Scholarly Works by Atsushi Mizumoto

in press

[118]
Mizumoto, A. (in press). API. In L. McCallum & D. Tafazoli (Eds.), The Palgrave Encyclopedia of Computer-Assisted Language Learning. Palgrave.
[117]
Huang, J., & Mizumoto, A. (in press). Prompt engineering. In L. McCallum & D. Tafazoli (Eds.), The Palgrave Encyclopedia of Computer-Assisted Language Learning. Palgrave.

2025

[116]
Huang, J., & Mizumoto, A. (2025). The role of generative AI in mediating L2MSS and engagement with written feedback in EFL learning: A structural equation modeling approach. Annual Review of Applied Linguistics. https://doi.org/10.1017/S0267190525000029
[115]
Mizumoto, A. (2025). Automated analysis of common errors in L2 learner production: Prototype web application development. Studies in Second Language Acquisition. [Postprint] https://www.iris-database.org/details/eFPsq-2pGp6
[114]
Sun, A. X., & Mizumoto, A. (2025). Learner’s attitudes, styles, strategies and behaviours in data-driven learning. In L. McCallum & D. Tafazoli (Eds.), The Palgrave Encyclopedia of Computer-Assisted Language Learning. Palgrave. https://doi.org/10.1007/978-3-031-51447-0_148-1
[113]
Sun, A. X., & Mizumoto, A. (2025). Metacognition and data-driven learning. In L. McCallum & D. Tafazoli (Eds.), The Palgrave Encyclopedia of Computer-Assisted Language Learning. Palgrave. https://doi.org/10.1007/978-3-031-51447-0_85-1
[112]
水本 篤 (2025). AIとライティング教育―英語ライティング教育における生成AIの活用と課題―. 李 在鎬・青山玲二郎(編著)『AIで言語教育は終わるのか?深まる外国語の教え方と学び方』(第8章) くろしお出版. [Preprint] https://mizumot.com/files/AI_L2writing.pdf
[111]
Mizumoto. A., & Teng, M. F. (2025). Large language models fall short in classifying learners’ open-ended responses. Research Methods in Applied Linguistics, 4(2), 100210. https://doi.org/10.1016/j.rmal.2025.100210 [Postprint] https://www.iris-database.org/details/Qnxrj-VeVUu
[110]
Sun, A. X., & Mizumoto, A. (2025). Exploring the barriers to data-driven learning in the classroom: A systematic qualitative synthesis. Applied Corpus Linguistics, 5(2), 100126. https://doi.org/10.1016/j.acorp.2025.100126
[109]
Mizumoto, A. (2025). The anatomy of word lists in New Word Level Checker: Description and comparison. In F. M. Teng, A. Kukulska-Hulme, & J. G. Wu (Eds.), Theory and practice in vocabulary research in digital environments. Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9781003367543-11/anatomy-word-lists-new-word-level-checker-atsushi-mizumoto

