Heewon Chang | Eastern University (original) (raw)
Books by Heewon Chang
Papers by Heewon Chang
Routledge eBooks, Jun 16, 2016
This stage will: • Explain different types of qualitative data analysis • Explain different types... more This stage will: • Explain different types of qualitative data analysis • Explain different types of quantitative data analysis • Help you to interpret the results of your data analysis Once you have decided on your method of data collection and have gathered all of the data you need, you need to decide how to analyze and interpret your data. This can be done in a variety of ways, and will depend on whether you used qualitative, quantitative, or mixed methods of data collection. How Do I Analyze and Interpret Qualitative Data? The first thing to do is to read through all of your textual material, listen to all of your audio material, and look carefully at all of your visual material. You have to have a holistic sense of what you have and you have to form some preliminary impression as to what it all means. "Preliminary" is emphasized here because as you go through the materials in any systematic way, your first impressions must be changed if necessary. We can think of organizing your analysis and interpretation in terms of: • Ways of measuring from your qualitative material: This may be, and mostly is, nothing more complicated than sorting things into kinds so the measurement is nominal. • Establishing meaning: We have "patterning" as one style and "understanding" as another. Of course we tend to do both as we work through the materials. Some formal methods have both approaches built into them. You may organize your analysis using one of these methods. Or you may choose to use one or more in combination. However, when using multiple methods, careful consideration must be given to integrating the resulting disparate elements into an overall synthesis. Classification involves sorting things into kinds. This can be a process of classifying and naming elements as a measurement device. Or it can involve the development of a system of concepts. It can be both. Induction is a more or less formal development of hypotheses on the basis of elements of the material which are tested against other elements. Content analysis involves elements in the material being counted in order to generate a set of numbers for statistical analyses. This can be very simple. For example, the number of times an issue is identified in a set of interviews can be counted and reported on as a frequency count. More complex statistical approaches are appropriate if there are a very large number of cases. Qualitative comparative analysis (QCA) is the systematic description of cases, in terms of the presence or SAGE 2017 SAGE Publications, Ltd. All Rights Reserved.
Handbook of Autoethnography
International Journal of Multicultural Education, 2017
In this introduction to the special issue of IJME, we highlight critical autoethnography’s potent... more In this introduction to the special issue of IJME, we highlight critical autoethnography’s potential for connecting the deeply personal experiences of race, gender, culture, language, sexuality, and other aspects of marginalization and privilege to the broader context of education in society. We discuss critical autoethnography as an interdisciplinary, blurred genre that transforms to fit the academic backgrounds, interests, and critical orientations of its authors. All contributors to this special issue situate their take on the genre in relevant literature and provide sociocultural critique in explicit and implicit ways.
Eileen R. O'Shea is a contributing co-author (with Roben Torosyan and Betsy Bowen), " Sp... more Eileen R. O'Shea is a contributing co-author (with Roben Torosyan and Betsy Bowen), " Spirituality & Professional Collegiality: Espirit de 'Core'", Chapter 5, pp. 87-107. Book description: This collection of articles explores how a wide range of academics-- diverse in location, rank and discipline-- understand and express how they deal with spirituality in their professional lives and how they integrate
Anthropology & Education Quarterly, 2013
Routledge eBooks, Jun 16, 2016
This stage will: • Explain different types of qualitative data analysis • Explain different types... more This stage will: • Explain different types of qualitative data analysis • Explain different types of quantitative data analysis • Help you to interpret the results of your data analysis Once you have decided on your method of data collection and have gathered all of the data you need, you need to decide how to analyze and interpret your data. This can be done in a variety of ways, and will depend on whether you used qualitative, quantitative, or mixed methods of data collection. How Do I Analyze and Interpret Qualitative Data? The first thing to do is to read through all of your textual material, listen to all of your audio material, and look carefully at all of your visual material. You have to have a holistic sense of what you have and you have to form some preliminary impression as to what it all means. "Preliminary" is emphasized here because as you go through the materials in any systematic way, your first impressions must be changed if necessary. We can think of organizing your analysis and interpretation in terms of: • Ways of measuring from your qualitative material: This may be, and mostly is, nothing more complicated than sorting things into kinds so the measurement is nominal. • Establishing meaning: We have "patterning" as one style and "understanding" as another. Of course we tend to do both as we work through the materials. Some formal methods have both approaches built into them. You may organize your analysis using one of these methods. Or you may choose to use one or more in combination. However, when using multiple methods, careful consideration must be given to integrating the resulting disparate elements into an overall synthesis. Classification involves sorting things into kinds. This can be a process of classifying and naming elements as a measurement device. Or it can involve the development of a system of concepts. It can be both. Induction is a more or less formal development of hypotheses on the basis of elements of the material which are tested against other elements. Content analysis involves elements in the material being counted in order to generate a set of numbers for statistical analyses. This can be very simple. For example, the number of times an issue is identified in a set of interviews can be counted and reported on as a frequency count. More complex statistical approaches are appropriate if there are a very large number of cases. Qualitative comparative analysis (QCA) is the systematic description of cases, in terms of the presence or SAGE 2017 SAGE Publications, Ltd. All Rights Reserved.
