Current Perspectives on Intercultural and Global Competence offers a compelling exploration of the evolving landscape of intercultural and global competence through a variety of lenses.  This insightful book delves into the complexities of navigating the practical implications of getting along together across difference and similarity.   With collective contributions from scholars and practitioners worldwide, this book presents a diverse array of perspectives from different disciplines, contexts, languages, and cultures.  Through rich discussion and insights, contributors to this book  invite readers to engage in delving further into the complexities of the crucial understanding needed to thrive in today’s interconnected and yet often polarized world.  Editors Dr. Darla K. Deardorff is Founding President of the World Council on Intercultural and Global Competence. She is also the UNESCO Chair on Intercultural Competence at Stellenbosch University (South Africa) as well as appointed faculty at other universities in Japan, China, the US and Canada.  She has worked in the international education field for thirty years and  is the author/editor of 14 books and over 60 other publications including the seminal work on intercultural competence, Sage Handbook of Intercultural Competence as well as the open access UNESCO Manual on Developing Intercultural Competence: Story Circles. Regularly invited to speak around the world, she is working on the intersections of intercultural competence with peacebuilding, gender equality and climate action.  Mizuho Tatebayashi, a Japanese scholar-practitioner, who is enthusiastic about intercultural communication and international education. Her roots lie in Japan, yet she had the privilege to explore outside the country during her undergraduate years, where she discovered the transformative power of cross-cultural experiences. As a doctoral student in North Carolina State University's Educational Psychology program, her focus centers on the development of intercultural competence and fostering enriching learning environments. She currently serves as an Executive Fellow at the World Council on Intercultural and Global Competence. _________________________________________________ Download the complimentary eBook here _________________________________________________ Order print copies here

This book includes a unique module-based, self-driven professional development program that empowers scholars to deepen their understanding of the Society of Transnational Academic Researchers (STAR) vision while enhancing their research agenda and leadership skills. Through a blended learning approach, participants engage in immersive learning experiences, including self-paced online modules, workshops, mentoring sessions, and support hours, to acquire the knowledge, skills, and mindset necessary for their professional success. This program goes beyond traditional professional development by emphasizing the social impact and justice aspects of research and scholarship. Scholars examine systemic inequalities, challenge dominant narratives, and advocate for structural change in their communities. With a focus on equity, diversity, and inclusion, the program addresses the needs of marginalized communities, fostering a culture of learning and growth. Order print copies  here   || Download digital copies  here

Mixed Methods Research: AI-Augmented Design, Analysis, and Publishing is a practical and scholarly guide for doctoral students, faculty members, institutional researchers, and interdisciplinary scholars seeking to conduct rigorous mixed-methods studies. While grounded in education and the social sciences, it is relevant to researchers in health, policy, business, and STEM fields. The book provides a roadmap from research design to publication. It covers foundational mixed methods paradigms, core designs, integration strategies, and meta-inference development. It also demonstrates how AI tools such as ChatGPT, Google Gemini, and Microsoft Copilot can be used responsibly to support literature reviews, instrument design, data analysis preparation, writing, and revision without compromising rigor or ethics. Each chapter blends conceptual clarity, applied examples, and practical workflows suitable for doctoral courses, faculty development, and research teams. Key Features Rigorous Mixed Methods Framework Guidance on design selection, integration, joint displays, and defensible interpretation. Responsible AI Integration Structured use of AI tools across research phases with attention to ethics, bias, and transparency. From Research to Publication Strategies for manuscript development, journal targeting, and navigating peer review. CONTENTS CHAPTER 1  What Is Mixed Methods Research? Defining Mixed Methods Research Why Mixed Methods? Key Advantages of Conducting Mixed Methods Research Types of Mixed Methods Research Key Elements of Mixed Methods Research CHAPTER 2  AI and Philosophical Foundations of Mixed Methods Research Pragmatism as Methodological Foundation Critical Realism and Ontological Depth Transformative Paradigms and Justice-Centered Inquiry Integration as the Core of Mixed Methods Rethinking Mixed Methods in the Age of AI CHAPTER 3  Convergent Mixed Methods Design Definition and Purpose Key Procedures of the Convergent Mixed Methods Design Examples of Convergent Mixed Methods Design AI Applications in the Convergent Mixed Methods Design CHAPTER 4  Explanatory Sequential Mixed Methods Design Definition and Purpose Key Procedures of the Explanatory Sequential Design Examples of Explanatory Sequential Design AI Applications in the Explanatory Sequential Design CHAPTER 5  Exploratory Sequential Mixed Methods Design Definition and Purpose Key Procedures of the Exploratory Sequential Design Examples of Exploratory Sequential Design AI Applications in the Exploratory Sequential Design CHAPTER 6  AI-Augmented Mixed Methods Methodology Conceptual Foundations of AI-Augmented Mixed Methods AI in Instrument Development AI for Qualitative Coding Validation AI for Statistical Assumption Checking Bias Detection and Ethical Safeguards Prompt Engineering for Research Empirical Mini-Case Studies Reporting AI in Mixed Methods Publications CHAPTER 7  Advanced Integration, Joint Displays, and Meta-Inference What Is Integration in Mixed Methods? Timing, Weighting, and Connecting Data Strands Building Joint Displays Types of Joint Displays Handling Convergence and Divergence Constructing Defensible Meta-Inferences Weak vs. Strong Meta-Inference AI-Assisted Integration with Human Validation CHAPTER 8  Writing a Mixed Methods Dissertation Proposal Structuring a Mixed Methods Proposal Introduction Purpose Statement Research Questions Methodology Anticipated Results Table of Contents for a Mixed Methods Dissertation Proposal AI Applications in Crafting a Mixed Methods Proposal Sample Assignment: Writing a Mixed Methods Research Proposal BIBLIOGRAPHY AND RESOURCES  Mixed Methods Books Mixed Methods Journals Prompts for AI Tools Research and Literature Review Tools Writing Tools