2024

[108]
Huang, J., & Mizumoto, A. (2024). Examining the effects of the L2 learning experience on the ideal L2 self and ought-to L2 self in a Japanese university context. International Journal of Applied Linguistics, 35(2), 745–755. https://doi.org/10.1111/ijal.12659 [Postprint] Postprint
[107]
Huang, J., & Mizumoto, A. (2024). The effects of generative AI usage in EFL classrooms on the L2 motivational self system. Education and Information Technologies. https://doi.org/10.1007/s10639-024-13071-6 [Postprint] https://doi.org/10.48316/GrDUz-5xLg1
[106]
Mizumoto, A., Yasuda, S., & Tamura, Y. (2024). Identifying ChatGPT-generated texts in EFL students’ writing: Through comparative analysis of linguistic fingerprints. Applied Corpus Linguistics, 4(3), 100106. https://doi.org/10.1016/j.acorp.2024.100106 [Postprint] https://www.iris-database.org/details/tRzxt-AJkvT
[105]
Huang, J., & Mizumoto, A. (2024). Examining the relationship between the L2 motivational self system and Technology Acceptance Model post ChatGPT introduction and utilization. Computers & Education: Artificial Intelligence, 7, 100302. https://doi.org/10.1016/j.caeai.2024.100302
[104]
Mizumoto, A. (2024). Developing and disseminating data analysis tools for open science. In L. Plonsky (Ed.), Open Science in Applied Linguistics (pp. 121–131). Applied Linguistics Press. https://www.appliedlinguisticspress.org/home/catalog/plonsky_2024
[103]
Allen, T. J., & Mizumoto, A. (2024). ChatGPT over my friends: Japanese EFL learners’ preferences for editing and proofreading strategies. RELC Journal. https://doi.org/10.1177/00336882241262533 [Postprint] https://www.iris-database.org/details/JHNdV-atG6s
[102]
Sasaki, M., Mizumoto, A., & Murakami, A. (2024). Developmental trajectories of multicompetence writers: An ecological-historical approach to L1/L2 writing abilities and L2 proficiency. Journal of the European Second Language Association, 8(1), 114–130. https://doi.org/10.22599/jesla.109
[101]
Mizumoto, A., Shintani, N., Sasaki, M., & Teng, M. F. (2024). Testing the viability of ChatGPT as a companion in L2 writing accuracy assessment. Research Methods in Applied Linguistics, 3(2), 100116. https://doi.org/10.1016/j.rmal.2024.100116
[100]
Alamer, A., Mizumoto, A., Teng, M. F. (2024). Revisiting the construct validity of Self-regulating Capacity in Vocabulary Learning Scale: The confirmatory composite analysis (CCA) approach. Applied Linguistics, 46(2), 230–247. https://doi.org/10.1093/applin/amae023 [Postprint] Postprint
[99]
水本 篤 (2024). AIのある英語教育・研究: Let there be AI! KELESジャーナル, 9, 52–58. https://doi.org/10.18989/keles.9.0_52
[98]
Teng, F. M., Mizumoto, A., & Takeuchi, O. (2024). Understanding growth mindset, self-regulated vocabulary learning, and vocabulary knowledge. System, 122, 103255. https://doi.org/10.1016/j.system.2024.103255 [Postprint] https://mizumot.com/files/GrowthMindset_System.pdf
[97]
水本 篤 (2024). 生成型AIと語学教育. 『日本語学』(2024年3月号), 43(1), 126–132.
[96]
Sasaki, M., Mizumoto, A., & Matsuda, P. K. (2024). Machine translation as feedback on L2 Writing. International Review of Applied Linguistics in Language Teaching. https://doi.org/10.1515/iral-2023-0223
[95]
Yabukoshi, T., & Mizumoto, A. (2024). University EFL learners’ use of technology and their perceived difficulties in academic writing. LET Kansai Chapter Collected Papers, 22, 117–129. https://doi.org/10.50924/letkansai.22.0_117
[94]
Teng, F., & Mizumoto, A. (2024). Developing and validating a growth mindset scale in vocabulary learning. In A. Leis, Å. Haukås, N. Lou, & S. Nakamura (Eds.), Mindsets in language education. (pp. 17–35). Multilingual Matters. https://www.multilingual-matters.com/page/detail/Mindsets-in-Language-Education/?k=9781800418301 [Postprint] Postprint
[93]
Teng, F., & Mizumoto, A. (2024). Validation of metacognitive knowledge in vocabulary learning and its predictive effects on incidental vocabulary learning from reading. International Review of Applied Linguistics in Language Teaching, 2024. https://doi.org/10.1515/iral-2023-0294

