Suppose you are developing a new scale called the 'Skepticism Index' to measure scientific literacy. Apply Cacioppo and Petty's correlation matrix approach by identifying two distinct, established variables you would measure alongside your index to validate it, and state the predicted direction (positive, negative, or near-zero Pearson's ) for each.
Question: Suppose you are developing a new scale called the 'Skepticism Index' to measure scientific literacy. Apply Cacioppo and Petty's correlation matrix approach by identifying two distinct, established variables you would measure alongside your index to validate it, and state the predicted direction (positive, negative, or near-zero Pearson's ) for each.
Sample answer: To validate the Skepticism Index, I would measure it alongside 'need for cognition' (predicting a positive correlation, as skeptical scientific inquiry requires thinking) and 'dogmatism' (predicting a negative correlation, as rigid belief systems oppose scientific skepticism). A correlation matrix showing these relations would support the scale's validity.
Key points:
- Application of correlation matrix approach to a new construct
- Identification of two established validation variables
- Theoretically justified prediction of positive correlation (e.g., with need for cognition or intelligence)
- Theoretically justified prediction of negative correlation (e.g., with dogmatism) or near-zero correlation (e.g., with socially desirable responding)
Rubric: Award full credit if the student names two distinct established variables (such as intelligence, dogmatism, need for cognition, or socially desirable responding) and provides a logically and theoretically justified correlation direction (positive, negative, or near-zero) for each variable in relation to a Skepticism Index.
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Research Methods in Psychology - 4th American Edition @ KPU
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Suppose you are developing a new scale called the 'Skepticism Index' to measure scientific literacy. Apply Cacioppo and Petty's correlation matrix approach by identifying two distinct, established variables you would measure alongside your index to validate it, and state the predicted direction (positive, negative, or near-zero Pearson's ) for each.