Atsushi Mizumoto
Biographic Data
| ID | 1011939 |
|---|---|
| NAME | Atsushi Mizumoto |
| GIVEN NAMES | Atsushi |
| FAMILY NAME | Mizumoto |
| SIGNATURE | MIZUMOTO A |
| AFFILIATIONS | Kansai University |
| ORCID | 0000-0001-6588-4052 |
| VERIFIED | Yes |
| TOTAL WORKS | 20 |
| TOTAL CITATIONS | 19 |
| AUTHOR COUNT | 20 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 3 |
The role of generative AI in mediating L2MSS and engagement with written feedback in EFL learning
This empirical study explores three aspects of engagement (affective, behavioral, and cognitive) in language learning within an English as a Foreign Language context in Japan, examining their relationship with AI utilization. Previous research has demonstrated that motivation positively influences AI usage. This study expands on that by connecting motivation with engagement, where AI usage serves as an intermediary construct. A total of 174 stude…
Revisiting the Construct Validity of Self-Regulating Capacity in Vocabulary Learning Scale
Research into self-regulating capacity in vocabulary learning is recognized as a significant topic within the second language domain. The self-regulating capacity in vocabulary learning scale (SRCvoc; Tseng et al. 2006) is arguably the most widely used tool for assessing this construct. The common factor model, which is applied through confirmatory factor analysis and exploratory factor analysis, has been the primary methods for validating the SR…
Automated analysis of common errors in L2 learner production
This research report presents the development and validation of Auto Error Analyzer , a prototype web application designed to automate the calculation of accuracy and its related metrics for measuring second language (L2) production. Building on recent advancements in natural language processing (NLP) and artificial intelligence (AI), Auto Error Analyzer introduces an automated accuracy measurement component, bridging a gap in existing assessment…
Exploring Individual Differences in AI‐Assisted and Corpus‐Based Data‐Driven Learning
This study examined the comparative effectiveness of corpus‐based data‐driven learning (DDL; Linguee) and artificial intelligence (AI)‐assisted DDL (ChatGPT) among 69 Japanese university EFL learners. Both approaches produced comparable learning gains, with no significant difference between groups after controlling for pretest performance. However, proficiency emerged as a key moderating factor: intermediate‐level learners achieved greater improv…
Comparing Peer Feedback and Generative Artificial Intelligence Feedback in Japanese English as a Foreign Language Speaking Context
This study explores the comparative effectiveness of peer feedback and generative AI (GenAI) feedback on Japanese university students learning English as a Foreign Language (EFL), specifically examining their motivation, engagement, and writing self‐efficacy during script‐writing preparation for speaking tasks. Acknowledging the close relationship between speaking and writing, as well as the essential role of feedback in second language acquisiti…
Validation of metacognitive knowledge in vocabulary learning and its predictive effects on incidental vocabulary learning from reading
This study investigates the impact of metacognitive knowledge on vocabulary learning among English as a Foreign Language (EFL) learner, involving 776 university students in China. Its primary goal is to develop and validate a scale for assessing metacognitive knowledge in vocabulary learning. The scale is structured around three sub-dimensions: person, task, and strategies, identified through exploratory and confirmatory factor analyses. These su…
Machine translation as a form of feedback on L2 writing
With advances in artificial intelligence (AI), many language teachers have started exploring the classroom implications of AI-powered technology, including machine translation (MT). To examine the usefulness of MT technology in writing instruction, we conducted a mixed-methods study comparing two types of written feedback: comprehensive direct Teacher Corrective Feedback (TCF), and MT feedback. Participants were 23 Japanese university students in…
Incorporating online writing resources into self‐regulated learning strategy‐based instruction
Examining the Effects of the L2 Learning Experience on the Ideal L2 Self and Ought‐to L2 Self in a Japanese University Context
Dörnyei's L2 motivational self‐system (L2MSS) is a dominant theory within the field of language motivation research. In this study, we explore the interrelationship between the three central components of L2MSS, with a particular focus on the often‐overlooked L2 learning experience (L2LE). While previous research has primarily examined the Ideal L2 Self and Ought‐to L2 Self in relation to various factors, this paper explores the impact of the L2L…
Understanding growth mindset, self-regulated vocabulary learning, and vocabulary knowledge
Exploring the potential of using an AI language model for automated essay scoring
