Review

1. Review • What is a researchable question? • What are some ways of collecting qualitative data? • What is meant by triangulation?

2. Notes on Chapter 2 • Don’t use first names or titles of books or articles when talking about a piece of research—just the last name • Be sure the reader knows what is being attributed to whom—and whether it is empirical or just opinion • Spend time laying out research that is very close to your own (who did what with whom and with what results)

3. More Chapter 2 hints • In reviewing the papers, use past tense. The findings have already been found. • When citing multiple papers, place the citations in alphabetic order (not the individual authors, the separate papers: Example: (Corning, 1998; Marcus & Abiton, 2001; Ziani, Meyers & Tuskatu, 1997)

4. Notes on Chapter 3 • If you decide to use an instrument that you have constructed, indicated that you have come up with the questions guided by previous research in your area. • Test group? Sample? • Don’t forget to talk about data analysis!

5. On tap for tonight • Data analysis • Coding categories • Constant comparative • Sense making

6. Coding Categories • Organize data • Make a copy of your data and work with the copy • Read through the data and become familiar with it • Identify main themes • Write notes in the margin • Underline what is important • Note your initial impression • Reread the data

7. Coding categories (con’t.) • Generate a list of main themes or codes – assign abbreviations (recall when we read questionnaire data on college math and science experiences early on) • Go through data again and assign codes to data sections • Do codes fit • Do they need to be modified • Double code? • Recode/collapse categories

8. Coding categories (con’t.) • Sort data by codes • Physically combine similar data sections to get the whole picture • Cut and paste • Put onto note cards • Color code • REASON to keep a clean, intact copy!! • See transparency • Computer aids

9. Summarizing Coding Categories • Try to find a pattern and organize data into categories • What makes sense from all the data • Triangulate to see if what you find in one set of data can be supported by another set

10. Switch to Transparency • Happenings in a teachers’ lounge

11. Constant Comparative • Method of data collection and analysis that is on-going: • Do preliminary observations (Teachers’ perspective on merit pay) • Develop a hypothesis based on observations (Lack of merit pay angers teachers and their anger is being taken out on the school and students)

12. Constant Comparative (con’t.) • Perform additional observations to • Support or reformulate hypothesis (Lack of merit pay does not make teachers angry; it lowers their self-esteem and this is translated into teaches distancing themselves from the school and students) • Continue until there are no new hypotheses developed and you are satisfied with what you have seen.

13. Example of Constant/Comparative • The excerpt in the text about faculty members’ doors. If you haven’t read it, please do!

14. Triangulate – How to’s • Analyze the different data sources • See if the assertions are supported, confirmed or disconfirmed • Make sense of the findings from the various sources • Use examples from different sources to back up your assertions.

15. Three important things to keep in mind with data analysis • What is important in the data? • Why is it important? • What can be learned from it?* *from Gay and Airasian

16. Practice • Look at our data. • What method will we use to analyze these data?

17. Debrief • What did you find? • Do these questions work? • What about the demographic information—too little, too much? • Suggestions for a “do over?”

18. Making Sense of Your Data for Yourself and Others • Look for general patterns and themes • See if there are linkages among responses, commonalities across data • What is the big picture • What hypotheses can you generate • Identify any outliers that you find interesting and feel should be presented • If alternative explanations could exist, state what these may be and why you chose the one you did

19. What you cannot explain to others, you do not understand yourself. Producing an account of our analysis is not just something we do for an audience. It is also something we do for ourselves. Producing an account is not just a question of reporting results; it is also another method of producing these results. Through the challenge of explaining ourselves to others, we can help to clarify and integrate the concepts and relationships we have identified in our analysis. I. Dey

20. Common problems with data collection and analysis • Insufficient amount of evidence –too little evidence to support your assertions (provide 3 quotes/examples for each theme) • Insufficient variety in kinds of evidence—too few sources of data (triangulate—multiple students, observers, sources of evidence, making sure that what was said and what was done match)

21. More problems • Faulty interpretation of the evidence—often due to insufficient time spent with interviewing, observing, etc. • Inadequate attempt to find disconfirming evidence – when an assertion is made, was it tested with additional data • Inadequate handling of disconfirming evidence – throwing out an assertion too soon; may just need to be refined (e.g. teacher praise v. amount of teacher praise)

22. Writing a Chapter FourResults and Discussion • Recall: in quantitative designs, results and discussions are separate chapters. In qualitative designed, these are intertwined. Findings and interpretation cannot be separated.

