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Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
Action research for_librarians_carl2012
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Action research for_librarians_carl2012

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The action research methodology can be easily applied to work done in libraries. This presentation

The action research methodology can be easily applied to work done in libraries. This presentation

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  • Three types
  • Some people describe AR as a type of EBL. EBL was first described in early 90s. Came out of Evidence Based Medicine/Evidence Based Healthcare which began at the same time. Those research paradigms sought to empower medical practitioners/ doctors in the same way Action Research empowered teachers, but seems to limit itself to the technical and practical level as the goal of EBM and EBL is to make current practices more efficient. As David Loertscher states in a 2009 essay in Evidence Based Library and Information Practice, EBL works as long as “antecedents or foundational inputs remain the same.” More credence given to quantitative data, formal data analysis with goal that results will be applicable beyond a specific workplace -- findings can be generalized, can be published in peer reviewed journals. Requires more rigorous methods. In Library Science, doesn’t seem to require collaboration, although this is required when used in other fields. Both data driven, practitioner-concern driven, ethics-driven. But EBL doesn’t have the same emancipatory possibilities.
  • This is the time in the action research process when you decide what you’re going to research and how you think you’ll do it. Usually identify the problem by reflecting on your work or through conversations with colleagues or friends. After you’ve thought about what you’d like to investigate, you develop a research plan. This plan will include lists of people or resources you think you’ll need, ideas about the types of data you can collect or that you’ve already collected, and ideas about how you think you’ll analyze your data. You can generate these ideas through conversations with colleagues or by looking at the literature. The main thing to understand about this time in the process is that this is what sets action research apart from being simply reflective practice. You’re going to systematically look at your issue and this is where you set that system into place.
  • This is where we can jot some of the problems we’ve overheard as we walk around the room.We can keep this up: Scenario: Virginia thinks of a question and brainstorms types of data/evidence she can collect. But how can she analyze it? She asks April and Stephanie for help. (VA, April, SRR, 5 mins)
  • http://www.voki.com/pickup.php?scid=5770291&height=267&width=200
  • First video: http://www.voki.com/pickup.php?scid=5778656&height=267&width=200Second video: http://www.voki.com/pickup.php?scid=5778765&height=267&width=200
  • 4 mixed methods designs3. ex. is demographic survey during a qual study or an interview with the circ manager to prep for analyzing circ statsActivity: consider the problem you described to your group or the problem that we introduced and draft a study plan using one of these designs, and if one of the other designs was more appealing to you, sketch out a study plan using that one, too.
  • Review what can be done in Excel. MS Excel is a great statistical tool – good for quantitative analysis.
  • You can use EXCEL for descriptive and inferential statistics. DEFINE both with examples of types of tests.
  • There are 4 levels of quantitative data: nominal, ordinal,interval, and ratio. A lot of the data we get in library instruction is nominal or ordinal, and ocassionaly interval. Nominal – male or female – exclusive catergories that don’t have a “value”Ordinal – likert scales, strongly agree, agree, disagree, strongly disagreee – exists in catergories that are ranked or related to each other by more/lessInterval – grades – data that is related or ranked like ordinal data, but the assumption is made that there is equal distance between the scales, but there isn’t ameaningful 0.Ratio data – 0 is meaningful. Like no money in your pocket. HELP APRIL.The types of tests you run on your data are determined by the type of data that you have, and how your data is distributed, and then what you want to find out. Much of the time, we only need descriptive statistics to answer the questions we have in libraries. But, no matter what, you have to start with descriptive statistics: namely measures of central tendency (mean or average, median, mode) and find out if the data is skewed or balanced, in order to determine if you can run further tests.
  • You can run specific formulas in EXCEL which you can find under functions or more functions, statistical. One you’re probably already familiar with is Average, but you can also run STDEV or standard deviations from this menu. You can also create Pivot Tables, which are also known as cross tabs, and look similar to what April ran in many eyes. You would use that to find out if there is a correlation between data points, so, as in our example if more students who attended a library workshop met or exceeded a professor’s bibliographic requirements. If you are using a PC, you can download the analysis toolpak add in for EXCEL. This will enable you to select a set of data and ask EXCEL to run standard statistical tests on it.However, you will need a good guide so you can understand what kind of data you have, and what tests to run and how to run them. We’ve recommended some in the bibliography.
  • Mean is the average – you can only use this if you have at least interval level data, median is the middle value when you place all of the values in order (ordinal) and the mode is the most frequently found value (nominal).Skewness is how far off the range of values is from a perfect, balanced curve.Standard deviation – standard amount of distance between interval scores, kurtosis, how peaked or flat the curve will be.
  • Rubrics are used to analyze qualitative data. They list criteria and levels of achievement, then specify what the evaluator should see in order to rank or score what is being analyzed. They can be honed as the researcher analyzes data.They are tested through use and should probably be tested with a second evaluator (interrater) and over time with the same evaluator (intrarater) : inter and intra-rater reliability,
  • some resources for finding rubrics already created AAU, RAILS etc.
  • http://www.voki.com/pickup.php?scid=5778959&height=267&width=200
  • So I hope that today you’ve gained some confidence in your ability to plan out your own action research study in to investigate and use new methods of collecting and analyzing data. I also hope that you’ve begun to realize the power of conversation with your peers and colleagues and gained some habits of mind that can enable you to approach change with less trepidation and perhaps foment change with authority.
  • Transcript

