![]() ![]() This course focuses on in-depth discussion of, and practice with, the three primary qualitative data collection methods - participant observation, in-depth interviews, and focus groups. This course presents alternatives to current practices and calls for greater clarity in the logic of design when producing ethnographic research in a multi-method intellectual environment. Qualitative researchers sometimes incorporate elements of quantitative methods into their research designs, such as selecting respondents “at random” for small, in-depth interview projects or identifying “representative” neighborhoods for ethnographic case studies, aiming to increase generalizability. Students new to qualitative research are welcome to attend. The course will cover how memo writing can lead to efficient coding and will look at the nature of codebook evolution and the differences between deductive, inductive, and thematic codes. Coding and memoing are presented as complementary tasks that occur while engaging textual data and identifying meaning units. This course focuses on coding and memoing qualitative data within both the psychometric and heuristic traditions. Finally, we will discuss how to use diagrams to visualize emerging themes. We will also review the co-occurrence explorer and query tool and introduce how to use multi-media data in ATLAS. This course will cover advanced analytic tools in ATLAS.ti, such as assessing intercoder reliability, the redundant codings analyzer, and working with survey data. This hands-on short course will cover analysis features (co-occurrence explorer, the query tool, the codes-primary-documents table) and using diagrams in your analysis.ĪTLAS.ti Workshop - Analysis & Special Tools ATLAS.ti provides numerous options for attaching memos and comments to text segments, documents, and codes. It provides a network editor that allows you to graphically display and examine the hierarchical and relational connections among your codes. This hands-on short course will illustrate the capabilities of the PC version of ATLAS.ti 7, a software program for coding and interpreting qualitative text. Finally, writing the mixed method proposal will be outlined. Day 2 we will discuss qual-qual and quan-quan mixed methods designs, issues of quality and common pitfalls. We will also discuss the research process, common problems, and examining published articles. Day 1 we will discuss Qualitative-quantitative mixed method designs (simultaneous and sequential designs: QUAL-quan and QUAL-quan and QUAN-qual two sample designs]. We will then discuss the notion of theoretical drive, and QUAL-quan and QUAN-qual simultaneous designs. First I will distinguish between multiple-methods and mixed-methods, and why mixed-method designs may present threats to validity. In this workshop I will discuss advances in mixed-method design involving the interface of qualitative and quantitative methods. Past course descriptions (Courses that have been held in the past, but may not be necessarily on our upcoming schedule):Īdvances in Mixed Methods Design (Two-day Workshop) Professional Development: Upcoming short courses highlighting skills for professionals and academics.Data Science: Upcoming short courses in data science.Survey Research: Upcoming short courses in survey research.Qualitative Research: Upcoming short courses in qualitative research methods/data analysis.Quantitative Analysis: Upcoming short courses in quantitative data analysis/statistical software.Courses that require non-refundable registration fees will indicate as much on the individual event pages. These courses fill up on a first-come, first-served basis. Many of our courses are free for the UNC community – you just need to secure your spot with a small deposit that is refundable upon attendance for the full course. A number of courses are also open to researchers from not-for-profit organizations, government agencies, and corporations. More than 2,250 participants, including UNC undergraduate and graduate students, faculty and staff, attend our short courses annually. ![]()
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