23. Chapter 4 includes • What you actually did • Who was involved • any changes to procedures and why (changes in sample or questions) • What you found • assertions/themes/generalizations and • What it means along with supporting evidence

24. Supporting evidence • Quotes from interviews and questionnaires • Field note excerpts • Other data • Recall 3 quotes is sufficient

25. Actually writing it • Prose/narrative - interweave evidence in your paragraph OR • More outline: present generalization/assertion and then provide evidence rather “off set” to back it up; OR • Combination of these two

26. Example of Prose • After reading the Novice Planner, C became visibly agitated. His ArcView problem-solving approach for identifying Losey’s house was a trial and error method of scrolling through the data table until he stumbled on the record. The think aloud narrative attests to the confusion that C experienced after reading problem 4. Nervous laughter

27. preceded his remark that “my problem now is that I don’t know which one if his house. I want to find Losey. I’m going to have to go back to…what did I do? It’s in the radius. What I’ll do is take the tool that measures and do it.” The halting, hesitating, disjointed remarks suggest that he was considered many alternative strategies simultaneously without evaluating their individual merits. Ultimately, he relocated Losey’s house by scrolling through the data.

28. Example 2 Teachers’ (n=82) answers to this item were classified into four categories: (a) explicit guidance that gives detailed instructions regarding correct investigation procedures (e.g., “You must control variables. You should only change one factor in each experiment.” or “Do another experiment. Change only the variable ‘light’ and leave everything else as it was before.”); (b) guidance through a series of directive questions (e.g., “I would ask her a series of questions, directing her to change only one variable at a time.”)…

29. Example 3 • Study Group Surveys. Ratings were increasingly positive from Year 1 to Year 2. Especially noteworthy is the meaningful change in team was successful in proposing solutions to topics, increasing from 75% to 94%. Representative comments from respondents in Year 1 indicated collaborative efforts, but expressed concerns about time constraints: “Each grade level compiled a list of activities…and presented to the group,”“Many great ideas and a foundation has been laid out…”“It took a long time to do a little work,” and “Our problem is finding time to implement.” Others commented about the inequity of participation of some SG members, “Some members shared a lot of ideas—others contributed a little bit.”

30. Assertion then example Role of a Scientist. The distribution of premethods responses for the role of a scientist is quite different from the theory responses (Table 2). Four teachers initially gave strong traditional responses that centered on the notion that scientists must be (or are assumed to be) objective in their work (Chalmers, 1982). [My] idea of the scientific method is you want to take as much of your personal opinion or anything else out. (Teacher B) [S]ome scientists can shed their preconceived notions to truly observe. (Teacher G) Scientists are more likely…to not let their opinions get into their work. (Teacher )

31. Example 2 All participants used rationalistic thought processes to guide their decision making in at least some of the genetic engineering scenarios presented to them. They made rationalistic calculations based on a variety of factors, such as patient rights, parental responsibilities, availability of other treatment options, side effects, future applications, and discrepancies in terms of access. The quotes below provide samples of how students relied on rationalistic informal reasoning:

32. 1F(IN): The other ones [the Huntington’s disease and nearsightedness scenarios] is something that you are born with. It is who you are; it is your personality; it has more factors that go into it. Those are ailments or deficiencies—this is not a deficiency. It may be a deficiency to some extent if a person has an extra chromosome or whatever that makes them retarded, but to make them smarter, no. I do not think so. • 18F(TC): Right now, there is a black market for organs so if you could create an organ, then that would be justifiable. The ends justify the means kind of thing…You have to weight all the options and decide whether it is worth the risk.

