Atsushi Mizumoto

Professor

Kansai University

Japan

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Professor Atsushi Mizumoto is a faculty member at Kansai University in Japan. His research interests encompass language learning, particularly the application of generative AI in educational contexts, self-regulation in vocabulary learning, and the challenges of data-driven learning. Recent publications highlight the importance of understanding the L2 motivational self system and the implications of technology usage in enhancing learner engagement and performance.

Articles (18)

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2022

Collaborators (2)

Masaki Eguchi

Research Assistant Professor

Waseda University

JAPAN

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Yo In'nami

Chuo University

JAPAN

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Atsushi Mizumoto

Research Interests

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Articles (18)

Large language models fall short in classifying learners’ open-ended responses

Automated analysis of common errors in L2 learner production: Prototype web application development

Examining the Effects of the L2 Learning Experience on the Ideal L2 Self and Ought‐to L2 Self in a Japanese University Context

The effects of generative AI usage in EFL classrooms on the l2 motivational self system

Exploring the Barriers to Data-driven Learning in the Classroom: A Systematic Qualitative Synthesis

The role of generative AI in mediating L2MSS and engagement with written feedback in EFL learning: A structural equation modeling approach

Examining the relationship between the L2 motivational self system and technology acceptance model post ChatGPT introduction and utilization

Testing the viability of ChatGPT as a companion in L2 writing accuracy assessment

Understanding growth mindset, self-regulated vocabulary learning, and vocabulary knowledge

Revisiting the Construct Validity of Self-Regulating Capacity in Vocabulary Learning Scale: The Confirmatory Composite Analysis (CCA) Approach

Validation of metacognitive knowledge in vocabulary learning and its predictive effects on incidental vocabulary learning from reading

Identifying ChatGPT-generated texts in EFL students’ writing: Through comparative analysis of linguistic fingerprints

Examining the effect of generative AI on students’ motivation and writing self-efficacy

Data-driven Learning Meets Generative AI: Introducing the Framework of Metacognitive Resource Use

The role of spoken vocabulary knowledge in language minority students’ incidental vocabulary learning from captioned television

Exploring the potential of using an AI language model for automated essay scoring

Calculating the Relative Importance of Multiple Regression Predictor Variables Using Dominance Analysis and Random Forests

Promoting computationally reproducible research in applied linguistics: Recommended practices and considerations

Collaborators (2)

Masaki Eguchi

Yo In'nami

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