Designing Effective Assessment
Design/select appropriate student learning goals:
- Differentiate between student learning goals and other possible program, course, or teaching goals.
- Recognize the basic components of an effective written student learning outcome when evaluating SLOs for use in assessment planning.
- Explain the difference and relationship between program SLOs and course SLOs.
- Formulate a learning outcome as a change in attitude, aptitude or behavior that a student can describe or demonstrate after participating in a program or learning experience.
Employ concepts of cognitive, behavioral, or affective development in drafting SLOs:
- Describe the characteristics of the four major stages of cognitive development based on the Perry Scheme.
- Evaluate SLOs from the perspective of Bloom’s hierarchy of cognitive processing and stages of knowledge development.
Differentiate among types of evidence collected during teaching activities:
- Contrast the use of grades versus assessment data in higher education.
- Differentiate between direct and proxy evidence of student learning.
- Contrast the role of formative versus summative data.
Design or select appropriate assessment devices, measurement tools and measures:
- Differentiate between the scoring rubric and the assessment device, e.g., a case study or essay.
- Describe examples of the various assessment devices that can be used to collect assessment data, e.g., observations of performance or behaviors; examination of written or visual artifacts.
- Apply the concepts of criteria, validity, performance levels, standards, and reliability in constructing and implementing assessment rubrics.
Analyze student data using a given rubric or measurement tool:
- Demonstrate effective scoring and analysis of student work using a given rubric.
- Describe the advantages and disadvantages of norm-referenced and criterion-based standards in evaluating student performance.
- Contrast the use of mode versus mean in reporting assessment results and identifying performance distributions.
- Examine assessment data across sections for inter-rater reliability.
- Triangulate data using direct and indirect sources.