33. 23F(HD): That is kind of a tricky question because there are a lot of issues with that. I think when you do that, when you use gene therapy to fix these problems, it is kind of artificial natural selection because naturally you would breed those genes out, I guess. I guess in the case of Huntington’s disease it comes on later so they have already reproduced. But if you can get rid of a disease that seems like, why not? The only problem I see with genetic engineering is there is going to be a cost thing. Are only some people going to be able to afford it?...There might be a class difference.

34. The interview excerpts just presented do not capture every reason-based consideration articulated in the interviews, but they do provide evidence to support the notion that rationalistic thought processes contributed to the resolution of socioscientific issues. In thinking about gene therapy for intelligence, participant I made a rationalistic distinction between deficiencies and other types of inherited traits. Participant 18 employed ends-and-means reasoning, to the issue of therapeutic cloning, reminiscent of utilitarian calculations of maximized outcomes (Beauchamp, 1982; DeMarco, 1996). The final..

35. Combination Example The teacher knew the students had no background understandings of the words “observation” and “inference” and provided direct instruction in this instance. Students were then asked to return to their desks and make observations and inferences about their snails. Students seemed to do a very good job of this and to have an accurate understanding of observation and inference. (See Figure 2 for an example of student work on this problem.) When reconvened as a whole group, their responses varied:

36. S: My observation is that it feels slimy. My inference is that when a snail is afraid it gets slimy. S: My observation is when you touch the feeler the cord goes inside the head. I think it does it because the cord goes in to help it see. During the second lesson, there were no specific objectives for finding out what students knew about snails. As the lesson progressed, however, it was evident that the teacher did provide opportunities for students to share their ideas. In this lesson…

37. Who can be called a scientist? • [Student teachers] placed themselves into one of two camps: (a) those who thought only people with degrees and careers in science should be granted the title and (b) those who argued that anyone using scientific thinking skills should be included as well…Daniel, for example, positioned himself squarely in the scientists-as-professionals group. Daniel stated that “a scientist, like a historian or a

38. linguist, has studied long and hard to earn certification in either field. While I think everyone can practice science, only a select few can claim to be scientists.” Daniel’s definitions of scientists can be understood to resonate with situative theorists’ descriptions of scientists as comprising discrete communities of practice (Brown, Collins, & Duguid, 1989; Driver, Asoko, Leach, Mortiner, & Scott, 1994)... Marie, Juantia, Elise, Elan, Leslie, Seth, and toni, in contrast, placed themselves in the second who-can-be-called-a –scientist camp. They defined scientists in broader terms. Juanita explained that scientists can be both people who work in laboratories and people who solve everyday

39. problems scientifically: A professional scientist, in a traditional view, wears a lab coat, works in the lab, does traditional science using the scientific method. Biologists and chemists. But I also think a scientist is someone who goes through the process of taking apart something. My dad is a mechanic and I think in a sense he is a scientist because he observes, looks at a problem, and uses science to figure out what is wrong. (interview).

40. Ways to add validity and reliability From analyzing transcripts, portfolios, and journals, we found multiple mediators including teachers’ students, readings, the instructors, tools, and peers. There was evidence of the traditional Vygotskian view of a “more capable peer” in dyads such as Sabrina and Isabella, where Isabella served as a tutor for Sabrina and taught her science concepts. However, most dyads learned well together as well as from each other…

41. Additional Info • Chapter 4 starts with your problem statement (yes, again) • Describes actual implementation (sample size, changes, etc.) • Provides findings with evidence • Ends with a summary/overview of main findings

42. Closure • Should be able to write Chapter 4 • Analyzing data • Triangulating • Coming up with assertions and supporting these