2023

[92]
Hiratsuka, T., & Mizumoto, A. (2023). Exploratory-talk instruction on EFL group discussion. Explorations in Teacher Development, 29(2), 13–20. https://td.jalt.org/wp-content/uploads/2023/12/Hiratsuka_Mizumoto_2023-ETD292.pdf
[91]
Mizumoto, A. (2023). Data-driven learning meets generative AI: Introducing the framework of metacognitive resource use. Applied Corpus Linguistics, 3(3), 100074. https://doi.org/10.1016/j.acorp.2023.100074
[90]
Teng, F., Huang, Y., & Mizumoto, A. (2023). Incidental vocabulary learning through word-focused exercises: The association with vocabulary learning strategies. Asian Journal of English Language Teaching, 32(1), 29–62. https://cup.cuhk.edu.hk/image/catalog/journal/jpreview/AJELT32(1)_29-62_full.pdf
[89]
Mizumoto, A., & Watari, Y. (2023). Identifying key grammatical errors of Japanese English as a foreign language learners in a learner corpus: Toward focused grammar instruction with data-driven learning. Asia Pacific Journal of Corpus Research, 4(1), 25–42. https://doi.org/10.22925/apjcr.2023.4.1.25
[88]
水本 篤 (2023). 生成系AIは英語教育研究をどう変えるのか?. 英語教育2023年8月別冊, 72(6), 61–63.
[87]
水本 篤 (2023). 量的手法のさまざまな展開. 竹内理・水本篤(編著)『外国語教育研究ハンドブック【増補版】―研究手法のより良い理解のために―』松柏社. [Postprint] https://mizumot.com/files/Handbook2023Chapter25.pdf
[86]
Murata-Kobayashi, N., Suzuki, K., Morita, Y., Minobe, H., Mizumoto, A., & Seto, S. (2023). Exploring the benefits of full-time hospital facility dogs working with nurse handlers in a children’s hospital. PLOS ONE, 18(5), e0285768. https://doi.org/10.1371/journal.pone.0285768
[85]
Teng, F., & Mizumoto, A. (2023). The role of spoken vocabulary knowledge in language minority students’ incidental vocabulary learning from captioned television. Australian Review of Applied Linguistics, 46(2), 253–278. https://doi.org/10.1075/aral.22033.ten
[84]
Mizumoto, A., & Eguchi, M. (2023). Exploring the potential of using an AI language model for automated essay scoring. Research Methods in Applied Linguistics, 2(2), 100050. https://doi.org/10.1016/j.rmal.2023.100050 [Postprint] https://osf.io/2uahv_v1
[83]
Mizumoto, A. (2023). Calculating the relative importance of multiple regression predictor variables using dominance analysis and random forests. Language Learning, 73(1), 161–196. https://doi.org/10.1111/lang.12518 [Postprint] https://osf.io/w8nb3_v1

2022

[82]
Sawaguchi, R., & Mizumoto, A. (2022). Exploring the use of make + noun collocations by Japanese EFL learners through a bilingual essay corpus. Corpora, 17(S1), 61–77. https://doi.org/10.3366/cor.2022.0247
[81]
In'nami, Y., Mizumoto, A., Plonsky, L., & Koizumi, R. (2022). Promoting computationally reproducible research in applied linguistics: Recommended practices and considerations. Research Methods in Applied Linguistics, 1(3), 100030. https://doi.org/10.1016/j.rmal.2022.100030 [Postprint] https://osf.io/drw8s/
[80]
水本 篤 (2022). New Word Level Checker の概要. 外国語教育メディア学会 (LET) 関西支部メソドロジー研究部会報告論集, 12, 1–24. https://doi.org/10.31219/osf.io/whr9a

2021

[79]
Mizumoto, A., Pinchbeck, G. G., & McLean, S. (2021). Comparisons of word lists on New Word Level Checker. Vocabulary Learning and Instruction, 10(2), 30–41. https://doi.org/10.7820/vli.v10.2.mizumoto

2020

[78]
水本 篤 (2020). オンライン語彙難易度解析プログラムNew Word Level Checkerの開発と利用方法. 英語教育(2020年10月号), 69(7), 86–87.
[77]
小林雄一郎,濱田 彰,水本 篤 (2020). Rによる教育データ分析入門. オーム社.
[76]
Mizumoto, A., Plonsky, L., & Egbert, J. (2020). Meta-analyzing corpus linguistic research. In S. Th. Gries & M. Paquot (Eds.), A practical handbook of corpus linguistics. (pp. 663-688). Springer. https://doi.org/10.1007/978-3-030-46216-1_27
[75]
Larson-Hall, J., & Mizumoto, A. (2020). Using statistical software for data analysis (R, SPSS). In J. McKinley & H. Rose (Eds.), Routledge handbook of research methods in applied linguistics (pp. 385–397). Routledge.

