Session 1 (Choose One) Session 2 (Choose One)
Mon. June 1 (all day), Tue. June 2 (all day), and Wed. June 3 (half day) Thr. June 4 (all day), Fri. June 5 (all day), and Sat. June 6 (half day)
Session 1: June 1-3, Four Course Options (Choose One)
This course focuses on Advanced Qualitative Methods for Micro-Management Research, the first of a two-course sequence. We will explore ethnography, interviewing techniques, and narrative analysis. We will briefly review the epistemological foundations of grounded theory qualitative research, then move immediately into aspects of early-stage grounded theory, including protocol development and interviewing, taking an applied focus through the use of exercises and activities. We will examine tactics for designing a grounded theory study, tips and techniques for coding, and pitfalls and strategies associated with the review process for qualitative papers. Students will gain hands-on experience with observation, interviewing, coding, and reviewing. We will also discuss published exemplars, with a focus on deconstructing the methods used.
Option #2: “Crafting High Quality Qualitative Research via a Phronetic Iterative Approach” – Dr. Sarah J. Tracy, Arizona State University
This workshop offers strategies for achieving quality in qualitative research across disciplines and paradigmatic leanings. Based upon material in the instructor’s book Qualitative Research Methods: Collecting Evidence, Crafting Analysis, Communicating Impact and article, Qualitative quality: Eight “big-tent” criteria for excellent qualitative research, participants will learn techniques so that their research evidences: 1) worthy topic, 2) rich rigor, 3) sincerity, 4) credibility, 5) resonance, 6) significant contribution, 7) ethics and 8) meaningful coherence. Along the way, they will be presented with claim-making and theory building heuristics that help their research have resonance and significance beyond the case at hand. This workshop is ideal for researchers, grant-writers, and instructors of qualitative methods—both those new to these areas as well as experienced. This eight-point conceptualization offers a useful pedagogical model and provides a common language of qualitative best practices that can be recognized as integral by a variety of audiences.
As a result of the workshop, participants will learn to:
- Craft a topic that is heard as relevant, timely, significant and interesting to core audiences
- Create rich rigor through using sufficient, abundant, appropriate, and complex theories, data, constructs, and analysis processes
- Communicate sincerity by being self-reflexive and transparent
- Mark credibility through thick description, triangulation, crystallization, multivocality, and member reflections
- Fashion resonant research that influences and moves audiences through aesthetic representation, naturalistic generalization, and transferable findings
- Develop a significant contribution—theoretically, practically, morally, methodologically, and heuristically
- Practice qualitative ethics–including procedural, situational, relational, and exiting considerations
- Craft meaningful coherence by interconnecting literature, research questions, findings and interpretations so that they fit together, cohere with the study’s goals, and connect with the audience’s expectations.
Tracy, S. J. (2020). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact, 2nd Ed. Hoboken, NJ: Wiley-Blackwell.
Tracy, S. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative Inquiry, 16, 837-851.
Option #3: “Qualitative Analysis for Organizational Change” – Dr. Jean Bartunek, Boston College – POSTPONED
This CARMA Short Course concerns exploration and critique of several qualitative approaches that may be used to study various types of change within organizations from a somewhat mezzo perspective. Course topics will include several types of change that may occur within organizations, including action research/planned change, organizational learning, and dialectical/paradoxical change. It will also address experiences of recipients of organizational change, and affective and temporal processes within change. From a research perspective, it will also address roles of the researcher with regard to change. Researchers may play several roles, including change participant, external researcher, or collaborator with one or more members of the organization in studying the change. In the course we will review recent scholarship that addresses approaches to change and critique qualitative methods this scholarship uses to study them. Finally, using available materials, we will explore how some of the methods would be used in students’ own research.
This course begins with an overview of mixed methods research designs, including sequential explanatory, exploratory, and transformational versions, as well as concurrent triangulation, nested, and transformative alternatives. Next, Qualitative Comparative Analysis (QCA) is introduced as an increasingly popular approach in management research that is relevant for qualitative and quantitative researchers alike. The course includes hands-on application of QCA, Crisp- and Fuzzy-Set analyses, the interpretation of QCA results, and the potential of using QCA as part of mixed methods research designs.
