Ch 7 Validity

Yun, the newly appointed director of academic and instructional effectiveness at a university, aims to evaluate the university's effectiveness in preparing students for life post-graduation.
Existing measures evaluate student learning; however, Yun seeks to assess students' perceptions of university service.
A faculty and staff committee identified eight constructs related to college student satisfaction, which must be validated.

Definition: A construct is an ideational concept used to measure students' satisfaction, not tangible or observable.
Yun's test contains both homogeneous (single construct) and heterogeneous dimensions (multiple constructs).
Initial constructs include:
- Quality of education
- Civility
- Feelings of belongingness
- Appreciation of diversity
- Meta-decision-making

The test's validity had not been established; thus, Yun collected feedback from faculty experts after administering it to students.
Revisions led to:
- Reducing constructs from eight to five, combining civility and belongingness into the "culture of respect" construct.
- Cutting test items from 65 to 28 with some items removed based on expert feedback and validation.
- Adding items to ensure all constructs were adequately measured (e.g., appreciation of diversity).

Validity: A test's ability to accurately measure what it intends and provide useful results.
Importance: Validity is crucial for ensuring that a measure is both accurate and useful as discussed in Lissitz & Sammuelson (2007).
Related Concepts:
- Reliability (consistency of a test).
- Precision (the reproducibility of a measure).
Validation process should ascertain if a test measures the construct accurately before considering its reliability and precision.

Figures 7-1 to 7-4 depict the relationships between precision, reliability, and validity:
- High Precision, High Reliability, Low Validity.
- Low Precision, High Reliability, Low Validity.
- Low Precision, Low Reliability, High Validity.

Validity consists of three components, as identified by Cronbach and Meehl (1955):
- Content Validity: Examines whether items accurately represent the constructs being measured.
- Construct Validity: Evaluates how well a test measures the intended constructs and whether the constructs are adequately defined.
- Criterion Validity: Determines how well a measure predicts outcomes, either concurrent (current behavior) or predictive (future behavior).

Evaluates the accuracy of individual items in measuring the construct.
The wording of items and response scales significantly contribute to content validity.
Example: Items relating directly to college satisfaction should effectively measure relevant sentiments.
Experts can evaluate item quality and track the effectiveness of each item using a ratio-based approach.

Methods include:
- Expert reviews during construction and after revisions.
- Confirmatory factor analysis to ascertain that items contribute to the intended constructs.
Challenges include the need for a sizeable participant pool for analysis.

Focused on the accuracy and utility of measuring identified constructs.
Evaluated through expert consultation to ensure constructs are relevant and adequately represented (theoretical method).
Complemented by empirical methods such as exploratory factor analysis to validate identified constructs against data-driven analysis.

Discriminant Validity: Valid tests should differentiate between different groups relevant to constructs being measured.
Convergent Validity: Assesses whether measures correlate with independently established measures of the same construct.

A minimum of three items is recommended per construct for validity, but variability needed can differ.
Criterion Validity Types:
- Concurrent Validity: Validity of measures against established benchmarks for current behaviors.
- Predictive Validity: Validity of measures in predicting future behaviors based on current data.

Measures how valid a test appears to users; impacts willingness of participants to engage honestly.
Testing involves user perceptions and modifications based on feedback.

Challenges the tripartite model by emphasizing overall assessment of validity rather than segmenting validity types.
Advocates for holistic analysis of empirical and theoretical justifications as ongoing processes in test application.

Test Content Evidence: Ensure items effectively measure constructs.
Response Processes Evidence: Assess how varied test-taker populations interact with items.
Internal Structure Evidence: Correlate scores within and between related tests for construct validation.
Relationships to Other Variables Evidence: Apply theoretical and empirical evaluation of variable relationships.
Consequences of Testing Evidence: Validate that results yield useful insights without misuse.

Continuous assessment of validity is crucial for accurate results in both academic and applied measures.
The evaluation process enhances the integrity of the testing and consequent interpretations of the results.