Overview
When advocating for students, the use of iterative and continuous data analysis helps provide valuable insights around student learning progress and needs so that educators can identify actionable steps and strategies to improve processes for improvement. Likewise, when data analysis is used for advocacy, it can help drive further research to further advocate for meeting student needs.
As you move forward in making sense of your data analysis findings, ensure that you have collected and analyzed data that will tell the full story. Quantitative data analysis is often the primary method for identifying student trends; however, collecting and analyzing qualitative data through interviews or focus groups with educators, counselors, leaders, staff, community partners, or students will provide valuable insights about their experiences and the support they received or provided.
Once you have analyzed both quantitative and qualitative data, as a last step, compare the results from your quantitative data analysis with your focus group/interview data analysis. It is important to remember that as you compare quantitative and qualitative data to connect your initial goal for advocating. Use the guiding questions below to make sense of your overall findings.
Does the qualitative data support the quantitative data, or is it different?
What are the similarities and/or differences between the quantitative and qualitative data?
How does the qualitative data provide insight for or explain differences in learning performance among groups of students?
Finally, to effectively contextualize and make sense of your findings for advocacy, it is important to consider any previous research that has been conducted examining student progress to help you understand the practical implications and significance of your findings.