2019

[74]
Mizumoto, A., Sasao, Y., & Webb, S. (2019). Developing and evaluating a computerized adaptive testing version of the Word Part Levels Test. Language Testing, 36(1), 101–123. https://doi.org/10.1177/0265532217725776 [Postprint] https://mizumot.com/files/cat-wplt.pdf
[73]
水本 篤 (2019). ストラテジー研究の方法. 英語教育(2019年6月号), 68(3), 14–15.

2018

[72]
Mizumoto, A. (2018). On questionnaire use in language learning strategies research. The Journal of Asia TEFL, 15, 184–192. https://doi.org/10.18823/asiatefl.2018.15.1.12.184
[71]
Sasaki, M., Mizumoto, A., & Murakami, A. (2018). Developmental trajectories in L2 writing strategy use: A self-regulation perspective. The Modern Language Journal, 102(2), 292–309. https://doi.org/10.1111/modl.12469
[70]
Mizumoto, A., & Takeuchi, O. (2018). Modeling a prototypical use of language learning strategies: Decision tree-based methods in multiple contexts. In R. L. Oxford & C. M. Amerstorfer (Eds.), Language learning strategies and individual learner characteristics: Situating strategy use in diverse contexts. (pp. 99–122). Bloomsbury. [Postprint] https://www.mizumot.com/files/Tree_LLS.pdf

2017

[69]
Yashima, T., Nishida, R., & Mizumoto, A. (2017). Influence of learner beliefs and gender on the motivating power of L2 selves. The Modern Language Journal, 101(4), 691–711. https://doi.org/10.1111/modl.12430
[68]
Mizumoto, A., Hamatani, S., & Imao, Y. (2017). Applying the bundle-move connection approach to the development of an online writing support tool for research articles. Language Learning, 67(4), 885–921. https://doi.org/10.1111/lang.12250 [Postprint] https://www.mizumot.com/files/LL-AWSuM.pdf
[67]
Mizumoto, A. (2017). Initial evaluation of AWSuM: A pilot study. Vocabulary Learning and Instruction, 6(2), 46–51. https://doi.org/10.7820/vli.v06.2.Mizumoto
[66]
水本 篤(編著) (2017). ICTを活用した英語アカデミック・ライティング指導―支援ツールの開発と実践―. 金星堂. https://kansai-u.repo.nii.ac.jp/records/705
[65]
水本 篤 (2017). 英語学術論文作成支援ツールAWSuM開発における理論的枠組み. 野口ジュディー津多江教授退職・古稀記念論文集編集委員会(編)『応用言語学の最前線ー言語教育の現在と未来ー』(pp. 132–144). 金星堂
[64]
水本 篤 (2017). 語彙学習方略―理論と実践―. KELESジャーナル, 2, 44–49. https://doi.org/10.18989/keles.2.0_44
[63]
水本 篤 (2017). 語彙増に向けた語彙のテスト・評価改善の可能性. 英語教育(2017年2月号), 65(12), 28–29.
[62]
水本 篤, 脇田貴文, 名部井敏代 (2017). 関西大学英語入試問題データの分析―テスト理論の活用を目指して―. 日本分類学会誌「分類の理論と応用」, 6(1), 21–29. https://mizumot.com/files/KU-EE.pdf

