Three essential pieces are necessary to ensure that students exceed learning expectations and make continuous growth. These pieces are high expectations, a school culture that prioritizes productive relationships, and data-driven decision making.
Data-driven decision making fits like a puzzle piece that connects high expectations and relationships. Students are able to meet or exceed a school’s expectations when immersed in a school with instruction that is research-based and effective. Further, relationships with students and parents are likely more positive when teaching is sound and produces results. Therefore, data-driven instruction is an essential component of a quality school environment.
What Data Should Teachers Be Looking At?
Data-driven instruction has long been a hallmark of an exemplary school. Time is a resource that is limited. Given the definite confines of time available, this precious resource must be used to its fullest for quality, purposeful, and relevant instruction. Instructional methodologies must produce results. Practices that are not working should be refined or stopped so that time is used in the best way to improve student learning and growth. While a focus on data-driven instruction is certainly not new to most educators, teachers and schools are having to rethink what data is essential to measure instruction in this new online world that PK-12 teachers were suddenly sent into.
To begin determining what data should be examined, teachers must first determine the essential standards and learning targets. Teachers must map the desired destination before monitoring progress along the way. Given this, assessments must be valid and reliable. That is, the assessments need to measure what is taught and results should be reproducible over time. These tools to gauge learning should be aligned and measure the learning targets. Additionally, ways to protect academic integrity must be considered so that data from the online environment is valid.
In considering which data to disaggregate, schools and teachers should prioritize and focus. By focusing on a few essential markers, educators are able to quickly examine key formative data to make sure they are on target to meet strategic goals. Formative data must be monitored along the way before summative assessments take place. Instruction can be revisited through alternative methods and remediation can occur before any summative assessments when formative data is used appropriately to inform instructional decisions.
This academic data could be class, school, or district benchmark assessments that measure all essential skills to that point throughout the year. Educators need to examine overall performance, individual growth, and subgroup performance when examining benchmark data. This data, in addition to some reading diagnostic tests like the PALS assessment, will be sufficient to gauge student mastery for most students.
Academic achievement data is not the only category to consider when assessing online instruction. Data related to accessibility, equity, engagement, and student retention must also be considered. To help ensure accessibility and equity, consider a consistent and organized aesthetic for each learning module. Teachers should try to minimize the number of clicks required to access content.
Further, directions and organization should be clear. Make content accessible to students by ensuring no specialty software is required to access any instructional components. Two core measures can be used to assess accessibility and equity. These measures are surveys completed by stakeholders, including parents and students, combined with objective course reviews completed by colleagues and supervisors. Feedback of these types are data, and most educators want to know how they are doing. Feedback is valuable, and teachers need to try to be objective and not take constructive feedback in a personal way. This idea is easy to state, but can be a challenge for most people. Building trust and transparency are keys to establishing a culture of constructive feedback.
Engagement and retention data can be found within the settings of most Learning Management Systems (LMS). Teachers can view the amount of interaction time with assignments, the log in times of students, and students who continue to be active in the class. Assignments should be written so that each assignment is essential to learning and requires higher-level thinking that will lead to heightened engagement. Engagement and retention data can also be qualitative in nature in terms of notes from stakeholder comments during personal phone calls and synchronous meetings. Data should be monitored and used to inform future decision-making.
Schools should aim to have academic progress results to be commensurate to in-person instruction. This goal is lofty, but it should be the aim. Initially assess student performance by comparing prior in-person learning with virtual instruction. Next, virtual data should be compared for upcoming years. This process will inform the teacher as to whether online instructional practices are improving over time.
How to Utilize Data to Improve Online Instruction
Data is only effective when it is used to inform decision-making. For this reason, too much data is a problem as it can overwhelm and end up not being used. Schools and teachers must decide which core pieces of data will be monitored to gauge student academic progress and engagement.
Further, data should be used as formative means throughout the year. Formative assessments are key to this data. Dissecting summative data in the form of end-of-year test data and summative grades is like an autopsy. This data may benefit future students, but does not help the current students in any way. With this in mind, formative data is often much more valuable in improving online instructional practices and informing decision-making. Formative data will help schools remain focused on summative goals.
Teachers can disaggregate achievement data by standards to see which lessons were effective and which were not as effective. Lessons that need improvement should be revised or taught using alternative means. This academic data can also inform differentiation and remediation groupings. Combining this data with feedback from stakeholders can help teachers decide which online instructional practices and formats are most helpful. By using data appropriately, teachers can consistently improve their online instructional practices.