As expectations rise, Nigel Nisbet of MIND Education explains why edtech’s future depends on productive struggle and experience-first design.
INTERVIEW | by Victor Rivero
With a background that spans mathematics, music, and classroom innovation, Nigel Nisbet brings a uniquely interdisciplinary lens to edtech. After earning a mathematics degree and launching an early career as a rock musician, he transitioned into education, teaching mathematics, AP Physics, and AP Computer Science at Van Nuys Senior High School in Los Angeles, where he was an early adopter of technology-rich instruction. He later served in district mathematics leadership at Los Angeles Unified School District before joining the nonprofit MIND Education. Today, he leads content creation for ST Math, helping shape a neuroscience-driven, visual learning approach designed to build deep conceptual understanding and equitable access for all learners.
From your perspective, what should define a new “gold standard” for edtech as schools become more discerning about what they adopt?
From my perspective, the new “gold standard” must move beyond simply digitizing traditional curriculum. As schools become more discerning, they should demand tools that are fundamentally built on the neuroscience of how the brain learns. A true gold standard is an “experience-first” model.
‘A true gold standard is an “experience-first” model.’
In most traditional edtech, the “gold standard” has been about content coverage: how many videos can a student watch or how many digital worksheets can they complete? But the brain doesn’t learn by being told; it learns by doing. A next-generation tool must facilitate deep conceptual understanding by allowing students to poke, prod, and experiment with mathematical ideas before symbols or language are ever introduced. This means prioritizing a language-independent approach that removes the heavy cognitive load of reading and vocabulary, which often acts as a gatekeeper to high-level math. The gold standard should be defined by how effectively a tool builds mental schemas—rich, interconnected webs of understanding—rather than just teaching isolated algorithms.
NIGEL NISBET
Many tools promise engagement. What should schools really be looking for to assess whether edtech is improving learning outcomes?
Many edtech tools promise “engagement,” but we need to distinguish between extrinsic and intrinsic engagement. Extrinsic engagement is the “gamification” we see everywhere: points, badges, and flashy animations that are often disconnected from the actual learning. While these might keep a student’s attention, they don’t necessarily lead to better outcomes.
To assess whether edtech is truly improving learning, schools should look for Productive Struggle. Are students being challenged to think, or are they just being prompted to click? True learning happens when a student faces a non-routine problem, makes a prediction, and has to navigate the tension of being “stuck.”
‘Are students being challenged to think, or are they just being prompted to click? True learning happens when a student faces a non-routine problem, makes a prediction, and has to navigate the tension of being “stuck.”’
Schools should also look for Informative Feedback. High-quality edtech doesn’t just show a red “X” when a student is wrong; it provides visual proof of why their logic failed, allowing the student to self-correct. Finally, look for Efficacy at Scale. We take pride at MIND in having over 100 independent studies, including large-scale, third-party evaluations like WestEd, that show consistent growth across all student demographics. If a tool can’t prove it works for every subgroup, it’s not truly moving the needle.
How can research-backed design and learning science help separate high-quality edtech from more surface-level solutions?
Research-backed design is the antidote to surface-level solutions that rely on “teaching by telling.” To separate high-quality edtech, we look at the Perception-Action Cycle. This is the fundamental way the brain builds knowledge: we make a prediction based on what we think we know (schema), we take an action, and we perceive the result. If the result matches our prediction, the neural pathway is strengthened. If it doesn’t, the brain experiences a “mismatch” signal from the hippocampus, which triggers the brain to re-evaluate and learn.
Surface-level solutions often bypass this cycle by giving students the steps to follow upfront. In contrast, research-backed design:
Prioritizes Visual Context: It allows students to develop an intuitive “sense” of a concept—like fractions or proportional reasoning—visually before introducing formal notation.
Builds Deep Schemas: Instead of treating math as a list of procedures to memorize, it treats math as a series of connected ideas. High-quality design ensures that what a student learns in second grade about the number line serves as the foundation for what they learn in sixth grade about coordinate planes.
How does ST Math reflect this next-generation standard, and what principles guided its development?
ST Math is the embodiment of this neuroscience-first philosophy. The “ST” stands for spatial-temporal reasoning, which is the brain’s ability to manipulate objects in space and time. This is a core cognitive ability that exists before language.
Visual-First, Language-Independent: We start with JiJi (the penguin) and a series of visual puzzles that have no written instructions. This levels the playing field for English learners and students with dyslexia, auditory or processing differences, or other reading challenges, allowing them to engage with rigorous, grade-level math immediately.
Mastery-Based Progression: ST Math requires 100% mastery to move forward. This ensures there are no holes in a student’s foundation.
Immediate Animated Formative Feedback: Every move a student makes is animated. If they get it wrong, they see JiJi get stuck or fall, showing the mathematical consequence of their choice. This turns “failure” into a data point for the brain to adjust its schema. We aren’t just teaching math; we are building confident problem-solvers who believe they can think their way through any challenge.
Looking ahead, how do you expect expectations for edtech to evolve, and how is MIND Education preparing for that shift?
Looking ahead, expectations for edtech will shift from “supplemental practice” to “comprehensive experience.” We are moving toward a world where the distinction between digital and classroom learning disappears. As AI becomes more prevalent, the danger is that technology will start “thinking” for the student, providing answers rather than facilitating thought.
‘We are moving toward a world where the distinction between digital and classroom learning disappears.’
MIND Education is preparing for this shift by using AI behind the scenes to analyze millions of anonymized learning interactions. This doesn’t mean the AI “talks” to the student; rather, it helps our designers refine the “productive struggle” in our games, ensuring the puzzles are perfectly calibrated to keep every student in the “learning zone.” We are ensuring that as technology evolves, it remains a tool to amplify human thinking, not replace it.
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Victor Rivero is the Editor-in-Chief of EdTech Digest and Executive Producer of EdTech Digest’s Future Focus Forums (F3), bringing together edtech companies with top U.S. school district technology leaders for an effective way to get feedback on new and existing products. Write to: victor@edtechdigest.com
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