The widespread adoption of ChatGPT, an AI language model, has the potential to bring about significant changes to the research, teaching, and learning of foreign languages. The present study aims to leverage this technology to perform automated essay scoring (AES) and evaluate its reliability and accuracy. Specifically, we utilized the GPT-3 text-davinci-003 model to automatically score all 12,100 essays contained in the ETS Corpus of Non-Native …
The role of spoken vocabulary knowledge in language minority students’ incidental vocabulary learning from captioned television
This study was to assess the spoken vocabulary knowledge and its role in incidental vocabulary learning from captioned television. The participants were a total of 87 minority students learning English as a foreign language in Australia. The breadth of their vocabulary knowledge was measured with a vocabulary size test, while the depth of their vocabulary knowledge was through an assessment of collocational and semantic relationships. The results…
Calculating the Relative Importance of Multiple Regression Predictor Variables Using Dominance Analysis and Random Forests
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a machine learning technique, in this method showcase article for accurately determining predictor imp…
Association between Productive Roles and Frailty Factors among Community-Dwelling Older Adults
The employment rate of older people in Japan is expected to increase in the future owing to the increase in the retirement age. Preventing frailty is imperative to maintaining productive roles of older adults. Therefore, this study aimed to examine the association between productive roles and frailty factors among community-dwelling older adults. A total of 135 older adults, enrolled in 2017, participated in the study. Productive roles and domain…
Developing and evaluating a computerized adaptive testing version of the Word Part Levels Test
The knowledge about affix plays a vital role in the development of word knowledge and vocabulary acquisition. A test for diagnostic information on the level of affix knowledge would be useful in order to inform the test users of what learners have gained or lacked in this integral component of vocabulary knowledge. This paper reports the development and evaluation of a computerized adaptive testing (CAT) version of the Word Part Levels Test (WPLT…
Applying the Bundle-Move Connection Approach to the Development of an Online Writing Support Tool for Research Articles
With advances in information and computer technology, genre-based writing pedagogy has developed greatly in recent years. In order to further this growth in technology-enhanced genre writing pedagogy, this study developed a data-driven and theory-based practical support tool for writing research articles. This web-based, innovative tool, powered by a combination of rhetorical moves and lexical bundles, has an autocomplete feature that suggests th…
R as a Lingua Franca
In this article, we suggest that using R, a statistical software environment, is advantageous for quantitative researchers in applied linguistics. We first provide a brief overview of the reasons why R is popular among researchers in other fields and why we recommend its use for analyses in applied linguistics. In order to illustrate these benefits, we report recent works and developments in quantitative data analysis seeking to move the field to…
Who is data-driven learning for? Challenging the monolithic view of its relationship with learning styles
Association between hip walking and physical fitness in the elderly in a community setting
This study examined the use of the hip walking (HW) distance test as a physical performance parameter, and investigated the association between HW distance and strength, balance, and gait speed in the elderly. The study involved 106 community-dwelling elderly individuals (mean age 75.4 years). Participants performed the following physical performance tests: the HW distance test, the functional reach test (FRT), and tests for knee extensor strengt…
Adaptation and Validation of Self-regulating Capacity in Vocabulary Learning Scale
This article reports on an adaptation and validation study of SRCvoc (self-regulating capacity in vocabulary learning scale; Tseng et al. 2006) in a Japanese EFL setting. The piloting phase revealed that factor structures were different from those in the original study. The main study, including a self-reported measure of procrastination to explore the convergent evidence of the construct validity, suggests that the scale can be a valid measure o…
Calculating the Relative Importance of Multiple Regression Predictor Variables Using Dominance Analysis and Random Forests
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a machine learning technique, in this method showcase article for accurately determining predictor imp…
Applying the Bundle-Move Connection Approach to the Development of an Online Writing Support Tool for Research Articles
With advances in information and computer technology, genre-based writing pedagogy has developed greatly in recent years. In order to further this growth in technology-enhanced genre writing pedagogy, this study developed a data-driven and theory-based practical support tool for writing research articles. This web-based, innovative tool, powered by a combination of rhetorical moves and lexical bundles, has an autocomplete feature that suggests th…
