How to do your research presentation

1. How to do your research presentation Research Methods IRE2002Y Radhakrishnan

2. Two elements of your research presentation • Content • Form

3. Content of your research presentation • Explain the logic of your Hypothesis • Describe how you tested your Hypothesis • Make logical inferences from research on your hypothesis

4. Explaining the logic for/against your hypothesis • Why the variables in your hypothesis are related OR • Why the variables in your hypothesis are not related

5. How to explain why two things are related • Create a good general impression • Conceptualize parts

6. 1st step to explaining why two things are related • Create a good general impression via graphic or model Extraversion is related to non verbal skills + NV Skills Extraversion

7. How to explain why two things are related • √ Creating a good general impression • Conceptualize parts

8. 2nd step to explaining why two things are related • Break down process/conceptualize parts • Give brief definition of each variable to illustrate how they are connected • Illustrate an example of the process • Cite empirical research

9. Example: Brief definition & breaking down the process

10. Example brief definition of first variable • Non-verbal Skills • E.g., Ability to perceive & interpret emotions accurately • Examples • e.g., ability to decode/encode • tone of voice, • eye contact, • facial expressions cite previous research on measurement here

11. Example brief definition of second variable • Extraversion • tendency to be frank, talkative, fun loving, sociableacross different types of situations & time • Example items (from Goldberg IPIP) • I am interested in people • I start conversations • I talk to a lot of different people at parties • I don't talk a lot.

12. Extraverts have better non verbal skills because they have more social experiences + + NV Skills Social experiences Extraversion Cite previous empirical/theoretical research on hypothesis here

13. More social experiences helps practice old skills or develop new skills Practice old skills + Social experiences + Develop new Skills Cite previous empirical/theoretical research on hypothesis here

14. Extraverts have more social experiences which help them practice old skills or develop new skills which in turn improves NV skills Practice old skills + + + Social experiences Extraversion NV Skills + + Develop new Skills Cite previous empirical/theoretical research on hypothesis here

15. Example of how to break down the process by giving an illustration of the process by using an empirical study

16. Specific & difficult goals improve performance Performance Goal Specificity & Difficulty Cite previous empirical/theoretical research on hypothesis here

17. Describing the empirical Study (XX ??) demonstrating how specific & difficult goals improve performance • Unskilled, uneducated loggers paid at piece rate were randomly assigned to one of two groups

18. Explaining how the research illustrates the relation between specific & difficult goals & performance Do your best goals • No external standard for • Performance • Performance defined • individually Low Performance Specific & Difficult Goals Clear performance standard Hi Performance Cite previous empirical/theoretical research on hypothesis here

19. Explaining the logic for/against your hypothesis • √ Why are the variables in your hypothesis are related OR • Why are the variables in your hypothesis not related

20. How to explain why variables are not related • State relation/hypothesis • Identify reason for why variables are believed to be related • Identify limitations of reasoning for hypothesis • Explain the reason for the counter hypothesis & how that reason is supported with empirical evidence

21. 1st step to explain why variables are not related • State Hypothesis verbally & graphically • e.g., Participation results in more difficult goals (cite previous empirical research here)

22. 2nd step to explain why variables are not related • Identify reason for why variables are related • Participation results in more difficult goals being set because supervisors do not know the abilities of subordinates (cite author of logic)

23. Assumption of the original Hypothesis Subordinate knows own Ability Participation Difficult goals = Supervisor does not know Subordinate Ability No Participation = Easy goals Cite researcher who questions assumption here

24. 3rd step to explain why variables are not related • Demonstrate limitations of reason behind why variables are related • Assumes that supervisors do not know the abilities of the subordinates and so assign easy goals Cite researcher who questions assumption here

25. 3rd step to explain why variables are not related • Explain the reason for the counter hypothesis & how that reason is supported with empirical evidence • When supervisors know the abilities of subordinates, participation does not result in more difficult goals as shown in results of study x conducted by xx in xx....

