'Personalized Learning': From Marketing Hype to Good Pedagogy

We (CN &ES) took a deep dive into one of the more popular "personalized learning" programs for K–8 mathematics instruction. We were impressed! We saw well-designed, graphically interesting, interactive, fun exercises that would be presented to a student based on (1) a diagnostic engine, making decisions about what a student is probably understanding/misunderstanding; and (2) a progressions chart which math concepts need to be learned before with others. We were told that a student would use this particular math instruction environment for 60-90 minutes per week.

What we saw, then, was concept-based practice embedded within differentiated math instruction — well-respected pedagogical strategies done very well. A human teacher would be hard-pressed to provide as careful and accurate a diagnosis for each of her/his 35 students in real-time, and hard-pressed to provide the range of specific interactive exercises that addressed the particular needs of each of the 35 students, again, in real-time. Designing a computer-based environment to carry out differentiated math instruction effectively is also a challenge, but clearly it can be done. Yay! Congrats all around — to the educators who designed the software, to the techies who developed the software, to the graphics designers and the interface designers who created a compelling user experience.

And, there is great value in having a software application that can provide excellent differentiated, math instruction: Cloning a great teacher is still beyond our manufacturing skill, but cloning a software application — making copies of bits — is literally child’s play. Each copy of the software can deliver the same effective differentiated instruction in each classroom — all around the world.

Our question then is this: What is the pedagogical value in relabeling well-respected, effective pedagogical strategies such as conceptual understanding, targeted practice, and differentiated math instruction? What is gained, pedagogically speaking, in calling that form of pedagogy "personalized learning?"

While we can’t see any particular pedagogical value in that relabeling, we can see that such relabeling has significant marketing value: Everyone wants something new and shiny, even educators, and the new and shiny thing today is "personalization." From using a 3D printer to print out personalized clothing, food and even body parts, to having your own personal digital assistant, 24/7, "personalization" is in. And, it’s a clever marketing idea for up-and-coming education companies to identify with a current trend.

Marketing does have value. Marketing practices help people learn what is available, who is using a product, and the degree to which that product is effective. On the other hand, marketing can bleed over to the point where the new product appears to be all there is — that the only product of value is that which is being marketed. We leave it to the reader to decide where "personalized learning" is along that spectrum of information to hype.

Back to pedagogy! Back to discussing how a software application can be used to complement a human teacher’s efforts to provide effective instruction. Now, it’s no secret, in this blog, we have not been kind to "personalized learning." We have not been supportive of the type of personalized learning where children are placed in cubicles, 1-on-1 with a computer, for half to three-quarters of the school day, where children sit next to each other — but have headphones that impede conversation.

But, using a targeted-practice, differentiated math instruction program for two to three times per week for 30 or so minutes per session — we can see the value in that! No need to take our word for it: There are scientific studies that show the value of such instruction. As we are longtime advocates for the use of computing in K–12 classrooms, we are happy — overjoyed would be more accurate — to see that there is solid evidence that demonstrates the effectiveness of a type of computer-based, instructional environment.  

About the Authors

Cathie Norris is a Regents Professor and Chair in the Department of Learning Technologies, School of Information at the University of North Texas. Visit her site at www.imlc.io.

Elliot Soloway is an Arthur F. Thurnau Professor in the Department of CSE, College of Engineering, at the University of Michigan. Visit his site at www.imlc.io.

Find more from Elliot Soloway and Cathie Norris at their Reinventing Curriculum blog at thejournal.com/rc.

Featured

  • abstract data flow

    Google Announces New Gemini Enterprise Agent Platform

    Google Cloud has introduced a new platform for building and managing enterprise AI agents, as the company seeks to turn its Gemini models and Vertex AI tooling into a broader system for automating business workflows.

  • person typing on a touch screen schedule plan calendar

    Deadline Extended for ADA Title II Compliance

    Schools working to meet the Americans with Disabilities Act Title II regulations for digital accessibility have received a temporary reprieve: The United States Department of Justice has published an interim final rule to push back the compliance deadline by one year.

  • large cloud icon with abstract code  and interconnected polygons

    Report: Enterprise AI Workloads Are Tipping Toward Private Cloud

    Broadcom's 2026 Private Coud Outlook report says enterprise AI is moving from experimentation into production, with private cloud emerging as the preferred deployment environment for AI inference among surveyed organizations.

  • blue wooden cubes block texture abstract background

    Gartner: Worldwide IT Spending Estimated at $6.31T for 2026

    According to a Gartner forecast, worldwide IT spending will total $6.31 trillion in 2026, a 13.5% increase from 2025. Sectors experiencing the largest growth include data center systems, software, and IT services.