Understanding growth mindset, self-regulated vocabulary learning, and vocabulary knowledge
Who is data-driven learning for? Challenging the monolithic view of its relationship with learning styles
Examining the Effects of the L2 Learning Experience on the Ideal L2 Self and Ought‐to L2 Self in a Japanese University Context
Dörnyei's L2 motivational self‐system (L2MSS) is a dominant theory within the field of language motivation research. In this study, we explore the interrelationship between the three central components of L2MSS, with a particular focus on the often‐overlooked L2 learning experience (L2LE). While previous research has primarily examined the Ideal L2 Self and Ought‐to L2 Self in relation to various factors, this paper explores the impact of the L2L…
Adaptation and Validation of Self-regulating Capacity in Vocabulary Learning Scale
This article reports on an adaptation and validation study of SRCvoc (self-regulating capacity in vocabulary learning scale; Tseng et al. 2006) in a Japanese EFL setting. The piloting phase revealed that factor structures were different from those in the original study. The main study, including a self-reported measure of procrastination to explore the convergent evidence of the construct validity, suggests that the scale can be a valid measure o…
Association between hip walking and physical fitness in the elderly in a community setting
This study examined the use of the hip walking (HW) distance test as a physical performance parameter, and investigated the association between HW distance and strength, balance, and gait speed in the elderly. The study involved 106 community-dwelling elderly individuals (mean age 75.4 years). Participants performed the following physical performance tests: the HW distance test, the functional reach test (FRT), and tests for knee extensor strengt…
R as a Lingua Franca
In this article, we suggest that using R, a statistical software environment, is advantageous for quantitative researchers in applied linguistics. We first provide a brief overview of the reasons why R is popular among researchers in other fields and why we recommend its use for analyses in applied linguistics. In order to illustrate these benefits, we report recent works and developments in quantitative data analysis seeking to move the field to…
Who is data-driven learning for? Challenging the monolithic view of its relationship with learning styles
Applying the Bundle-Move Connection Approach to the Development of an Online Writing Support Tool for Research Articles
With advances in information and computer technology, genre-based writing pedagogy has developed greatly in recent years. In order to further this growth in technology-enhanced genre writing pedagogy, this study developed a data-driven and theory-based practical support tool for writing research articles. This web-based, innovative tool, powered by a combination of rhetorical moves and lexical bundles, has an autocomplete feature that suggests th…
Developing and evaluating a computerized adaptive testing version of the Word Part Levels Test
The knowledge about affix plays a vital role in the development of word knowledge and vocabulary acquisition. A test for diagnostic information on the level of affix knowledge would be useful in order to inform the test users of what learners have gained or lacked in this integral component of vocabulary knowledge. This paper reports the development and evaluation of a computerized adaptive testing (CAT) version of the Word Part Levels Test (WPLT…
Association between Productive Roles and Frailty Factors among Community-Dwelling Older Adults
The employment rate of older people in Japan is expected to increase in the future owing to the increase in the retirement age. Preventing frailty is imperative to maintaining productive roles of older adults. Therefore, this study aimed to examine the association between productive roles and frailty factors among community-dwelling older adults. A total of 135 older adults, enrolled in 2017, participated in the study. Productive roles and domain…
Exploring the potential of using an AI language model for automated essay scoring
The widespread adoption of ChatGPT, an AI language model, has the potential to bring about significant changes to the research, teaching, and learning of foreign languages. The present study aims to leverage this technology to perform automated essay scoring (AES) and evaluate its reliability and accuracy. Specifically, we utilized the GPT-3 text-davinci-003 model to automatically score all 12,100 essays contained in the ETS Corpus of Non-Native …
The role of spoken vocabulary knowledge in language minority students’ incidental vocabulary learning from captioned television
This study was to assess the spoken vocabulary knowledge and its role in incidental vocabulary learning from captioned television. The participants were a total of 87 minority students learning English as a foreign language in Australia. The breadth of their vocabulary knowledge was measured with a vocabulary size test, while the depth of their vocabulary knowledge was through an assessment of collocational and semantic relationships. The results…
