HLP 6

Effective educators appreciate and find value in the diversity of today’s classrooms (McCray et al., 2021).  They understand that one test on one isolated day is not likely to give a full picture of a student’s abilities.  They also understand some assessments have biases that can provide false results.  When choosing the best assessments to gauge student learning and progress, educators must ask questions.  Specific prompts should address: What information is being gathered, what is the best method to capture information, and where and when will the student be comfortable enough to demonstrate knowledge?  The effective educator not only takes time to consider these questions, but does so through the lens of considering students’ individualized needs.

Effective educators get to know students, building relationships so they can tell or at least confidently ask students about their day or lives.  Through information gained via educator-student relationships, they understand some assessments need to be postponed or not administered at all.  To illustrate, if you had a car accident or perhaps got a speeding ticket on your way to school, you would likely want to postpone an administrator observed lesson for your “final evaluation.”  Yes, everyone should be able to compartmentalize and focus on the task at hand, but sometimes that is not possible for adults, and the same consideration should be given to children.  Therefore, effective educators contextualize the experiences and daily events students bring with them on any given day, and reflect on the validity of assessment results that might be affected (Riddle, 2017).

Similarly, educators who are considerate of cultures and support learning of all students incorporate input from family members (HLP 3) when determining the purpose of assessing students (Cioè-Peña, 2020).  When assessments are needed, educators and families collaborate to determine which assessments to administer.  Federal mandates require families to provide informed consent before testing (IDEA, 2004).  Just as skilled educators can interpret and explain data (HLP 5) to families, they also can explain the purpose of each proposed assessment and what the student will be asked to do during the assessment and under what conditions.

In the classroom, educators incorporate students in data analysis and interpretation. Students select work samples and explain why they believe they showcase their achievements. Educators value students’ expression and reflect with them to highlight strengths, areas of growth since the last reflection, and work collaboratively with students to develop goals.  Effective educators understand education is implemented with students not “to” them. 

It seems self-evident that educators who use student performance data to inform their decision-making, planning, and instructional changes would have a positive impact on student learning or behavior relative to peers who did not, yet this is an important research question to be addressed.  There are several empirical studies, including randomized control trials, where researchers documented impact on student learning outcomes across reading and mathematics domains following teachers’ inclusion of data-based decision making alongside their various instructional approaches.  Although this can make difficult the detangling of variability contributed by the act of data-based decision making alongside the specific instructional approach being used (usually explicit instruction), there is strong evidence for this HLP (Nelson et al., 2022).

To begin, Gersten and colleagues (2009) conducted a meta analysis including seven randomized control trials documenting the impact of different interventions including data-based decision making on the mathematics outcomes of students with disabilities.  Results were positive favoring students taught by educators who used data in their decision processes alongside explicit instruction and feedback.  Filderman and colleagues (2018) conducted a meta analysis including 15 studies exploring the impact of data-based decision making on reading outcomes of students with disabilities.  Results favored students taught by educators using data, which means they made statistically significant gains in their reading performance compared to peers taught by educators not using data in their decision processes.  In a follow up review, Filderman and colleagues (2022) found educators can successfully learn to become data literate and develop skills for implementation.  However, educators do not always do so (Datnow & Hubbard, 2016).  This analysis and discussion provided by Filderman and team is critical because many educators emerge from their preparation programs (or the street) without any specific skills for understanding data and making actionable decisions that lead to improved student outcomes.