Gather & Analyze Evidence

Overview

Evidence of learning shows the degree to which students are meeting stated learning outcomes, including their ability to demonstrate knowledge, skills, and attitudes (KSAs).

The central question at this stage is: To what extent did students achieve the intended outcomes? Programs might answer this by analyzing improvement across multiple drafts of an assignment, tracking performance over time, or measuring learning gains through pre- and post-assessments.

Approach

1. 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.

2. 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.

3. 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.

Key Considerations

When gathering and analyzing evidence of student learning, consider the following:

Characteristics

Systematic enough to support interpretation, with a clear approach to collecting, organizing, and analyzing evidence.
Attentive to patterns and variation, rather than relying only on averages or isolated examples.
Focused on strengths as well as areas for improvement, providing a balanced understanding of student learning.

Connections

Clearly connected to the learning outcomes being examined, so the analysis answers a meaningful question about student learning.
Contextualized, recognizing relevant differences in courses, students, modalities, or other circumstances when interpreting findings.

Engagement

Collaboratively interpreted where appropriate, allowing multiple perspectives to inform conclusions.
Used to generate actionable insights, rather than collected primarily for reporting or compliance.

Examples of Evidence

Evidence may take many forms. Courses and programs are not expected to provide every type of evidence listed below. Depending on the context, one or more of the following may be appropriate:

Summaries of student learning evidence connected to specific learning outcomes.
Rubric results or analyses of student work.
Pre- and post-assessment findings.
Qualitative analyses of student work, reflections, or other evidence.
Disaggregated or comparative analyses where relevant and appropriate.
Documentation of faculty conversations interpreting findings.
Identification of strengths, patterns, gaps, or questions emerging from the evidence.
Recommendations grounded explicitly in findings.

Resources and Tools

Chapter 10 in Meaningful and Manageable Program Assessment (2017) by Laura Massa and Margaret Kasimatis
Explains how to organize, summarize, and present assessment evidence so programs can better interpret student learning data and use it to inform improvement.
A New Decade for Assessment: Embedding Equity into Assessment Praxis (2020) by Erick Montenegro and Natasha Jankowski
Explores how equity minded assessment practices can help educators examine structural inequities in student learning and use assessment to support more inclusive educational environments.
Becoming a Critically Reflective Teacher, 2nd ed. (2017) by Stephen Brookfield
Discusses how educators can use critical reflection to examine their teaching practices, question assumptions, and improve learning by considering multiple perspectives, including those of students and colleagues.
Qualitative Inquiry and Research Design: Choosing among Five Approaches, 2nd ed. (2007) by John Creswell
Outlines five qualitative research traditions and describes how researchers design studies, analyze data, and interpret findings within qualitative inquiry.

Questions About Evidence of Learning?

Whether you're collecting and analyzing quantitative or qualitative student data, we're here to partner with you to consolidate and make sense of the gathered information. Let us support you in synthesizing data to improve teaching methods.