Calculating the Relative Importance of Multiple Regression Predictor Variables Using Dominance Analysis and Random Forests
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a machine learning technique, in this method showcase article for accurately determining predictor imp…
Incorporating online writing resources into self‐regulated learning strategy‐based instruction
Examining the Effects of the L2 Learning Experience on the Ideal L2 Self and Ought‐to L2 Self in a Japanese University Context
Dörnyei's L2 motivational self‐system (L2MSS) is a dominant theory within the field of language motivation research. In this study, we explore the interrelationship between the three central components of L2MSS, with a particular focus on the often‐overlooked L2 learning experience (L2LE). While previous research has primarily examined the Ideal L2 Self and Ought‐to L2 Self in relation to various factors, this paper explores the impact of the L2L…
Understanding growth mindset, self-regulated vocabulary learning, and vocabulary knowledge
The role of generative AI in mediating L2MSS and engagement with written feedback in EFL learning
This empirical study explores three aspects of engagement (affective, behavioral, and cognitive) in language learning within an English as a Foreign Language context in Japan, examining their relationship with AI utilization. Previous research has demonstrated that motivation positively influences AI usage. This study expands on that by connecting motivation with engagement, where AI usage serves as an intermediary construct. A total of 174 stude…
Revisiting the Construct Validity of Self-Regulating Capacity in Vocabulary Learning Scale
Research into self-regulating capacity in vocabulary learning is recognized as a significant topic within the second language domain. The self-regulating capacity in vocabulary learning scale (SRCvoc; Tseng et al. 2006) is arguably the most widely used tool for assessing this construct. The common factor model, which is applied through confirmatory factor analysis and exploratory factor analysis, has been the primary methods for validating the SR…
Automated analysis of common errors in L2 learner production
This research report presents the development and validation of Auto Error Analyzer , a prototype web application designed to automate the calculation of accuracy and its related metrics for measuring second language (L2) production. Building on recent advancements in natural language processing (NLP) and artificial intelligence (AI), Auto Error Analyzer introduces an automated accuracy measurement component, bridging a gap in existing assessment…
Exploring Individual Differences in AI‐Assisted and Corpus‐Based Data‐Driven Learning
This study examined the comparative effectiveness of corpus‐based data‐driven learning (DDL; Linguee) and artificial intelligence (AI)‐assisted DDL (ChatGPT) among 69 Japanese university EFL learners. Both approaches produced comparable learning gains, with no significant difference between groups after controlling for pretest performance. However, proficiency emerged as a key moderating factor: intermediate‐level learners achieved greater improv…
Comparing Peer Feedback and Generative Artificial Intelligence Feedback in Japanese English as a Foreign Language Speaking Context
This study explores the comparative effectiveness of peer feedback and generative AI (GenAI) feedback on Japanese university students learning English as a Foreign Language (EFL), specifically examining their motivation, engagement, and writing self‐efficacy during script‐writing preparation for speaking tasks. Acknowledging the close relationship between speaking and writing, as well as the essential role of feedback in second language acquisiti…
Validation of metacognitive knowledge in vocabulary learning and its predictive effects on incidental vocabulary learning from reading
This study investigates the impact of metacognitive knowledge on vocabulary learning among English as a Foreign Language (EFL) learner, involving 776 university students in China. Its primary goal is to develop and validate a scale for assessing metacognitive knowledge in vocabulary learning. The scale is structured around three sub-dimensions: person, task, and strategies, identified through exploratory and confirmatory factor analyses. These su…
Machine translation as a form of feedback on L2 writing
With advances in artificial intelligence (AI), many language teachers have started exploring the classroom implications of AI-powered technology, including machine translation (MT). To examine the usefulness of MT technology in writing instruction, we conducted a mixed-methods study comparing two types of written feedback: comprehensive direct Teacher Corrective Feedback (TCF), and MT feedback. Participants were 23 Japanese university students in…
Computer Science (13 works) · Psychology (12 works) · Linguistics (10 works) · Second Language Acquisition and Learning (9 works) · EFL/ESL Teaching and Learning (7 works) · Vocabulary (6 works) · Innovative Teaching and Learning Methods (5 works) · Machine learning (5 works) · Mathematics education (5 works) · Artificial Intelligence (4 works)