Session 2: June 4-6, Four Course Options (Choose One)
In this course, students will be exposed to research methods currently used in macro-level management fields, specifically in strategic management, organization theory and entrepreneurship. This course assumes limited prior knowledge of qualitative methods, but it will still provide a deep grounding in several advanced qualitative methods and text analysis as applied in management research. Methods covered include comparative case study research, content analysis, discourse analysis, rhetorical analysis, sentiment analysis (also called tenor or tone analysis), and the construction of dictionaries. The course will be interactive with discussion of exemplar papers that showcase each of these methods. Students will also be given the opportunity to “pilot test” the methods by interviewing each other and content analyzing a small sample of text. A focus of this workshop will be on matching methods to research questions and the interests and strengths of the research team.
Required Software: LIWC2015 (30 day rental available for $9.95; purchase for $89.95 from Linguistic Inquiry and Word Count)
We will explore the process of conducing a grounded theory study. We will discuss generating research questions and interview protocols; collecting data (e.g., participatory, interview, secondary); the coding process; other data analytic processes beyond coding; generating a grounded model; and navigating the review process. We will examine how to ensure trustworthiness and rigor in grounded theory research, and consider challenges of conducting such research when you’ve been trained primarily in quantitative research. Our approach will be a mixture of readings discussion (exemplar and how-to articles) and hands-on exercises.
This seminar is an intensive “hands-on” experience with video methods in organizational studies. Participants will learn how to collect and analyze video data that provide empirical support for scholarly evidence and arguments. People may bring their own video, already captured and ready for examination, or use video data provided by the instructor. On the one hand, participants will look closely at human interaction within organizational settings: we will examine how people orchestrate their talk and bodily movement, moment to moment, within social and material environments, all in the service of social action and sense-making. On the other hand, we will keep an eye on “big” social and organizational issues, such as:
- What do power and status (or weakness and inequity) look and sound like?
- How do new ideas emerge and evolve, necessarily taking a social and material form?
- How is expertise enacted and acquired?
- What are patterns of healthy (and deficient) collaboration within an organization?
Seminar activities and assignments have two purposes. First, we will become better acquainted with research methods that may include video (e.g., conversation analysis, context analysis, and ethnography). We will talk about the underlying assumptions, distinctive features, and strengths and weaknesses of various approaches. Second, we will talk about the practical issues of this kind of research, such as research design, site selection and entrée, recording equipment and data collection, transcribing, data management and analysis, paper writing and publication.
Day 1: Analyzing talk as action
- Overview of methods for studying naturally occurring discourse
- Data collection (consent and confidentiality; observing; recording; logging; transcribing)
- Conversation analysis
Day 2: Multimodality: Embodied Interaction
- Using multimedia technologies
- Analyzing visible (nonverbal) behavior
- Context analysis
Day 3: Organizational studies: Knowledge, Power and Identity
- The emergence and evolution of new ideas
- Organizational routines
- Business strategy as practice
Content analysis is a structured way to extract meaning from artifacts (e.g., texts, images, videos), and its application ranges from qualitative to quantitative research designs. Using modern computational techniques, we can bridge the two designs to varying degrees, retaining more of the depth of qualitative research at the traditionally larger scale of quantitative research. This short course focuses on computational approaches to content analysis that enable large scale quantitative research using text data, with a particular emphasis on the foundational skills of identifying, collecting, and preparing text data using Python. We will begin with an overview, emphasizing the specific skills that have a high return on investment for researchers. Then, we will walk through foundational Python skills for working with data. Using those skills, we will cover collecting text data at scale using several techniques, including web scraping and application
programming interfaces (APIs). From there, we will extract meaning from text, in the form of quantitative measures, using computer-augmented human coding, dictionary methods, supervised machine learning, and unsupervised machine learning. By the end of the course, you will have the skills—and many hands–on code examples—to conduct a rigorous and efficient pilot study, and to understand the work needed to scale it up. The course design does not assume any prior training, though reasonable spreadsheet skills and some familiarity with one of the commonly–used commercial statistical systems is helpful. In particular, no prior knowledge of Python is required, and we will cover an introduction to Python in the beginning of the course content.