2016

[61]
Mizumoto, A. (2016). Multilevel analysis. 20th Anniversary Special Issue of JLTA Journal, 236–239. https://mizumot.com/files/MultilevelAnalysis.pdf
[60]
Mizumoto, A., & Takeuchi, O. (2016). Examining the effectiveness of explicit instruction of vocabulary learning strategies with Japanese EFL university students (Reprint of article published in 2009). In S. Webb (Ed.), Vocabulary. (Vol. 3, Chapter 9). Routledge. https://www.routledge.com/Vocabulary/Webb/p/book/9781138838604
[59]
Mizumoto, A., & Chujo, K. (2016). Who is data-driven learning for? Challenging the monolithic view of its relationship with learning styles. System, 61, 55–64. https://doi.org/10.1016/j.system.2016.07.010 [Postprint] https://mizumot.com/files/DDL-Style.pdf
[58]
Mizumoto, A. (2016). Introducing Kyoto Appeal: Issues in and implications of using four-skills proficiency tests as entrance examinations in Japan. British Council New Directions in Language Assessment: JASELE Journal Special Edition, 59–68. https://mizumot.com/files/KyotoAppeal.pdf
[57]
中條清美, 水本 篤, 西垣知佳子, 内堀朝子, 横田賢司, キャサリン・オヒガン (2016). DDL実践を評価するためのテストと質問紙の開発. 日本大学生産工学部研究報告B, 49, 45–61. https://www.cit.nihon-u.ac.jp/laboratorydata/kenkyu/publication/journal_b/b49.4.pdf
[56]
Chujo, K., Kobayashi, Y., Mizumoto, A., & Oghigian, K. (2016). Exploring the effectiveness of combined web-based corpus tools for beginner EFL DDL. Linguistics and Literature Studies, 4(4), 262–272. https://doi.org/10.13189/lls.2016.040404
[55]
草薙 邦広, 水本 篤, 竹内 理 (2016). 日本の外国語教育研究における効果量・検定力・標本サイズ:"Language Education & Technology" 掲載論文を対象にした事例分析. Language Education & Technology, 52, 105–131. https://doi.org/10.24539/let.52.0_105
[54]
Mizumoto, A., Ikeda. M., & Takeuchi, O. (2016). A comparison of cognitive processing during cloze and multiple-choice reading tests using brain activation. ARELE (Annual Review of English Language Education in Japan), 27, 65–80. https://doi.org/10.20581/arele.27.0_65
[53]
水本 篤, 浜谷 佐和子, 今尾 康裕 (2016). ムーブと語連鎖を融合させたアプローチによる応用言語学論文の分析—英語学術論文執筆支援ツール開発に向けて—. English Corpus Studies, 23, 21–32. https://mizumot.com/files/ecs2016.pdf
[52]
水本 篤 (2016). コンピュータ適応型語彙テストの開発と有用性の検証―オープンソースプラットフォームConcertoを利用して―. 石川有香・石川慎一郎・清水裕子・田畑智司・長 加奈子・前田忠彦(編著)『言語研究と量的アプローチ』(pp. 1–11). 金星堂. https://mizumot.com/files/CAT-VocSize.pdf
[51]
Kumazawa, T., Shizuka, T., Mochizuki, M., & Mizumoto, A. (2016). Validity argument for the VELC Test score interpretations and uses. Language Testing in Asia, 6(2). https://doi.org/10.1186/s40468-015-0023-3
[50]
Mizumoto. A., & Plonsky, L. (2016). R as a lingua franca: Advantages of using R for quantitative research in applied linguistics. Applied Linguistics, 37(2), 284–291. https://doi.org/10.1093/applin/amv025 [Postprint] https://mizumot.com/files/AL_R.pdf
[49]
Mizumoto, A., Chujo, K., & Yokota, K. (2016). Development of a scale to measure learners’ perceived preferences and benefits of data-driven learning. ReCALL, 28(2), 227–246. https://doi.org/10.1017/S0958344015000208 [Postprint] https://mizumot.com/files/ReCALL_DDL.pdf

2015

[48]
Kudo, Y., Mizumoto, A., & Kumazawa, T. (2015). Validation of a vocabulary learning strategy scale and its relationship to vocabulary level test scores. Asian Journal of English Language Teaching, 25, 81–111. https://mizumot.com/files/Kudo_etal_2015.pdf
[47]
水本 篤 (2015). LMS を利用した教育効果の測定. 大澤真也・中西大輔(編著)『eラーニングは教育を変えるか』(pp. 165–179). 海文堂. https://mizumot.com/files/ShudoLMS2015.pdf
[46]
Mizumoto, A., & Chujo, K. (2015). A meta-analysis of data-driven learning approach in the Japanese EFL classroom. English Corpus Studies, 22, 1–18. https://mizumot.com/files/JSSS2015.pdf
[45]
Mizumoto, A. (2015). Corpus-based analysis of lexical bundles: Its potential applications in English language teaching. Journal of the Japan Society for Speech Sciences, 16, 30–34. https://mizumot.com/files/ecs2015.pdf

