Yo In’nami

1.6k total citations · 1 hit paper
38 papers, 953 citations indexed

About

Yo In’nami is a scholar working on Language and Linguistics, Developmental and Educational Psychology and Literature and Literary Theory. According to data from OpenAlex, Yo In’nami has authored 38 papers receiving a total of 953 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Language and Linguistics, 18 papers in Developmental and Educational Psychology and 10 papers in Literature and Literary Theory. Recurrent topics in Yo In’nami's work include EFL/ESL Teaching and Learning (22 papers), Second Language Acquisition and Learning (10 papers) and Second Language Learning and Teaching (9 papers). Yo In’nami is often cited by papers focused on EFL/ESL Teaching and Learning (22 papers), Second Language Acquisition and Learning (10 papers) and Second Language Learning and Teaching (9 papers). Yo In’nami collaborates with scholars based in Japan, United Kingdom and United States. Yo In’nami's co-authors include Rie Koizumi, Mariko Abe, Kazuya Saito, Jean‐Marc Dewaele, Phil Hiver, Ali H. Al‐Hoorie, Luke Plonsky, Atsushi Mizumoto, Keita Nakamura and Pavel Trofimovich and has published in prestigious journals such as SHILAP Revista de lepidopterología, Frontiers in Psychology and TESOL Quarterly.

In The Last Decade

Yo In’nami

35 papers receiving 889 citations

Hit Papers

Motivation, Emotion, Learning Experience, and Second Lang... 2018 2026 2020 2023 2018 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yo In’nami Japan 13 519 406 224 190 184 38 953
Wen‐Ta Tseng Taiwan 12 567 1.1× 658 1.6× 261 1.2× 340 1.8× 137 0.7× 36 1.2k
Jenifer Larson‐Hall Japan 12 692 1.3× 575 1.4× 376 1.7× 218 1.1× 57 0.3× 25 1.3k
Rie Koizumi Japan 13 334 0.6× 358 0.9× 161 0.7× 152 0.8× 31 0.2× 59 703
Joseph P. Vitta Japan 11 236 0.5× 301 0.7× 120 0.5× 243 1.3× 172 0.9× 29 706
Patricia Dunkel United States 16 761 1.5× 439 1.1× 334 1.5× 244 1.3× 69 0.4× 37 1.1k
Mansoor Tavakoli Iran 18 673 1.3× 530 1.3× 434 1.9× 413 2.2× 146 0.8× 114 1.2k
Aek Phakiti Australia 17 634 1.2× 611 1.5× 432 1.9× 565 3.0× 63 0.3× 27 1.3k
Anne Lazaraton United States 15 1.1k 2.1× 439 1.1× 635 2.8× 304 1.6× 44 0.2× 27 1.5k
Rüdiger Grotjahn Germany 11 305 0.6× 184 0.5× 147 0.7× 124 0.7× 54 0.3× 30 624
Albert Weideman South Africa 14 543 1.0× 261 0.6× 516 2.3× 239 1.3× 39 0.2× 70 968

Countries citing papers authored by Yo In’nami

Since Specialization
Citations

This map shows the geographic impact of Yo In’nami's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yo In’nami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yo In’nami more than expected).

Fields of papers citing papers by Yo In’nami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yo In’nami. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yo In’nami. The network helps show where Yo In’nami may publish in the future.

