Working with Direct Evidence

Setting benchmarks

The next decision to be made is to set your benchmarks. What score on the assignment or set of MC questions indicates that students have “met” the objective? Would you be satisfied with an individual student scores of 75%, or would you expect a 90%? According to Linda Suskie (2012), the benchmark depends on the objective. In some cases, a 75% might be enough. In other cases, such as nurses learning to do injections, you probably want your benchmark closer to 100%.

The next question to address is the level of overall performance you will accept as evidence that your students have “met the objective.” Suskie suggests that you do some further investigation on any rubric criteria or test questions for which fewer than 50% of students reached your benchmark.

Displaying data

The way that you display your evidence has an impact on how easy or difficult it is for you to interpret it. For example, percentages are helpful only for large numbers of students (roughly over 25 or 30). If you have fewer students than that, numbers will be easier to interpret. For large numbers, convert them to percentages to make them easier to interpret. You may also want to sort the data in a meaningful way, perhaps from highest to lowest, to highlight areas you want to attend to.

See an example below.

Questions? Contact the Schreyer Institute for Teaching Excellence at assess@psu.edu.


Assessing a psychology program – setting benchmarks, displaying data and interpreting results

Benchmark
We expect that 75% of our students to score excellent or very good on each criteria. Although the assignment includes elements of communication, at this point we are considering the content and ability of students to evaluate the research, so only those elements will be considered in this example.

 Results
73 student projects were scored using the rubric, with the following results.

Excellent

Very Good

Adequate

Needs Attention
Title Page

32%

52%

13%

3%

Rationale

15%

60%

22%

3%

Methods

32%

44%

18%

6%

Results

7%

15%

52%

26%

Conclusions

9%

35%

38%

18%