    • 1. Action Research How to easily incorporate evidence based research into your practice 1CARL Pre-conferenceThursday, April 5, 2012, April8:00 am – 12: 00 pm Cunningham, Saddleback Community CollegeSalon A-CSan Diego, Calif. Stephanie Rosenblatt, California State University, Fullerton
    • 2. Learning Outcomes Learning OutcomesI. Articulate questions about your practice andcollaborate with peers to generate ideas forinvestigating these questionsII. Practice using various methods and tools fordata collection and analysis.III. Understand the concept of action research 2
    • 3. Action Research Cycle 3 Plan Share Act Reflect
    • 4. Types of Action Research 4
    • 5. Evidence Based Action ResearchLibrarianship 5
    • 6. Action Research is… 6 Informed by concerns about practice/praxis Conducted and often initiated by the librarian(s) impacted as their expertise is valued Collaborative Critical, deliberative, and self-reflexive Instigated with the goal of changing practices, processes, policies, theories, or systems Applicable to the local context
    • 7. 7Getting toknow… What do you hope What do to get out you do?YOU! of today’s session? What kinds of research/ Where evaluation do you have you work? done before?
    • 8. Plan 8• What’s problematic in your work?• Identify partners and “critical friends” by talking to them throughout the process• Review the literature• Develop a research plan• What kind of information do you need to investigate your question/problem?• How can you collect it?
    • 9. Task: Consider Your Work 9• Take a moment to think aboutyour own work. What’sproblematic?• Generate one or two questionsyou’d like to investigate.•Talk to a partner in your group.Do you share anyquestions/problems in common?
    • 10. Problems/Questions 10?????????????????????
    • 11. ‹#›
    • 12. ‹#›
    • 13. METHODOLOGY INTERLUDE Quan Qual MixedBUT FIRST: WORLDVIEWS (ESPECIALLYPRAGMATISM) 13
    • 14. WORLDVIEW RESEARCH FOCUS ActPragmatism Problem centeredPostpositivism Theory verification, ObjectivityConstructivism Multiple meanings, SubjectivityAdvocacy Empowerment, Change oriented 14
    • 15. 15Quantitative Intent: see how data fits anInquiry existing theory, model, or explanation  Ask close-ended questions  Collect and analyze numbers; Statistics  Large samples
    • 16. 16Qualitative  Intent: learn participants’Inquiry Act views  Ask open-ended questions  Collect and analyze words and images; themes  Small Samples
    • 17. TYPICAL METHODSQuantitative QualitativeCollection Act Collection•Quasi-experiment •Interview•Close-ended Survey •Open-ended Survey•Usage Statistics •Focus Group •ObservationAnalysis Analysis•Descriptive statistics •Coding•Cross-Tabulation •Discourse analysis•Correlation•Comparing Means 17
    • 18. VALIDITYQuantitative Qualitative•Statistical methods: Act methods: •Coding -rejecting hypotheses -identifying themes -calculating effect sizes •Small samples studied in•Large, random or depth in their naturalrepresentative samples environment•Take steps to remove •Peer review of data andresearcher bias analyses; reciprocity with participants 18
