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  • 1. Some experimental methods in Educational Research Questions Design Analysis Adam Dubrowski, HSC Learning Institute

2. Not enough? 3. You need to perform a systematic review of literature 4. You need togenerate an answerable question 5. You need to generate a 6. You need to design of a clean experiment 7. You need to be able to us ethe stats 8. You need togenerate an answerable question 9. Types of Questions

  • Health Care Intervention(or treatment, prevention therapy): Determining the effect of different interventions
  • Harm(causation): Ascertaining the effect of potentially harmful agents
  • Prognosis : Estimating the future course of a patients disease or condition
  • Diagnosis(or assessment): Establishing the power of a diagnostic tool
  • Meaning : Describing, exploring, and explaining phenomena
  • Economics : Studying the economic efficiency of health care programs or interventions

10. Types of Questions

  • Education : Determining the effect ofeducationalinterventions

11. Matching Question to Study Design

  • Quantitative studies are most useful for answering questions of how many or how much
  • Qualitative studies are most appropriate for answering questions about how people feel about or experience certain situations and conditions.

12. Matching Question to Study Design

  • Quantitative studies are most useful for answering questions of how many or how much
  • Qualitative studies are most appropriate for answering questions about how people feel about or experience certain situations and conditions.

13. Asking Structured Questions (WHY?) 14. Asking Structured Questions (WHY?) 15. Asking Structured Questions (WHY?) 16. Asking Structured Questions (WHY?) 17. Asking Structured Questions (WHY?) 18. Quantitative Questions (PICO)

  • Population
  • Intervention or exposure
  • Comparison
  • Outcome

19. Quantitative Questions ( P ICO)

  • The Population
    • Who are the trainees?
    • Why are they enrolled?
    • Is there a particular age or sex grouping?
    • Is there a particular profession grouping?
    • What else?

20. Quantitative Questions (P I CO)

  • The Intervention
    • What interventions are we interested in?
    • Examples?

21. Quantitative Questions (PI C O)

  • The Comparison
    • What are the current educational practices or what are other possible educational practices that we are interested in comparing?

22. Quantitative Questions (PIC O )

  • The Outcome
    • What are the relevant consequences of the intervention in which we are interested?
      • Satisfaction
      • Performance
        • Individual
        • Team
        • Patient
      • System changes
      • Economics

23. Quantitative Questions (PIC O )

  • Group work

24. Hypothesis 25. Hypothesis A hypothesis[from Greek] consists either of a suggested explanation of a phenomenon or of a reasoned proposal suggesting a possible relationship between multiple phenomena.In science:The Scientific Method requires that one cantesta scientific hypothesis.Generally base such hypotheses on previous observations or on extensions of scientific theories. 26. Hypothesis

  • For evaluation of a hypothesis, one needs to define operational terms.
  • I predict that A will lead to D only if B and C are in place
  • A hypothesis should enablepredictionsby testing.
  • A hypothesis requires work by the researcher in order to eitheracceptorrejectit.

27. Hypothesis

  • A hypothesis may take the form of asserting a causal relationship (such as "A causes D") but not always.
  • For example, if a particularindependent variablechanges, then a certaindependent variablealso changes.
  • However
  • . what we do not know is whether there is a direct causal relationship, or whether there is another variable in the middle that causes the change.

28. Hypothesis: Variables Anindependent variableis the variable whose value one actively controls and can change.Adependent variableis the thing whose value then changes as a result. Example: In a study of how introduction of eLearning modules affect the adherence to a program, a researcher could compare the course drop out rate (the ? variables) with the presence of eLearning module (the ? Variable), and attempt to draw a conclusion. 29. Hypothesis: Variables Anindependent variableis the variable whose value one actively controls and can change.Adependent variableis the thing whose value then changes as a result. 30. Hypothesis testing In statistics, there are only two kinds of hypothesis that are being tested:The null hypothesis or H 0 .The alternative hypothesis or H 1 . 31. Hypothesis testing In education research, the null hypothesis may be used to test differences in intervention and control groups at the end of a program, and theassumption is that no difference exists between the two groups for the outcome variable being compared. 32. Not guilty unless proven otherwise 33. Hypothesis testing: Statistical significance The p value or alpha is the chance you are willing to take torejectthe Ho [not guilty], while you actually should haveretainedit. The choice of the level is up to the experimenter and may be determined as a function of the phenomenon being studied. 34. Pause 35. Experimental design 36. You have performed a systematic review of literature 37. You have generated an answerable question 38. You have generated a 39. What is the next step? 40. You need to design of a clean experiment 41. Example You may wish to examine if a new hands on simulation based educational program leads to adherence to hand washing protocols [by nurses .newly hired nurses etc]. Is this a good research question? Does it have all the parts? What are the hypotheses? Ho H1 Experimental design 42. Example You may wish to examine if a new hands on simulation based educational program leads to adherence to hand washing protocols. Is this a good research question?OK, but not great Does it have all the parts?No control, participants, outcomes. What are the hypotheses? Ho:Old and new programs are the same H1:Old and new are different (note no directionality) Experimental design 43. To test this hypothesis requires 2 conditions to be met(Cook and Campbell; 1979) .1. Changes in the outcome occurafter , rather thanbeforethe institution of the program/intervention.2. The program/intervention are theonlyreasonable explanation for the changes in the outcome.If there are any other explanations for the observed changes in outcomes the researcher cannot be confident that the presumedcause effectrelationship is correct. How do you know if there are other explanations? Experimental design 44. Eliminating these alternative explanations is the purpose of a proper experimental design. These are also known asthreats to internal validity(Cook and Campbell 1979).Experimental design 45. MinimizingThreats to Internal Validity:Argument .This is the least effective ways to argue threats to internal validity.-In a paper it is in the intro Design .This is by far the most powerful method to rule out alternative explanations.-In a paper it is in the methods Analysis .The researcher can use various statistical analysis performed on the collected data.-In a paper it is in the methods and results Experimental design 46.

  • The three ways ofMinimizing Threats to Validityare not mutually exclusive and a good research plan should make use of multiple methods for reducing threats.

Experimental design 47.

  • Design construction
  • Most research designs can be conceptualized and represented graphically from four basic elements
  • Time, randomization, groups, interventions, observations, etc.
  • XOXOXOXO

Experimental design 48.

  • Time .In design notation time is represented horizontally.
  • Intervention(s).In design notation the intervention is depicted with the symbol "X".
  • Observation(s).Assessments and observations are
  • depicted as the symbol "O".
  • XOXOXOXOX

Experimental design 49.

  • Groups.Each group is indicated on a separate line.
  • Most importantly however, the manner in which groups are assigned to the conditions can be indicated by a letter:
  • "R" represents random assignment,
  • "N" represents non-random assignment (i.e., a nonequivalent group or cohort)
  • "C" may represent an assignment based on a cutoff score.
  • Group 1:ROXO
  • Group 2:NOXO

Experimental desi