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Based on the team's findings, diagnose which type of interaction effect is present in this study, and explain how this pattern would look visually on a graph.
Case context: A research team conducts a factorial experiment to test the effects of a new study application (App vs. Traditional Book) and student motivation level (High vs. Low) on test scores. When compiling the results, they discover that for highly motivated students, the App leads to much higher test scores compared to the Traditional Book. However, for students with low motivation, there is virtually no difference in test scores between the App and the Traditional Book.
Question: Based on the team's findings, diagnose which type of interaction effect is present in this study, and explain how this pattern would look visually on a graph.
Sample answer: This scenario demonstrates a spreading interaction. In this case, there is a large difference in the dependent variable (test scores) between the App and Traditional Book at the level of high motivation, but little to no difference in test scores at the level of low motivation. Visually, this creates the characteristic spreading pattern where the difference in the dependent variable is only prominent at one level of the independent variable.
Key points:
- Identify the effect as a spreading interaction.
- Explain that there is a large difference in the dependent variable at one level (high motivation).
- Explain that there is little to no difference at the other level (low motivation).
- Relate these differences to the visual pattern expected on the graph.
Rubric: To earn full credit, the student must: 1) Correctly identify the pattern as a spreading interaction. 2) Explain that the defining feature is a large difference at one level (high motivation) and little to no difference at the other level (low motivation). 3) Connect this to the visual principles of graphing spreading interactions.
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Research Methods in Psychology - 4th American Edition @ KPU
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