By Zach Vander Veen
We often spend a great deal of time in education debating the promise of technology in the classroom. Terms like “personalized learning,” “AI-driven instruction,” and “adaptive learning” become buzzwords. Educators and policymakers alike gaze at algorithms with a mix of hope and wonder, imagining how software might reshape how students think. It’s easy to get excited about the “next big thing” and to expect technology to perform like magic.
It’s worth pausing to ask a more practical question: what is educational technology—EdTech—actually best at doing, consistently and reliably, right now? Which tasks can it support every day, and which should remain primarily human responsibilities?
A useful way to answer that is to consider how we learn. Bloom’s Taxonomy provides a clear framework for this. At its base are two essential objectives: Knowledge and Comprehension. These foundational skills—remembering facts and understanding concepts—are prerequisites for higher-order thinking. You can’t analyze, evaluate, or create meaningfully without a solid base of knowledge and comprehension to draw from.
Cognitive scientists have identified several effective methods for mastering these foundational skills. One of the most powerful is retrieval practice: the repeated act of recalling information from memory after initial learning. When learners repeatedly bring information into working memory and then reconsolidate it into long-term memory, retention improves. Spaced repetition, low-stakes quizzes, and focused practice are some practical forms of this principle.
Machines and algorithms excel at supporting those lower levels of Bloom’s Taxonomy. Digital flashcards, automated quizzes, and adaptive review systems can present material in precisely timed intervals, track correct and incorrect responses, and provide repeated retrieval opportunities tailored to each learner’s pace. For memorization and automaticity, software is not only efficient but often more consistent than human-administered practice.
Where technology struggles is with the upper levels of cognition: abstract reasoning, nuanced discussion, moral judgment, deep synthesis, and creative problem-solving. These higher-order skills rely on subtle human capacities—empathy, cultural context, open-ended questioning, and the ability to read and respond to complex social cues—that current algorithms cannot fully replicate. That’s not a flaw so much as a reality we should plan around.
And that is perfectly fine.
Time is a finite resource in classrooms. When teachers and students delegate lower-level, repetitive learning tasks to software, they free up valuable time and attention for activities that require human judgment and interaction. With core facts and basic concepts practiced and retained through EdTech, classroom time can shift toward rich discussion, critical analysis, project-based learning, and mentorship: the work that benefits most from human presence.
During my time teaching social studies, for example, students needed a solid grasp of key facts about the Constitution, major historical events, and civic structures before they could engage in meaningful debate or construct well-reasoned essays. Programs designed for memorization—flashcards and gamified review tools—made those fundamentals more reliable. Software like Quizlet helped my students attain a level of automatic recall so we could spend class time diving into interpretation, connecting history to contemporary issues, and developing arguments.
Beyond academic gains, EdTech also created space for a critical element of effective teaching: relationship-building. When routine communications and administrative tasks are automated—notifications, basic progress updates, scheduling reminders—teachers can reserve their time for individual conversations, coaching, and attention to students who need it most. That human connection is the engine behind motivation, engagement, and deeper learning.
There is another practical benefit worth emphasizing: efficiency. Thoughtfully implemented tools reduce busywork. Early in my career I spent significant time on repetitive tasks like calling every parent to share baseline information. Automated messages, emails, or app notifications now handle much of that, allowing teachers to focus on purposeful interactions. I estimate a substantial portion of educators’ day—perhaps thirty percent or more—consists of tasks that could be automated or streamlined, freeing time for higher-value work.
As with many industries, the current hype around AI often outpaces what the technology can reliably deliver today. Yet even with that gap, AI and algorithms provide tangible value by taking on routine, lower-level functions. That creates an opportunity: educators can use technology to secure the foundation of learning so that classroom time, professional energy, and human creativity are devoted to what only people can do best.
In short: let machines handle repetitive practice; let people handle meaning, judgment, and relationships. That collaboration—between reliable tools and intentional teachers—offers the clearest path to richer, deeper education.
About the author
Zach Vander Veen has worked in many roles across education, including history teacher, technology coach, administrator, and director of technology. He enjoys learning, teaching, traveling, and seeking adventures with his family. Currently, Zach is the co-founder and VP of Development and Customer Success at Abre.io, an education management platform.