Handbook of Autoethnography
International Journal of Multicultural Education, 2017
In this introduction to the special issue of IJME, we highlight critical autoethnography’s potent... more In this introduction to the special issue of IJME, we highlight critical autoethnography’s potential for connecting the deeply personal experiences of race, gender, culture, language, sexuality, and other aspects of marginalization and privilege to the broader context of education in society. We discuss critical autoethnography as an interdisciplinary, blurred genre that transforms to fit the academic backgrounds, interests, and critical orientations of its authors. All contributors to this special issue situate their take on the genre in relevant literature and provide sociocultural critique in explicit and implicit ways.
Eileen R. O'Shea is a contributing co-author (with Roben Torosyan and Betsy Bowen), " Sp... more Eileen R. O'Shea is a contributing co-author (with Roben Torosyan and Betsy Bowen), " Spirituality & Professional Collegiality: Espirit de 'Core'", Chapter 5, pp. 87-107. Book description: This collection of articles explores how a wide range of academics-- diverse in location, rank and discipline-- understand and express how they deal with spirituality in their professional lives and how they integrate
Anthropology & Education Quarterly, 2013
Journal of Research Practice, 2010
Autoethnography is a qualitative research method that utilizes data about self and context to gai... more Autoethnography is a qualitative research method that utilizes data about self and context to gain an understanding of the connectivity between self and others. This introductory article exposes the reader to our own praxis of collaborative autoethnography which we used to interrogate how we navigate the US academy as immigrant women faculty. Before introducing the articles in this special issue, we explore the autoethnography continuum, provide sample areas covered by autoethnographers, and explicate the practice of collaborative autoethnography. We conclude this piece with implications for future use of autoethnography as research method.
This methods book will guide the reader through the process of conducting and producing an autoet... more This methods book will guide the reader through the process of conducting and producing an autoethnographic study through the understanding of self, other, and culture. Readers will be encouraged to follow hands-on, though not prescriptive, steps in data collection, analysis, and interpretation with self-reflective prewriting exercises and self-narrative writing exercises to produce their own autoethnographic work. Chang offers a variety of techniques for gathering data on the self-from diaries to culture grams to interviews with others-and shows how to transform this information into a study that looks for the connection with others present in a diverse world. She shows how the autoethnographic process promotes self-reflection, understanding of multicultural others, qualitative inquiry, and narrative writing. differs from ethnography -a qualitative research method in which a researcher uses participant observation and interviews in order to gain a deeper understanding of a group&ap...
Christian Higher Education
Abstract This article draws from a keynote address presented at the 2019 Doctoral Education Forum... more Abstract This article draws from a keynote address presented at the 2019 Doctoral Education Forum sponsored by the Council for Christian Colleges & Universities (CCCU). A review of the literature reveals growth in doctoral education in the United States and the proliferation of types of doctoral degrees. The article describes an increase in the variety of doctoral capstone products (DCPs) beyond the dissertation, including portfolios, digital DCPs, artistic performances, interdisciplinary collaborations, and professional endeavors; the article also identifies a concomitant need for achieving and maintaining quality outcomes in all forms of DCPs, including the dissertation. Systems thinking is applied to this end by first identifying three factors—the student, faculty, and program context—as influencing the DCP process, based on a review of the literature and then analyzing the interactions among those factors which influence the quality of the DCP processes and outcomes. To holistically improve the DCP process and outcome, five principles are offered: (a) develop a program context that adheres to its standards of excellence; (b) recruit qualified students and position them for success; (c) engage qualified and committed faculty in the growth journey with students; (d) prioritize resource allocation in support of high-quality DCP production; and (e) implement a fair and appropriate DCP evaluation system. The conclusion describes possible implications for future research related to this topic within the context of Christian Higher Education.
This article provides a critical review of global mindset literature. After establishing the sign... more This article provides a critical review of global mindset literature. After establishing the significance of global mindset, the borderline frenetic pace in which models for global mindset development are being produced, and the significance of scholarly conceptualizations of mindset within global “mindset,” we examine the convergences and divergences among scholarly assertions and conclude that knowledge represents the common thread interwoven throughout the many conceptualizations of global mindset. We identify knowledge as the foundation for and a significant key to the development of global mindset and suggest several areas that warrant attention in future research. Further, a case is made for interdisciplinary study as numerous concepts and terms appear analogous to various fields of study within the humanities.