Testing 101: Quantitative Approaches to Assessment CTE – November 2, 2005 Noelle Griffin, PhD LMU Office of Assessment at Data Analysis

Test Design  Generally applies to more quantified approaches to assessment  Multiple choice or short answer question  More objective (vs. subjective) approaches to scoring than qualitative/performance-based assessment

Approaches to Assessment Through Quantitative Testing  Standardized/externally developed tests  Locally designed tests

Standardized Tests  Examples: ETS content area tests, GREs, FE exam  Benefits Statistical properties established Less draw on faculty time Comparison data available  Drawbacks $$ Comparability of content Timing

Locally Designed Tests  Benefits Content linked directly to Los Local control over scope/focus Adaptable to curricular changes  Drawback Lack of outside comparison data No established reliability/validity

Steps in Test Design  Identify “constructs”  Develop items  Pilot  Scoring  Tracking/benchmarking

Identifying Constructs  What are the general areas of knowledge or skill that you will be assessing in the test?  Will form “scales” or groups of items  Example: Learning Outcome = students will be able to identify and define the primary theories in psychology; Constructs = Psychoanalytic theory, behavioral theory, cognitive theory

Role of Constructs Learning Outcome Construct Multiple Items Construct Multiple Items

Drafting Items  For each construct, what are the specific concepts/information points central to that construct?  Draft items that address each of these concepts  All items addressing a specific construct = scale

Item Drafting “Tips”  Avoid “dual pronged” items (asking two questions at once)  Avoid confounding vocabulary or jargon with the concept you want to assess (e.g., select the answer that best represents operationalization of the primacy effect)  “Multiple response” items  Including adequate detractors

Test Quality  Pilot testing (trying out the test with a smaller group of students before full-scale implementation)  Issues of reliability and validity

Reliability  Does the test measure what it purports to measure consistently?  Most applicable: internal consistency, or how well the items “hold together”  Emergence of “scales”  Looking for “outliers”  Assessment office as resource

Validity  Is the test assessing what you say it is assessing?  Conceptually: Face, construct  Empirically (if possible): Criterion  Issue of student intent: Do students actually address the test with serious effort?  Ideas for making test meaningful

Approaches to Scoring/Analysis  Overall vs. scale scores  Percentage correct  Average score  Criterion-based/% meeting standard

Comparison Considerations  Cross-sectional (comparing two groups at same time)  Cohort/time series (comparing different cohorts across time) Consideration of cohort effects  Longitudinal (looking at same group over time) Importance of matching pre/post

Additional Resources  Test Development (2001). P.W. Miller & H.E. Erickson. Miller & Associates.  Introduction to Test Construction in the Social and Behavioral Sciences (2003). J.A. Fishman & T. Galguera. Rowman and Littlefield Publishers.