Annals of Mixed Methods Research
Online ISSN : 2436-8407
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Displaying 1-3 of 3 articles from this issue
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  • A Systematic Learning Approach Informed by the 'Shuhari' Model
    Hisako Kakai, Tomoko Kamei, Manami Nozaki, Miwako Fukuda, Tomomi Suda, ...
    2025 Volume 4 Issue 1 Pages 350-365
    Published: 2025
    Released on J-STAGE: June 07, 2025
    JOURNAL OPEN ACCESS

    This paper introduces an educational tool titled Mixed Methods Research for Nursing Researchers, which was developed to address the challenges associated with learning and implementing mixed methods research. Based on the experiences of nursing researchers in Japan and abroad, this paper examines the background, objectives, structure, and significance of the tool. This e-learning program was developed primarily by board members of the Japan Society for Mixed Methods Research (JSMMR) and was designed as an educational tool for systematically learning mixed methods research. It incorporates the traditional Japanese learning model of "Shu-Ha-Ri," allowing learners to progress through structured, step-by-step learning based on their proficiency levels. At the 10th Annual JSMMR Conference Open Forum in 2024, representatives of the program developers and test users participated in discussions, sharing their experiences with mixed methods research while evaluating the usability of the program. This paper reports on the forum’s discussions and examines the possible impact of this e-learning program on the learning process of mixed methods research. Through this program, we aim to enable learners to actively develop research designs suited to their research objectives and effectively apply mixed methods research in practice.

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  • Yoshitaka Otsuka
    2025 Volume 4 Issue 1 Pages 366-381
    Published: 2025
    Released on J-STAGE: June 07, 2025
    JOURNAL OPEN ACCESS

    This study proposes a novel mixed method research approach that integrates the epistemology and methodology of Bayesian statistics (including application in AI). To reframe each research paradigm: quantitative research (frequency theory) is positioned as hypothesis testing by deduction (theory driven); qualitative research as hypothesis generating via abduction and self-validation through qualitative induction (data interactive); and Bayesian statistics as hypothesis selection through quantitative induction (data driven). The proposed mixed method approach involves the following steps: 1) Designing the overall research framework and building the database using qualitative research; 2) Applying Bayesian statistics to the database to identify the most plausible model and narrow down key hypotheses and variables; 3) Testing these key hypotheses through quantitative research and summarizing the overall conclusions; 4) Feeding significant findings back into the research project to iteratively refine and restart the process.

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  • Yoko Kawamura
    2025 Volume 4 Issue 1 Pages 382-395
    Published: 2025
    Released on J-STAGE: June 07, 2025
    JOURNAL OPEN ACCESS

    A research project funded by Kaken, the Grant-in-Aid for Scientific Research, and conducted by board directors from the Japan Society for Mixed Methods Research (JSMMR), has successfully developed a comprehensive e-learning program for Mixed Methods Research (MMR) focusing on nursing researchers. As a result, we have publicly begun offering the program in spring 2025. In this academic journal published by JSMMR, we have launched the series, “Method Cafe: Mixed Methods Dialogues in Relay,” to provide materials for learning MMR that support the e-learning content further, such as providing opportunities to explain research designs.

    As the first in the series, this paper aims to deepen readers' understanding by introducing two mixed-method research studies that also applied the positive deviance (PD) approach and examining and explaining them from the perspectives of the PD approach and MMR.

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