Analyze and Summarize Data
Using data analytical tools such as Excel offer several built-in functionalities to summarize and analyze assessment data:
- Sum: Adds values from selected cells to calculate totals.
- Average: Computes the mean score for a criterion.
- Standard Deviation: Measures how spread out the data points are from the mean.
- Frequency: Counts how often a specific score occurs using the COUNTIF function.
- Percentage: Provides a clear representation of data distribution.
When analyzing data, consider whether you are looking to understand a trend over time or a snapshot at a specific moment. For assessment purposes, it can be helpful to have baseline data to track changes over time. If baselines are unavailable, consider using benchmarks, such as data from similar programs, to improve your analysis and interpretation within your specific context.
Identify Strengths, Weaknesses, and Gaps
Reflecting on student learning outcome data helps instructors identify what was achieved and where improvements are needed.
To gain a comprehensive understanding of student achievement, instructors and programs should triangulate assessment data as much as possible. This may involve reviewing both direct and indirect methods of assessing student learning, such as
- Student performance on assignments and activities designed to assess learning outcomes directly
- Evaluation of course materials and assignments for clarity, coherence, content quality, and appropriate level of challenge
- Informal or formal surveys
- Classroom assessment techniques
- Mid-course feedback (e.g., small group analysis)
- End-of-term focus groups
- Course evaluations (CTECs)
- Learning analytics from Canvas
By understanding student learning from different perspectives and holistically, instructors and programs can make informed decisions about targeted improvements to instruction as well as to course and curriculum design.
Make Recommendations
A successful assessment process involves gathering meaningful data, interpreting the results, and making strategic improvements based on evidence of student progress to achieving learning outcomes. The ultimate goal is to use this data to inform decision-making. Recommendations play a crucial role in this process, and when grounded in accurate data, analysis, and interpretation, they help guide targeted interventions that lead to meaningful improvements.
Ensure your recommendations are well-organized, supported by clear evidence, and presented in accessible formats such as visualizations, graphs, or summary tables. By following this approach, educators can effectively use assessment data to enhance student learning outcomes at both course and program levels.