The students in any given classroom represent a range of learning needs—and students learn best when instruction is tailored to those needs. But while teachers know the one-size-fits-all approach often leaves students behind, time constraints can make meaningful personalization a challenge.
However, with the help of technology, teachers can now gather deeper insights into students’ needs to help them efficiently and effectively personalize instruction. This data-driven instruction empowers teachers to transform classrooms into dynamic environments where every learner can thrive.
This article explores 4 data-driven instruction strategies: unit pretests, digital quizzes, assessment choice boards, and grammar mini-lessons.
Key Takeaways
Data-driven instruction is the process of tailoring instructional content to the learning levels or learning preferences of your students. The process involves 3 main steps:
By ensuring course content aligns with students’ prior knowledge and is personalized to their needs, data-driven instruction leads to improved engagement—and better outcomes.
The following techniques are just a few ways teachers can use data about their students to provide personalized teaching.
One data-driven strategy begins with pretesting students’ readiness for each unit. A pretest is a diagnostic assessment that introduces the skills and content students will need to master in order to achieve the unit’s objectives. Students’ performance serves as a benchmark to help inform your choices about what content to cover and how to teach it.
For example, before teaching students how to write literary analysis essays, an English Language Arts (ELA) teacher could pretest students on literary devices and essay-writing techniques. If most of the class is unfamiliar with metaphor and imagery, the teacher incorporates those topics into the unit. If a handful of students missed questions on essay-writing basics, the teacher would plan small-group workshops or individualized lessons.
This strategy improves student achievement because it helps you cover the skills and content students need most. Without diagnostic pretest data, students missing prerequisite skills might be left behind. Conversely, if students have already mastered the skills, you can avoid them becoming disengaged or bored.
Tip: Write the summative assessment and the scoring guide or rubric before you create the pretest.
While a unit is in progress, teachers can also use more informal digital quizzes to conduct formative assessment and collect data about student learning over time. A digital quiz consists of a few questions—delivered via a testing platform or learning management system—to target the learning objectives from a portion of a unit. The data from these formative assessments helps teachers make short-term adjustments to teaching techniques and lesson content.
For example, a high school Physics teacher covering a unit on Newtonian mechanics could quiz students at regular intervals during the unit, such as after students learn about Newton’s First Law, Second Law, and Third Law. The digital format would provide the teacher with immediate results so that teaching adjustments can be implemented as soon as the next class period.
If most students struggle with a quiz on the First Law, the teacher would explain the concept in a different way or through a new medium (e.g., a video rather than a print source) before moving onto instruction about the Second Law.
One benefit of formative quizzes is the immediate impact on teaching efficacy. For example, TAO grades quizzes instantly, which creates more time for teachers to consider how the most recent teaching strategies affected learning and what techniques might work better during the next few class periods.
Another benefit on assessment platforms like TAO is the variety of question types, particularly portable-custom interactions that require students to do complex, interactive tasks that provide rich data about student understanding.
Data about your students’ interests and preferences can also help you offer robust choices for assessing skills and knowledge. An assessment choice board is a visual display of several options for demonstrating knowledge at the end of a unit. The teacher designs choices based on informal observations or formal polling of students’ interests or learning preferences.
For example, in a Grade 3 lesson on weather vocabulary, you could offer students different ways to show what they learned—for example, by creating vocabulary cards, writing a story or poem, or writing a paragraph.
Choice boards improve academic achievement because they allow students to engage more deeply in summative assessments. When students can choose how they demonstrate learning, they’re more invested in the final product.
You can also use data from student writing samples to create mini-lessons on the grammar skills your students need most. These 10-minute mini-lessons focus on a pattern of error—such as multiple run-on sentences—that you observe across multiple students’ writing.
Let’s say a teacher for Advanced Placement (AP) European History observed a pattern of apostrophe errors while grading practice essays. If multiple students repeatedly forgot or misplaced apostrophes, the teacher could spend 10 minutes during class reviewing apostrophe rules and sharing models of correct apostrophe usage.
Grammar mini-lessons improve writing achievement by breaking grammar concepts into manageable chunks that are easier to commit to long-term memory.
Tip: If commas are a concern, focus each mini-lesson on a single comma rule (rather than all the comma rules) to prevent cognitive overload.
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By implementing these 4 data driven instruction strategies—unit pretests, digital quizzes, assessment choice boards, and grammar mini-lessons—you can personalize your teaching to your students’ needs, to ensure that all learners remain engaged and can make meaningful progress.
For more information about data-driven instruction, please see Connecting the Dots Between Learning & Assessment Through Test Item Metadata, Reimagining Education Through Data Analytics in Assessment, and more articles in the TAO blog.
Examples of data-driven instruction include planning units based on diagnostic assessment data, making ongoing teaching adjustments based on quiz data, offering student-centered choices for summative assessments, and creating mini-lessons to target skills gaps.