2014

[44]
水本 篤, 染谷 泰正,山西 博之 (2014). 語彙学習を促進するブレンディッド・ラーニングの試み:Grammar & Vocabulary Development の理念とその効果に関する中間報告. 関西大学外国語学部紀要, 11, 71–92. https://www.kansai-u.ac.jp/fl/publication/pdf_department/11/06mizumoto.pdf
[43]
水本 篤 (2014). 測定された差の分析と解釈(第15章「統計的な分析結果の解釈の現状と展望」第2節)全国英語教育学会第40回研究大会記念特別誌『英語教育学の今—理論と実践の統合—』全国英語教育学会, 376–380. https://mizumot.com/files/JASELE40Ch15
[42]
水本 篤 (2014). コーパス活用のための統計処理. 赤野一郎・堀 正広・投野由紀夫(編著)『英語教師のためのコーパス活用ガイド』(pp. 200–215), 大修館書店.
[41]
Mizumoto, A., Urano, K., & Maeda, H. (2014). A systematic review of published articles in ARELE 1–24: Focusing on their themes, methods, and outcomes. ARELE (Annual Review of English Language Education in Japan), 25, 33–48. https://doi.org/10.20581/arele.25.0_33 [Postprint] https://mizumot.com/files/ARELE2014.pdf

2013

[40]
Mizumoto, A. (2013). Effects of self-regulated vocabulary learning process on self-efficacy. Innovation in Language Learning and Teaching, 7, 253–265. https://doi.org/10.1080/17501229.2013.836206 [Postprint] https://mizumot.com/files/ILLT2013.pdf
[39]
山西 博之, 水本 篤, 染谷 泰正 (2013). 関西大学バイリンガルエッセイコーパスプロジェクト―その概要と教育研究への応用に関する展望―. 関西大学外国語学部紀要, 9, 117–139. https://www.kansai-u.ac.jp/fl/publication/pdf_department/09/117yamanishi.pdf
[38]
Mizumoto, A. (2013). Enhancing self-efficacy in vocabulary learning: A self-regulated learning approach. Vocabulary Learning and Instruction, 2(1), 15–24. https://doi.org/10.7820/vli.v02.1.mizumoto
[37]
水本 篤 (2013). 英文解析プログラムから得られる各種指標を使ったテキスト難易度の推定―教材作成への適用可能性―. 外国語教育メディア学会(LET) 関西支部メソドロジー研究部会2012年度報告論集, 142–150. https://www.mizumot.com/method/2012-11_Mizumoto.pdf

2012

[36]
Mizumoto, A. (2012). Exploring the effects of self-efficacy on vocabulary learning strategies. Studies in Self-Access Learning Journal, 3(4), 423–437. https://sisaljournal.org/archives/dec12/mizumoto/
[35]
Takeuchi, O., Ikeda, M., & Mizumoto, A. (2012). The cerebral basis for language learner strategies: A near-infrared spectroscopy study. Reading in a Foreign Language, 24(2), 136–157. http://hdl.handle.net/10125/66861
[34]
Takeuchi, O., Ikeda, M., & Mizumoto, A. (2012). Reading aloud activity in L2 and cerebral activation. RELC Journal, 43, 151–167. https://doi.org/10.1177/0033688212450496 [Postprint] https://mizumot.com/files/RELC2012.pdf
[33]
竹内 理, 水本 篤 (2012). 外国語教育研究ハンドブック—研究手法のより良い理解のために—. 松柏社. https://mizumot.com/handbook/
[32]
水本 篤 (2012). 質問紙調査における相関係数の解釈について. 外国語教育メディア学会(LET) 関西支部メソドロジー研究部会2011年度報告論集, 63. https://www.mizumot.com/method/2011-06_Mizumoto.pdf
[31]
Mizumoto, A., & Takeuchi, O. (2012). Adaptation and validation of Self-regulating Capacity in Vocabulary Learning Scale. Applied Linguistics, 33, 83–91. https://doi.org/10.1093/applin/amr044 [Postprint] https://mizumot.com/files/AL2012.pdf

