Two types of empirical questions

1. Two types of empirical questions • Descriptive • This kind of empirical question requires a researcher to describe some aspect of behavior • For example, a researcher might ask, What are people’s attitudes toward the homeless? • Causal • This type of empirical question requires a researcher to determine what causes something to happen • For example, a researcher might ask, Does stress cause people to have road rage?

2. Our studies • We want to know whether or not verbal estimate-based depth perception training benefits subsequent performance on verbal and active tasks? • In other words, we want to know whether or not such training causes better performance later on

3. Question • How do you determine that one thing caused something else to happen? • For example, how could we determine that a new training simulation improved performance?

4. A simple logical method • Collect data about current behavior • Change the suspected cause • Do not change anything else • Collect data about subsequent behavior • Compare data collected before and after the change was made

5. Example

6. Example • Pre-test painting ability • Provide training via simulator • Do not change anything else • Post-test painting ability • Compare pre and post-test data

7. Complications • The logical process outlined earlier is intuitive and straightforward • When studying behavior, however, several issues could occur that would complicate the interpretation of the data

8. Potential Complications 1 & 2 • Something other than the suspected cause changes • Something inside the participants changes • This is known as a maturation problem • Something outside the participants changes • This is known as a history problem

9. Maturation • Pre-test painting ability • The participant warmed up during the pre-test • Provide training via simulator • Do not change anything else • Post-test painting ability • Compare pre and post-test data • Is the difference due to training or warm-up?

10. History • Pre-test painting ability • Provide training via simulator • The simulator technician provides some advice • Do not change anything else • Post-test painting ability • Compare pre and post-test data • Is the difference due to training or advice?

11. Training, Maturation or History?

12. Potential Complication 3 • The initial data collection may bias participants • This is known as a testing problem

13. Testing • Pre-test painting ability • Certain aspects of painting are assessed • Provide training via simulator • Participants work hard on aspects of painting that will be assessed • Do not change anything else • Post-test painting ability • Compare pre and post-test data • Is the difference due to training or bias?

14. Training or Testing?

15. Potential Complication 4 • How one collects the Pre-Test data may differ from how the Post-Test data are collected • This is known as a instrumentation problem

16. Instrumentation • Pre-test painting ability • Test involves a door panel • Provide training via simulator • Do not change anything else • Post-test painting ability • Test involves a trunk lid • Compare pre and post-test data • Is the difference due to training or tasks?

17. Training or Instrumentation?

18. Potential Complication 5 • Sometimes the Pre-Test scores are extreme, so it is likely that Post-Test scores will be different, no matter what • This is known as a regression problem

19. Regression • Pre-test painting ability • A number of participants score abnormally low • Provide training via simulator • Do not change anything else • Post-test painting ability • Those low scoring participants score more average, while others stay the same • Compare pre and post-test data • Is the difference due to training or abnormal scores?

20. Training or Regression?

21. Solution • There is a simple way to capture these issues, if they occur • Include a control group • If Pre and Post-Test scores differ for both the experimental and control groups, then it is likely that the study was affected by one of these problems • This is known as having a confound in a study

22. A more complex method 1. Collect data about current behavior 2a. Experimental group - Change the suspected cause 2b. Control group - Don’t change the suspected cause 3. Don’t change anything else 4. Collect data about subsequent behavior 5. Compare data collected before and after the change was made

23. Example • Pre-test painting ability • Provide training • Via simulator (Experimental group) • Via standard method (Control group) • Don’t change anything else • Post-test painting ability • Compare pre and post-test data

24. No Confounds

25. Confounds

26. Confounds

27. Our studies • Experimental group • Pre-Test, Verbal Training w/ Feedback, Post-Test • Control group • Pre-Test, Verbal Training w/o Feedback, Post-Test

28. Potential Confounds • Maturation • History • Testing • Instrumentation • Regression