Co-authorship network of co-authors of Yo In’nami

This figure shows the co-authorship network connecting the top 25 collaborators of Yo In’nami. A scholar is included among the top collaborators of Yo In’nami based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yo In’nami. Yo In’nami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Al‐Hoorie, Ali H., Phil Hiver, & Yo In’nami. (2025). Looking beyond the L2 Motivational Self System. Studies in Second Language Acquisition. 47(4). 1193–1204.
2.
Saito, Kazuya, et al.. (2025). Disentangling the causal role of motivation, enjoyment, and anxiety in second language speech learning: A final report. Studies in Second Language Acquisition. 47(2). 461–487. 3 indexed citations
3.
Koizumi, Rie, et al.. (2024). Considerations to promote and accelerate Open Science: A response to Winke. Language Testing. 41(4). 892–897. 2 indexed citations
4.
Koizumi, Rie & Yo In’nami. (2023). Predicting functional adequacy from complexity, accuracy, and fluency of second-language picture-prompted speaking. System. 120. 103208–103208. 3 indexed citations
5.
Al‐Hoorie, Ali H., Phil Hiver, & Yo In’nami. (2023). The validation crisis in the L2 motivational self system tradition. Studies in Second Language Acquisition. 46(2). 307–329. 25 indexed citations
6.
Koizumi, Rie, et al.. (2022). Skill profiles of Japanese English learners and reasons for uneven patterns. Language Testing in Asia. 12(1). 4 indexed citations
7.
In’nami, Yo & Rie Koizumi. (2022). Another Generation of Fundamental Considerations in Language Assessment: A Festschrift in Honor of Lyle F. Bachman. Language Assessment Quarterly. 19(5). 547–551. 2 indexed citations
8.
In’nami, Yo, Mike W.‐L. Cheung, Rie Koizumi, & Matthew P. Wallace. (2022). Examining Second Language Listening and Metacognitive Awareness: A Meta‐Analytic Structural Equation Modeling Approach. Language Learning. 73(3). 759–798. 11 indexed citations
9.
Koizumi, Rie & Yo In’nami. (2022). Assessing Functional Adequacy Using Picture Description Tasks in Classroom-Based L2 Speaking Assessment. 25(0). 60–79. 1 indexed citations
10.
In’nami, Yo, Atsushi Mizumoto, Luke Plonsky, & Rie Koizumi. (2022). Promoting computationally reproducible research in applied linguistics: Recommended practices and considerations. Research Methods in Applied Linguistics. 1(3). 100030–100030. 24 indexed citations
11.
In’nami, Yo & Rie Koizumi. (2021). THE RELATIONSHIP BETWEEN L2 LISTENING AND METACOGNITIVE AWARENESS ACROSS LISTENING TESTS AND LEARNER SAMPLES. International Journal of Listening. 36(2). 100–117. 12 indexed citations
12.
In’nami, Yo, et al.. (2021). WORKING MEMORY CAPACITY AND L2 READING. Studies in Second Language Acquisition. 44(2). 381–406. 11 indexed citations
13.
Koizumi, Rie & Yo In’nami. (2020). Structural Equation Modeling of Vocabulary Size and Depth Using Conventional and Bayesian Methods. Frontiers in Psychology. 11. 618–618. 10 indexed citations
14.
Saito, Kazuya, Pavel Trofimovich, Mariko Abe, & Yo In’nami. (2020). Dunning-Kruger effect in second language speech learning: How does self perception align with other perception over time?. Learning and Individual Differences. 79. 101849–101849. 14 indexed citations
16.
In’nami, Yo, et al.. (2015). Relationships Between Strategy Use, Listening Proficiency Level, Task Type, and Scores in an L2 Listening Test. SHILAP Revista de lepidopterología. 18(2). 45–77. 6 indexed citations
17.
In’nami, Yo & Rie Koizumi. (2013). Review of Sample Size for Structural Equation Models in Second Language Testing and Learning Research: A Monte Carlo Approach. International Journal of Testing. 13(4). 329–353. 30 indexed citations
18.
Koizumi, Rie & Yo In’nami. (2012). Effects of text length on lexical diversity measures: Using short texts with less than 200 tokens. System. 40(4). 554–564. 62 indexed citations
19.
In’nami, Yo & Rie Koizumi. (2011). Structural Equation Modeling in Language Testing and Learning Research: A Review. Language Assessment Quarterly. 8(3). 250–276. 44 indexed citations
20.
In’nami, Yo & Rie Koizumi. (2010). Can Structural Equation Models in Second Language Testing and Learning Research be Successfully Replicated?. International Journal of Testing. 10(3). 262–273. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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