need for additional instruction. Standardized ORF assessments require substantial resources to develop and take time from instruction to administer; they may also increase test anxiety. To address these concerns, we explored stealth assessment of ORF during book reading. Eighty students (grades 4–5) engaged in interactive book reading th…

  • Exploring linguistic characteristics across Cefr writing levels and their relationships with student backgrounds

    Open Access•Mikyung Kim Wolf, Stefan D Keller et al.•ARTICLE•Journal of Second Language Writing•2026

    This study attempted to identify significant linguistic features that distinguish across CEFR writing levels. The sample included essays from 959 German-speaking EFL students on two tasks: an Independent argumentative task and an Integrated summarizing task. Using natural language processing tools, 19 linguistic features encompassing fluency, lexical, syntactic, and cohesion dimensions were extracted and analyzed through ANOVAs and post-hoc tests…

  • A comparative study of the human, automated scoring model, and GPT-4 ratings of young EFL students’ writing

    Open Access•Michael Suhan, Mikyung Kim Wolf•ARTICLE•Language Testing•2026

    Large language models, such as OpenAI’s GPT-4, have the potential to revolutionize automated writing evaluation (AWE). The present study examines the performance of the GPT-4 model in evaluating the writing of young English as a foreign language learners. Responses to three constructed response tasks ( n = 1908) on Educational Testing Service’s (ETS’s) TOEFL Junior ® Writing test were scored using two different GPT-4 prompting methods. Scores pre…

Electronic learning (2 obras) · Fluency (2 obras) · Reading and Literacy Development (2 obras) · Writing and Handwriting Education (2 obras) · AI in Service Interactions (1 obra) · Argumentative (1 obra) · Child Development and Digital Technology (1 obra) · Educational Assessment and Pedagogy (1 obra) · Educational Methods and Media Use (1 obra) · EFL/ESL Teaching and Learning (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae