How to Use Technology to Differentiate Instruction in the Classroom

Differentiating instruction in the classroom is hard. But technology can help.

Teachers know that students learn best when they are working on material that is challenging enough that they require guidance and support but not so challenging as to be impossible—what psychologist Lev Vygotsky famously called the zone of proximal development, or ZPD. Yet, in a classroom of students who vary in terms of what they know and what they are ready to learn, targeting instruction to each student’s zone means understanding and addressing the needs of dozens of students—and that can be overwhelming.

In a 2008 survey, 43% of teachers agreed with the statement, “My class/classes in my school have become so mixed in terms of students’ learning ability that I/teachers can’t teach them.” The 2018 HMH Educator Confidence Report also revealed that using data to inform instruction—a key aspect of differentiated instruction—is a top concern among 45% of the educators who responded. Technology can help to provide a solution to teachers who struggle to differentiate instruction effectively.

The Challenges of Differentiated Instruction in the Classroom

Teachers need deep domain knowledge to differentiate.

One of the greatest challenges of differentiated instruction is that it requires deep domain knowledge—of the subject itself, of the potential ways students progress from one level of understanding to the next, of where students might get stuck, and of common gaps in students’ understanding. However, research by Washburn, Joshi, and Cantrell has shown that not all teacher education programs are preparing teachers with the detailed domain knowledge that’s required to differentiate.

Teachers need to identify students' ZPD to differentiate.

Up-to-date information about a student’s zone of proximal development is indispensable to determining what students should work on next, and that’s where formative assessment comes into play. Dylan Wiliam of the University of London has called assessment “the bridge between teaching and learning—only through some kind of assessment process can we decide whether instruction has had its intended effect.”

But administering and scoring formative assessments is time consuming, meaning teachers often need to choose between having timely, instructionally relevant information and actually teaching their students. The complexity of data analysis can also leave teachers data-rich but insight-poor if they have no way to filter through and visualize the information that’s most relevant to planning instruction for their particular students.

Teachers need to implement flexible grouping to differentiate.

Small-group instruction allows teachers to differentiate more efficiently by working with students who have common needs at the same time, as research by Chambers and colleagues has shown. Effective, harmonious grouping requires determining which students have similar ZPDs, common interests and learning preferences, and can get along together. Grouping is not a one-time event: groups should be reassembled flexibly as students learn more and their zones diverge.

Teachers need to identify resources to differentiate.

Last but not least, a challenge teachers face with differentiated instruction is that it requires them to identify instructional resources that target skills at the level that each group or individual student should be working on while taking into account a variety of other student characteristics that are relevant to choosing effective instruction. Carol Ann Tomlinson's list of relevant student characteristics includes background experience, culture, language, gender, interests, readiness to learn, modes of learning, speed of learning, support systems for learning, self-awareness as a learner, confidence as a learner, and independence as a learner. Without an organized repository of resources available to them, teachers can spend an inordinate amount of time searching for supplemental open educational resources (OERs) to meet student needs and interests—and OER materials typically do a poor job of providing guidance for differentiation.

Differentiated Instruction Strategies Using Technology

It’s no wonder that teachers find differentiating instruction a challenge! Instead of pre-planning and following a set instructional path, differentiation is a continuous cycle of evaluating needs, planning and delivering instruction around those needs, and re-evaluating progress to start the cycle over again.

While teachers must be at the center of this process, using technology to differentiate instruction can alleviate some of the burden, especially when it comes to saving time.

Technology can provide domain maps and potential learning pathways.

Digital and blended learning programs that rely on evidence-based maps of how students learn within a domain can help teachers better understand how current instructional goals relate to prior and future learning. For instance, HMH’s Into Math, Into Reading, Into Literature, and ¡Arriba la Lectura! core programs utilize learning spines that map out skills and knowledge in math and language arts from kindergarten through high school to help teachers track development over time.

Technology can identify students' ZPDs through computer-based formative assessment.

Computer-based formative assessments that provide group administration, automatic scoring, and curated reporting allow teachers to focus on moving students forward rather than testing and number crunching. Adaptive assessments target questions to a student’s level, providing more specific information about his or her zone in less time. Stealth assessments—like those embedded in HMH’s Waggle adaptive practice application—reduce the need for formal assessments by providing a constant stream of up-to-date information, which is reported out to teachers and used by the program to automatically adapt to student needs.

Technology for differentiated instruction can recommend groups of students in similar zones.

Using formative assessment data and records of student progress, grouping engines—such as Waggle's skill groups—can recommend how to organize students with similar skill needs for small-group instruction. Teachers can then adjust these suggested groupings based on their own knowledge of their students, and they can get updated recommendations for flexible regrouping as the program acquires more information. It also allows for content recommendations if teachers are looking for this.

Technology can identify resources targeted to student needs.

When the instructional resources of a program are organized against skills in a domain map, it’s much easier for teachers to find resources that address the skills students need to learn at the right level. Modular content enables teachers to pull out and recombine instructional resources that fit their classroom’s needs rather than constraining them to a strict scope and sequence that requires supplementation to reach all learners.

Effective teaching in today’s mixed classrooms often means differentiating instruction based on student needs—a challenge that can range from headache-inducing to nearly impossible without resources and support. Advances in differentiated instruction technology tools can help teachers meet the challenges of this worthwhile approach to instruction, automating some of the most time-consuming and cumbersome parts so they can focus on what matters most: the students in front of them.

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This blog, originally published in 2019, has been updated for 2023.

Differentiating Instruction With Technology

Learn more about how HMH’s Waggle program that help teachers differentiate both core and supplemental instruction in their diverse classrooms through formative assessments, insightful reports, targeted recommendations, and student-focused resources.