26. Explaining the reason for the counter Hypothesis Supervisor does not know Subordinate Ability Easy goals No Participation = Supervisor knows Subordinate Ability No Participation = Difficult goals

27. Describing how the empirical research (xx, ??) supports the counter hypothesis

28. What we covered so far...what’s next √ Your Hypothesis Describe how you tested your Hypothesis Inferences from research on your hypothesis

29. Describe how you tested your Hypothesis • Method • Participants • Measures • Procedure • Results • Describe Data analytic techniques used • Graphs/Tables of results obtained • explain how they support/do not support the hypothesis

30. Example Description of Participantsfrom Convenience Store Study

31. Who was observed in each store Descriptive title of the type of participants • 1319 clerks • Mostly urban stores • 44% male clerks Sample size, relevant demographic characteristics with frequencies/mean info where possible

32. Response Rate of Participants Descriptive title of the feature of the sample • 74% of women participating in a women-only leadership development program

33. Demographic Characteristics of Participants Descriptive title of the feature of participants illustrated in slide • Average Age=40 • Range=26-57 • 92% White • Avg. Salary =~78K (SD= ~32k) Sample size, relevant demographic characteristics with frequencies/mean info where possible

34. Family Status Characteristics of Participants Descriptive title of the feature of participants illustrated in slide • 50% had children under 18 yrs • 71% in committed relationships Sample size, relevant demographic characteristics with frequencies/mean info where possible

35. Example Good & Bad Descriptions of Procedure

36. (good)Stratified sample of stores 2 Countries 1st Division 10th Division ........... 18th Division ........... 1st District ........... 50th District ........... 72nd District 1st Store .............. 4th Store ............... 8th Store 576 stores in total

37. (not so good)Procedure • Faxed questions to participants a few days before interview • Pilot tested interview qs on 28 women managers • Tape-recorded and transcribed each interview

38. Example Description of Measuresfrom Convenience Store Study

39. Measurement of Clerk Image Brief description of Measure • 3 items rated by observers on a yes/no scale (reliability=??) • Was clerk wearing a smock? • Was smock clean? • Was clerk wearing name tag? Shorten questionnaire; give examples of items, reliability info, cite previous research on measures

40. Measurement of Store Stock Level Brief description of Measure • Extent to which shelves, snack stands & refrigerators were fully stocked • Rated on 5-point Likert scales Shorten questionnaire items, give examples of scale & Reliability info if relevant; previous research on measures here

41. What was observed in each store Brief description of Measure • 11805 transactions • 3 month observation period • For each of the 576 stores • 1 day + 1 swing shift • 25% of stores observed during night shift • 1-20 transactions/visit • Up to 60 transactions/store • 75% male customers Establishes reliability of measure: describes number of measurements, length of measurement, time of day of measurement

42. Describe how you tested your Hypothesis • √ Method • Participants • Measures • Procedure • Results • Remind audience of Hypothesis • Describe Data analytic techniques used • Present results in graphs/tables • explain how they support/do not support the hypothesis

43. Example of Results Section from Convenience Store Study

44. Analysis to test whether line length predicts the positive emotions of a clerk Type of analysis conducted to test hypothesis (reminds audience of hypothesis) • Clerk as unit of analysis (n=1319) • Hierarchical multiple regression • Dependent variable=positive emotion Brief description of key components of analysis, indicate preliminary combinations here

45. Line length predicts a clerk’s positive emotions Title indicates support/non support for hypothesis Visual & numerical Display of Results Short description of graphic display of results • Yes, line length adds 3% of variance • Line length negatively predicted display of positive emotion β=.-14 p<.001

46. Describe test of hypothesis visually & orally • Present information numerically (e.g., via means, frequencies, correlations) & describe orally/written phrases • Use graphics (e.g., bar charts, pie charts, line graphs) and interpret orally or w/ short phrases

47. What we covered so far...what’s next √ Your Hypothesis √ Describe how you tested your Hypothesis Inferences from your research on your hypothesis

48. Inferences from your research • What do your results imply for future research? • What research would help you understand more about the hypothesis

49. What kinds of information will help you know more about your hypothesis? • Should future research • Test reasons for why hypothesis is true? • Test reasons for why hypothesis is not true? • Test reasons for why hypothesis is true in some situations but not in others?

50. 1st Type of Proposed Research • Test explanations for hypothesis • Identify how to measure the (inner) explanatory variables and how to establish their connection to those of the hypothesis