Module 2: Compiling Data with an Equity Frame

There are many pieces of data that we collect to evaluate the strengths and needs of children with exceptionalities. Importantly, these data may represent children from historically marginalized backgrounds differently, given that assessments of education and mental health are often developed based upon cultural expectations of majority cultures (for example, assessments are often normed on majority-White samples). The Relay School of Education suggests three principles of equity-centered data analysis: (1) practicing self-awareness when analyzing data, (2) taking context into account, and (3) collaborating with others to meet the diverse needs of students. Educators should understand their own biases and how these may result in biased interpretation of data. Educators should take into account the context in which the data were collected as well as the original purpose and design of the assessment, and the cultural context of the child. Lastly, educators should collaborate with other professionals to gain a holistic view of the child’s strengths and needs, particularly those that may not be reflected in traditional data analysis due to a cultural mismatch. Considering data from an equity lens will look different based upon your unique school community - it is essential to reflect on gaps in your own school community related to using data in an equitable manner. Read the CDE page “Understanding Context: Demographics and Data” and complete the reflective activities to gain a deeper understanding of what data are collected in your school and how these data may misrepresent students.