Introduction to Learning Outcomes

This course explores the development and use of well-articulated learning outcomes to generate meaningful data.

Core Lessons

Developing Intended Learning Outcomes

Assessing Student Learning Outcomes

Using Assessment Data for Decisions

Task Modules and Exercises

Writing Intended Learning Outcomes for Individual Courses: Explores techniques and tips for writing intended learning outcome statements for individual courses.

Intended Learning Outcomes at the Institutional and Program Level: Explores the development of institutional and program-level outcomes by aligning course-level outcomes with the mission, vision, core values, goals and strategies of the program and/or institution.

Exit Test Analysis: Demonstrates how to measure student learning gains by analyzing and interpreting exit test results.

Pre-and Post-test Evaluations: Demonstrates how to evaluate results for pre- and post-tests to assess learning gains.

Portfolios for Learning Assessment: Demonstrates the use of student portfolios to assess evidence of student learning. 

Using Proxy Measures: Demonstrates the use of indirect measures of student learning to support direct measures and inform decisions.

Knowledge & Skills Taught 

  • Understanding and differentiating cognitive, affective and psychomotor learning domains

  • Characteristics of outcomes statements

  • Writing action-oriented statements

  • Understanding direct and indirect evidence of student learningnderstanding direct and indirect evidence of student learning

  • Developing measurable outcomes

  • Identifying and articulating measurable and observable skills, behaviors or dispositions

  • Analyzing and interpreting exit test results

  • Calculating learning gains by using  pre- and post-test analysis

  • Using portfolios as repositories of student learning

  • Using portfolios as tangible evidence of student learning

  • Using proxy measures in analysis

  • Compiling proxy measures of student learning

  • Comparing characteristics of a sample with the population

  • Using practical significance in analysis

 Course fee: $700 ($600 for AIR members)

Download a registration form (PDF) to mail or fax.