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Par for the course in assessment planning
March 16th, 2010 by Michael Strait

It is important to recognize that it is “par for the course” to be disappointed in your first efforts to assess program level learning outcomes, and that it may take several trials before you begin to see results you believe in. But this does not mean you won’t be learning from your first several trials and making program improvements based simply on clarifying your intended learning outcomes and trying to measure them.

If you try to start by just selecting a new test to add at the end of a program, you can expect to waste your time and money and be disappointed with the results. You have a much better chance of seeing real benefit from the process and the results when you start by clarifying one really important learning outcome and asking how that outcome can be measured.

Once you think you have clarified the intended learning outcome and thought of ways you might measure it, it is time to experiment with measuring it. You can expect to learn from the first experiment that you still have more rethinking and refining to do on the both intended learning outcome and the methods of assessment, and then you will experiment again. You can expect to do this three or four times before you actually start to believe that you understand what you are trying to measure and how to measure it. You can expect that as you go through these iterations of trial and refinement of your intended outcome and assessment methods, you will also be consciously or unconsciously changing what you teach and how you teach.

Thus you can expect the first round of program improvements to come simply from engaging in the process of clarifying an intended outcome and experimenting with methods of assessment.

Finally, you will implement a re-conceptualized, retooled, and re-calibrated assessment plan and begin to collect evidence you believe in and that tells you something you want to know about how to strengthen student learning of the intended outcome and how to improve your program based on actual collection and analysis of data.


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