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# overlyhonestmethods : Mixed Methods step-by-step

# overlyhonestmethods : Mixed Methods step-by-step. Cat Biddle EPSSA Methods Workshop April 11 th , 2013. Img source: http://runt-of-the-web.com/best-overly-honest-methods. The project. What role does place play in defining school purpose?

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# overlyhonestmethods : Mixed Methods step-by-step

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  1. #overlyhonestmethods:Mixed Methods step-by-step Cat BiddleEPSSA Methods WorkshopApril 11th, 2013

  2. Img source: http://runt-of-the-web.com/best-overly-honest-methods

  3. The project What role does place play in defining school purpose? • Tradition of local control of schooling in America • Neo-institutional theory suggests normative, coercive and mimetic forces may play a role in shaping school purpose • Schools are local/national institutions – so, who/what determines school purpose?

  4. Data and definitions • Data = school district mission statements • Place = urbanicity using NCES locale codes

  5. Method selection • Content analysis of district mission statements -Data must be durable in nature -used to understand specified characteristic of messages • Emergent coding structure: • Randomly selected 25 mission statements and coded them by hand, compared our coding and developed initial coding structure • Coded 50 mission statements by hand using initial coding schematic, reconciled any differences through more discussion of what codes signified

  6. Coding

  7. Using Nvivo in MM Step 1: Import spreadsheet -External Data  Dataset -Differentiate between codable and classifying fields in your spreadsheet (this creates attributes) -Create nodes for each “case” in your spreadsheet (this is just a good idea in any project) through

  8. Using Nvivo in MM

  9. Using Nvivo in MM Step 2: Code the data and reconcile coding divergence -Merge Kai’s coding file with my version -Compare Kai’s and my coding by using the “Show coding stripes” function (and selecting “users”) -View  Coding Stripes  “Selected Items”  Users  select desired codes

  10. Using Nvivo in MM

  11. Using Nvivo in MM • Matrix queries allowed us to see preliminary results that led us to pursue more analysis • Exported a spreadsheet of a Matrix Query of all districts for all codes (with presence of code = 1 and absence of code = 0) • Save query  right click on it and “Export list” to Excel

  12. Using Nvivo in MM work

  13. Scooped! • Stemler, Bebell and Sonnabend (2011) EAQ piece is a MM piece looking at high school mission statements (including looking at them by urbanicity, amongst some other factors). • BUT, their findings were really different from our initial findings.

  14. Method Selection • Chi-square tests of bivariate association • By urbanicity • Binary logistic regression using CCD • Coded themes as dichotomous outcome variables • Variables included students eligible for free/reduced price lunch, PSSA score of advanced on reading and math, % non-white students*, district drop out rate*, and student-teacher ratio *log-transformed to correct for non-normal distribution

  15. Responding to reviewers • Questions about the unit of analysis led us to collect additional data • Randomly selected • 75 elementary schools • 75 middle schools • 75 high schools Compared these mission statements (if they existed) to the district mission statement

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