    • 19. 19MIXED METHODS: “clarify  Qualitative data enhance subtleties, cro quantitative findings because ss-validate they explain the statistical findings, and relationships inform efforts to  Qualitative data can inform plan, impleme instrument design for a later nt, and quantitative phase evaluate strategies” ctCreswell & Clark (2007). Designing and conducting mixed methods research.
    • 20. 1. Exploratory 2. Explanatorya) Qual a)Quant b)Quant b) Qual3. Embedded 4. Triangulation a) Complementary Supported Qual & by b) Quant
    • 21. Break for 10 minutes. When wecome back, we’ll…o Collect datao Analyze datao Continue talking to our collaborators 21
    • 22. ACT 22• Collect data• Analyze data• Continue to talk to collaborators or friends about your findings to get different perspectives on your process/methods and what you’re discovering
    • 23. Data Collection Tools: 23
    • 24. Data Analysis Tools: 24 Tableau Public Excel Rubrics LIWC Word text.stat
    • 25. Tableau Public 25HTTP://WWW.TABLEAUSOFTWARE.COM/PUBLIC
    • 26. Microsoft Excel 41
    • 27. Types of Statistics 42Descriptive statistics Inferential statisticsDescribing the numerical Using the sample youdata you have by have to make inferencesorganizing, graphing, or or hypotheses about atabulating. larger population. 6 5 4 3 2 1 0
    • 28. NominalOrdinalInterval Ratio 43
    • 29. 44
    • 30. Microsoft Excel 45
    • 31. 46
    • 32. Posttest Results Pretest Results 126 105 84 63 Frequency 42 Frequency 21 00 47
    • 33. Rubrics 48
    • 34. 49
    • 35. Microsoft Word 50
    • 36. Linguistic Inquiry and Word Count (LIWC) 52 HTTP://WWW.LIWC.NET/TRYONLINE.PHP
    • 37. Text Stat 56HTTP://TEXTSTAT.SOFTWARE.INFORMER.COM/
    • 38. ‹#›
    • 39. Your Turn: Data Analysis Task: Analyze data Select a recorder and timekeeper for this task. Work with your group to begin analyzing datasetsYou’ll find electronic copies of some datasets, along data analysis tools on our blog: http://alaworkshopdata.wordpress.com/carl- preconference-2012/ 62
    • 40. Task: Your Turn to Reflect  Were you able to learn something about the instruction program in this scenario?  What was a successful approach to the data?  What was frustrating?  How else could you investigate the problem/issue? 63
    • 41. Action Research Cycle 64 Plan Share Act Reflect
    • 42. Reflect 67Think about how the findingswill impact your own work.What will you change?Do you now have newquestions? How can you explorethose?
    • 43. Share 68
    • 44. 67  What did you learn aboutTask: Share the instruction program in this scenario?  How could you use what you learned about the program?  Changes?
    • 45. Your turn:Plan your ownproject How might you analyze that information? Identify or collect the information you need Identify potential collaboratorsWhatproblemsare youhaving? 68
    • 46. Applying the Action Research Methodology 69
    • 47. Thank You 70 April Cunninghamacunningham@saddleback.eduStephanie Rosenblatt srosenblatt@fullerton.edu

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