'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

  • glowing digital human brain composed of abstract lines and nodes, connected to STEM icons, including a DNA strand, a cogwheel, a circuit board, and mathematical formulas

    OpenAI Launches 'Reasoning' AI Model Optimized for STEM

    OpenAI has launched o1, a new family of AI models that are optimized for "reasoning-heavy" tasks like math, coding and science.

  • landscape photo with an AI rubber stamp on top

    California AI Watermarking Bill Supported by OpenAI

    OpenAI, creator of ChatGPT, is backing a California bill that would require tech companies to label AI-generated content in the form of a digital "watermark." The proposed legislation, known as the "California Digital Content Provenance Standards" (AB 3211), aims to ensure transparency in digital media by identifying content created through artificial intelligence. This requirement would apply to a broad range of AI-generated material, from harmless memes to deepfakes that could be used to spread misinformation about political candidates.

  • clock with gears and digital circuits inside

    Report Estimates Cost of AI at Nearly $300K Per Minute

    A report from cloud-based data/BI specialist Domo provides a staggering estimate of the minute-by-minute impact of today's generative AI boom.

  • glowing lines connecting colorful nodes on a deep blue and black gradient background

    Juniper Intros AI-Native Networking and Security Management Platform

    Juniper Networks has launched a new solution that integrates security and networking management under a unified cloud and artificial intelligence engine.