Developing the Skills to Identify, Sort, and Implement Relevant Student Data
Data-driven instruction has been a massive pedagogical shift during the last decade. Instead of looking at assessments as the end goal of a unit or course, assessments are now being used to drive instruction and remediate student weaknesses.
Under the mandates of the No Child Left Behind legislation, using data to steer instruction was largely seen as "teaching to the test." Many educators saw this quick and sudden shift toward student percentages and passing rates as a bureaucratic band-aid that didn't necessarily reflect their students' abilities.
However, this is not the true purpose of data-driven instruction. When used in combination with the goal of identifying specific student weaknesses in order to build skills, this model is highly effective in closing the achievement gap. Let's examine this cycle of data acquisition, analysis, action, and reflection that is designed to bolster every child's achievement.
How to Use Student Data to Effectively Drive Instruction
Collect Data via Formative and Summative Assessments
In order to analyze student performance, proficiency, and needs, data needs to be collected for the student. Formative assessments, which involve gathering information in order to monitor student learning and progress, can take on many forms. A great data collection tool is to give a pre-test before a unit to assess what students do or do not already understand. This data gives your class a baseline reading to see which specific areas need focus.
Formative assessments are low-stakes, and provide ongoing feedback to the instructor about student progress. For example, students could read a text independently, then complete a "think/pair/share" activity where they focus on a specific concept or skill. By monitoring students' conversations, an instructor will clearly be able to identify which students need further assistance with the topic.
Exit tickets are also quick end of class formative assessments that give the instructor immediate feedback on the day's topic. The instructor asks the class a question based on the day’s content, and students must turn this in before exiting the class. This simple activity can give the instructor immediate feedback about what areas may need further reinforcement during the next lesson.
Summative assessments are used to evaluate students at the end of a chapter, unit, or course. They are larger in scale, and provide data after the course of instruction. This type of data can be used to alter instruction for the next cycle of the course, but may not always be used for day-to-day adjustments.
Once you have your assessment data, recording the information is the next step. Meaningful data recording that can be done through online sites, or with written charts or Word documents, is the beginning of the cycle of data collection.
Tools such as an LMS allow you to administer formative and summative assessments, provide instant feedback, and can automatically house and visualize student performance data easily and in one place.
Analyze the Data You Collect
Now that you have students' assessment data, what do you do with it? Instructors need to ask several key questions when looking at the data, such as:
- What is this assessment measuring?
- What are the characteristics of the students who took this assessment?
- What conclusions can be drawn from this type of assessment?
These questions will help educators identify and isolate where students may have struggled with information. It may also reveal flaws within the assessment itself. For example, if an assessment was supposed to utilize map skills but the questions focused more on memory recall, the assessment isn't giving accurate data.
Decide What and How to Teach
In a group of diverse learners, your data will likely reveal that you have students who have several different instructional needs within one class. How do you address all of these students' needs effectively?
Flexible grouping allows educators to group students according to need and proficiency. If you have five students in your class who struggled with academic vocabulary on their pre-test, those students would be best suited working together on an activity that reinforced the meanings of vocabulary words. Teachers can also lead whole group instruction, and then have the students break out into smaller sub-groups to complete an activity related to an identified need.
Within flexible grouping, student-led groups are valuable for giving students the autonomy to work together to formulate questions, brainstorm, quiz their group, or teach their partners. This can provide a great deal of confidence to students who struggle with asking their instructor for assistance, and allows peers to step up for each other and take ownership over their learning.
Plan Your Lessons and Assessments Starting with Your Goals
Quality units begin by looking at the ending and building instruction backwards from the summative assessment. What is it you want students to be able to know and do by the end of your unit or course? By keeping the end in mind, you will be able to build lessons and formative assessments that create building blocks for you to collect data and scaffold skills over time.
Being organized during this process is key, since there are so many things to keep each lesson moving forward. A personalized lesson plan calendar, as well as local and state standards, are two pieces to help keep your year on-track for student success.
Teach, Assess, Reflect, Repeat
During the daily classroom grind, many educators forget to ask the essential question, "How do I know what my students learned today?" Without reflection, the data cycle loses its meaning. Effective reflection allows educators to honestly critique what went well and what could use improvement when trying to increase student performance.
You may have had a very creative and fun lesson, but if your formative assessment shows that students didn't learn a darn thing, then you need to re-evaluate where the disconnect occurred. By examining this data, you are beginning the data cycle all over again.