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Huma Haroon 1.pptx research methodology presentation
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- 2. We will bediscussing… INTERNAL VALIDITY THREATS TO INTERNAL VALIDITY STRATEGIES TO ENHANCE INTERNAL VALIDITY
- 3. INTERNAL VALIDITY Internalvalidity refers to degree of confidence that results happened due to treatment only and not influenced by other factors. Validity in research means to what extent the experiment delivers the true results. High Internal validity means that the study’s findings are trustworthy. In simpler terms: Did the experiment really test what it was supposed to test?
- 4. INTERNAL VALIDITY Example: Suppose you’re testing whether a new teaching method improves students’ test scores. If the students’ scores improve, you need to be sure it’s because of the teaching method and not because: They already knew the material. They got extra help outside of class. The test was easier than usual.
- 5. THREATS TO INTERNAL VALIDITY HISTORICAL EVENTS MATURATION TESTING INSTRUMENTATION SELECTION BIAS ATTRITION STATISTICAL REGRESSION
- 6. History Something happensduring the experiment that affects the outcome but isn’t related to your treatment. Example: You’re testing a diet plan, and halfway through, there’s a health campaign on TV about eating healthy. People might change their eating habits because of the campaign, not your diet plan. Maturation Changes happen naturally over time, not because of your experiment. Example: You’re studying how a reading program helps kids improve. But kids naturally get better at reading as they grow older, so it might not be the program causing the improvement.
- 7. Testing The actof taking a test more than once can change how people perform. Example: You give a pre-test, then teach something, and then a post-test. If students do better on the post-test, it might just be because they got familiar with the test format, not your teaching. Instrumentation Changes in how measurements are taken affect results. Example: You use two different tools to measure stress levels in an experiment, and they give slightly different results. This inconsistency can mess up your findings.
- 8. Selection Bias The groups in your experiment are not equal to begin with. Example: You’re comparing two classes to see if a teaching method works, but one class already has higher-performing students. That difference can affect your results. Attrition (or Dropout) Participants drop out of the study, and it affects the results. Example: In a weight-loss program, people who don’t see results quit, leaving only the successful cases. It looks like the program worked, but the data is biased.
- 9. Statistical regression Extremeresults naturally move closer to the average over time. Example: You pick students with very low test scores to test a program. Even without the program, their scores might improve because they were unusually low to start with.
- 10. STRATEGIES TO ENHANCE INTERNALVALIDITY RANDOM ASSIGNMENT Using random assignment to distribute participants across groups helps ensure that the group are comparable. CONTROL GROUP Including a control group that does not receive the experimental treatment can help isolate the effect of other factors.
- 11. BLINDING Keepingparticipants and researchers unaware of group assignment can help reduce bias. CONSISTENT PROCEDURES Standardizing the way the experiment is conducted for all participants can minimize variability due to Procedural differences. PRE TEST AND POST TEST DESIGNS Using pre test and post test can help researchers to measure changes more accurately.
- 12. References Campbell, D.T., & Stanley, J. C. (1963). Experimental and quasi- experimental designs for research. Houghton Mifflin. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage.