Short Course on Text Analysis Systematic Techniques for Analyzing Qualitative Data

Supported by the National Science Foundation Duke Marine Labs, Beaufort, North Carolina, July 14-18, 2008

Course Schedule

Monday Morning	Jump to day... Monday Tuesday Wednesday Thursday Friday

• Introductions & Class Logistics
• Overview of Qualitative Research
• Collection techniques (*Bernard et al. 1986; Weller & Romney 1988)
• Analytic traditions (*Ryan & Bernard 2000; Bernard & Ryan 1998)
• The Role of Software in Qualitative Research (Johnston 2006; MacMillan 2005; Peters 2007; Welsh 2002)
• The Basics (a brief overview)
  • Identifying themes
  • Building and applying codebooks
  • Describing themes
  • Making comparisons
  • Building and testing models
• Lecture Slides

Monday Afternoon

• Identifying Themes (*Ryan & Bernard 2003; *Jehn & Doucet 1996, *Jehn & Doucet 1997; *Boeije 2002)
  • Lab: Identifying Themes
  • Illness data (compare & contrast, metaphor, transition) [MAXQDA]
  • Personals data (paw & sort)
• Lecture Slides

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Tuesday Morning

• Building and Applying Codebooks   (*MacQueen et al. 1998; *Carey et al. 1996; *Willms et al. 1992)
  • Example of Codebook: WaterSim
  • Lab: Building and Applying Codebooks
    • Illness data [MAXQDA]
    • Personals data [Excel]
• Describing Themes (*Coulter et al. 2000; *Rubinstein1995; *Gallimore et al. 1989; *Bloom 2001)
• Lab: Describing Themes
• Illness data [MAXQDA]
• Personals data [Excel]
• Lecture Slides

Tuesday Afternoon

• Making Comparisons (*Yoder 1995, *Weisner et al. 1991)
  • Handouts: Examples of Comparisons
  • Lab: Making Comparisons
    • Illness data [MAXQDA]
    • Personals data [Excel]
• Building & Testing Models (*Addison 1992; *Eisenhardt 1989)
• Lab: Building and Testing Models
• Illness data [MAXQDA]
• Personals data [Excel]
• Lecture Slides

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Wednesday Morning

• Data Archiving
• Notes, video, and recordings (*Maloney & Paolisso 2001; Stigler et al. 1999)
• Transcription (McLellan et al. 2003)
• Data documentation and sharing (*Fielding, 2004; *Corti, Witzel, & Bishop eds. 2005)
• Web sources (*ESDS Qualidata; *Harvard-MIT Data Center; *ICPSR; *Data Documentation Initiative)
• Lecture Slides
• Grounded Theory & Schema Analysis (*Charmaz 2000; *Morrow & Smith 1998; *Abrahamsson 2002; *Maijala et al. 2003; *Bringer et al. 2006; *Markovic 2006)
• Negative case analysis (*Dey 1993:226–233; *Denzin 1979:194-199)
• Key references: (Glaser & Strauss 1967; Strauss 1987; Glaser 1992; Corbin & Strauss 2008; Dey 1993)
• Web sources: AREOL, Pandit, Online Grounded Theory Articles, More bibliography
• Software: ATLAS.ti; AnSWR; Text Analysis Info; MAXQDA; NVivo; TAMS Analyzer.
• Lecture Slides

Wednesday Afternoon

• Grounded Theory
  • Lab: Grounded Theory
    • Memos [MAXQDA]
    • Concept mapping [MAXMaps]
    • Corbin & Strauss [MAXQDA]

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Thursday Morning

• Word-Based Analysis
  • KWIC (*McCarthy et al. 2004)
  • Word counts (*Ryan & Weisner 1998)
  • Semantic networks/cognitive maps (*Jang & Barnett 1994; *Ryan et al. 2000; *Nolan & Ryan 2000; Strauss 1992; Kirchler 1992)
  • Web resources: Simple Concordance Program; System Quirk
  • Software: General; KWIC & Word Counts: Concordance; TextPack; TextSTAT

Thursday Afternoon

• Semantic Network Analysis
  • Lab: Semantic Network Analysis
    • KWIC: Deconstruction [Paw & Sort]
    • Word counts [MAXqda, QDAMiner]
    • Word co-occurrence [Anthropac/UCINet, QDAMiner]
    • Personals data
    • AA abstracts
    • Illness severity data
    • Civil rights oral histories

• Lecture Slides

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Friday Morning

• Classic Content Analysis (*Hirschman 1987; Cowan & O’Brien 1990; *Schuster et al. 1998)
  • Intercoder Reliability: Kappa
  • Key references: (Krippendorf 2004; Weber 1990; Neuendorf 2002)
  • Web sources: Neuendorf’s excellent site; The Content Analysis Guidebook Online
  • Software: General; EZText, MAXDictio, WordStat 5.1
• Content Dictionaries (Colby 1966; Gottschalk 1997)
  • Web sources: General Inquirer; Gottschalk Scales.
• Generic Analysis (*Crabtree & Miller 1992; Morgan 1992)
• Ethnographic Content Analysis (Altheide 1996)

Friday Afternoon

• Classic Content Analysis
  • Lab: Classic Content Analysis
    • Personals data
    • AA abstracts

• Lecture Slides

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