2011

[30]
水本 篤 (2011). 自己調整語彙学習における自己効力感の影響. 関西大学外国語学部紀要, 5, 35–56. http://www.kansai-u.ac.jp/fl/publication/pdf_department/05/035mizumoto.pdf
[29]
水本 篤, 竹内 理 (2011). 効果量と検定力分析入門 ―統計的検定を正しく使うために―. より良い外国語教育のための方法―外国語教育メディア学会 (LET) 関西支部メソドロジー研究部会2010年度報告論集―, 47–73. https://www.mizumot.com/files/metho2010.pdf

2010

[28]
水本 篤 (2010). 主成分分析:データの情報を圧縮する. 石川慎一郎・前田忠彦・山崎誠(編)『言語研究のための統計入門』(pp. 193–217). くろしお出版.
[27]
Mizumoto, A. (2010). Exploring the art of vocabulary learning strategies: A closer look at Japanese EFL university students. Kinseido. https://www.mizumot.com/files/book2010.pdf
[26]
水本 篤 (2010). サンプルサイズが小さい場合の統計的検定の比較―コーパス言語学・外国語教育学への適用―. 統計数理研究所共同研究リポート238 言語コーパス分析における数理データの統計的処理手法の検討, 1–14. https://www.mizumot.com/files/permutation.pdf
[25]
小山 由紀江, 水本 篤 (2010). 単語連鎖にみる科学技術分野と他分野の英語表現比較. 統計数理研究所共同研究リポート239 ESPコーパスからの特徴表現の抽出, 1–12. https://www.mizumot.com/files/LexBundle.pdf

2009

[24]
Mizumoto, A., & Takeuchi, O. (2009). A close look at the relationship between vocabulary learning strategies and the TOEIC score. TOEIC Research Report No. 4. The Institute for International Business Communication. https://www.mizumot.com/files/TOEIC_Report4.pd
[23]
Mizumoto, A., & Takeuchi, O. (2009). Comparing frequency and trueness scale descriptors in a Likert scale questionnaire on language learning strategies. JLTA Journal, 12, 116–136. https://www.mizumot.com/files/JLTA2009_Likert.pdf
[22]
Mizumoto, A., & Takeuchi, O. (2009). Examining the effectiveness of explicit instruction of vocabulary learning strategies with Japanese EFL university students. Language Teaching Research, 13, 425–449. https://doi.org/10.1177/1362168809341511 [Postprint] https://www.mizumot.com/files/LTR13-4_Mizumoto-Takeuchi.pdf
[21]
水本 篤 (2009). 複数の項目やテストにおける検定の多重性―モンテカルロ・シミュレーションによる検証―. Language Education & Technology, 46, 1–19. https://www.mizumot.com/files/LET2009.pdf
[20]
水本 篤 (2009). コーパス言語学研究における多変量解析手法の比較―主成分分析 vs. コレスポンデンス分析―. 統計数理研究所共同研究リポート23 コーパス言語研究における量的データ処理のための統計手法の概観, 53–64. https://www.mizumot.com/files/2009_corpus2.pdf
[19]
水本 篤, 野口 ジュディー (2009). 多変量解析を用いたPERCコーパスの領域分類. 統計数理研究所共同研究リポート232 コーパス言語研究における量的データ処理のための統計手法の概観, 85–106. https://www.mizumot.com/files/2009_corpus1.pdf
[18]
水本 篤, 東 淳一 (2009). 大学授業における教員のメディア利用と授業評価の関係. 日本教育工学会論文誌, 32, 17–20. https://ci.nii.ac.jp/naid/110007023981
[17]
西出 公之, 水本 篤 (2009). 英単語8000語についての親密度測定の試み. 都留文科大学大学院紀要, 13, 57–92. http://trail.tsuru.ac.jp/dspace/handle/trair/180

2008

[16]
Mizumoto, A., & Shimamoto, T. (2008). A comparison of aural and written vocabulary size of Japanese EFL university learner. Language Education & Technology, 45, 35–52. https://www.mizumot.com/files/LET2008.pdf
[15]
水本 篤 (2008). 自由英作文における評定者評価の種類と信頼性. 統計数理研究所共同研究リポート215 学習者コーパスの解析に基づく客観的作文評価指標の検討, 43–49. https://www.mizumot.com/files/GeneralizabilityTheory.pdf
[14]
水本 篤 (2008). 自由英作文における語彙の統計指標と評定者の総合的評価の関係. 統計数理研究所共同研究リポート215 学習者コーパスの解析に基づく客観的作文評価指標の検討, 15–28. https://www.mizumot.com/files/essay-index.pdf
[13]
水本 篤, 竹内 理 (2008). 研究論文における効果量の報告のために―基礎的概念と注意点―. 関西英語教育学会紀要 英語教育研究, 31, 57–66. https://www.mizumot.com/files/EffectSize_KELES31.pdf
[12]
Mizumoto, A., & Takeuchi, O. (2008). Exploring the driving forces behind TOEIC scores: Focusing on vocabulary learning strategies, motivation, and study time. JACET Journal, 46, 17–32. https://ci.nii.ac.jp/naid/110007137438
[11]
西出 公之, 水本 篤 (2008). 「習得特性」に基づく語彙リストの可能性. 都留文科大学大学院紀要, 12, 31–46. https://cir.nii.ac.jp/crid/1520290883065811712
[10]
西出 公之, 水本 篤, 前田 浩 (2008). 「語彙サイズテスト」による経年的語彙数推定の試み. 都留文科大学研究紀要, 67, 47–58.

2007

[9]
西出 公之, 水本 篤 (2007). 「語彙サイズテスト」の語彙表とサンプリング. 都留文科大学大学院紀要, 11, 21–31.
[8]
西出 公之, 水本 篤, 前田 浩 (2007). 「語彙サイズテスト」による語彙数推定の試み. 都留文科大学研究紀要, 65, 61–77. https://cir.nii.ac.jp/crid/1520009408001974400
[7]
水本 篤 (2007). 主成分分析を用いた学習語彙表の精緻化の試み. 統計数理研究所共同研究 リポート199 日英語の基本語抽出における統計手法の研究, 15–26. https://www.mizumot.com/files/WordlistPCA.pdf
[6]
水本 篤 (2007). より良い学習語彙表の開発にむけた統計的手法の検討. 統計数理研究所共同研究リポート199 日英語の基本語抽出における統計手法の研究, 1–14. https://www.mizumot.com/files/WordlistDevelopment.pdf
[5]
Mizumoto, A. (2007). The role of learning styles in vocabulary learning strategies. 『英語授業実践学の展開』(pp. 229–244). 三省堂. https://www.mizumot.com/files/style.pdf
[4]
水本 篤 (2007). TOEFL語彙の語彙レベル, 真正性, 特徴の検証. 言語文化学会論集, 27, 3–15. https://www.mizumot.com/files/TOEFLvoc.pdf

2006

[3]
水本 篤 (2006). 語彙サイズテストは何を測っているのか?―語彙サイズテストの開発における問題点―. 統計数理研究所共同研究レポート190 言語コーパス解析における共起語 検出のための統計手法の比較研究, 71–80. https://www.mizumot.com/files/VocSizeMeasure.pdf
[2]
水本 篤 (2006). 大学生の語彙学習方略使用と学習成果の関係―人文系女子大学生を対象とした調査―. 甲南女子大学 研究紀要 文学・文化編, 42, 93–107. https://ci.nii.ac.jp/naid/110004868193

2004

[1]
水本 篤 (2004). JACET8000とTOEICの相関性:TOEICミニコーパスを使っての数量的検討.『JACET8000活用事例集』大学英語教育学会(JACET)基本語改定委員会, 60–61. https://www.mizumot.com/files/J8_use.pdf