Bridging Math, Standards, and AI in Education: An Interview with Dr. Robby Robson, 2026 Hans Karlsson Standards Award Recipient

An interview with Dr. Robby Robson, recipient of the 2026 Hans Karlsson Standards Award.

Dr. Robby Robson is co-founder and former CEO at Eduworks Corporation and former Chair of the IEEE Computer Society Learning Technology Standards Committee, whose pioneering work in learning technology standards and online learning systems has launched the learning technology industry and enabled modern web-based education.

We connected with Dr. Robson to discuss the transition from abstract mathematics to EdTech entrepreneurship, the pivotal role of interoperability standards like SCORM, and how data-driven technologies and AI are reshaping competency-based workforce development.

What specific analytical skill from your mathematical background proved most surprisingly useful in building online learning systems?

There is a lot of math underlying the work I have done over the years in online learning. I’ll mention two problems. The first problem is to start with a body of content – like textbooks, manuals, and presentations – and use this to autogenerate an intelligent tutoring system. The second is to figure out how skills relate to each other and how to determine to what extent someone has a higher-level skill based on assessments of sub-skills. My background, both in abstract algebra and computational number theory, turned out to be very valuable in both cases – in part because I could understand the math when we found a solution but more so because I could suggest places to look for one. Of course, AI can do a lot of this now, but this was before all of that.

In 2000, you left a tenured position to co-found Eduworks. For a researcher today who is considering leaving the "safety" of academia for a startup, what was the deciding factor that made the risk feel necessary?

The deciding factor for me was the opportunity to have the impact I could not have in academia. During my last few years in the academy, I started to consult for industry on web-based learning, and I was working on technical standards in groups with significant industry participation. My colleagues from industry produced innovative real-world products that had hundreds of thousands or millions of users. That opened my eyes to the possibility. By the time I made the jump, I didn’t feel it was much of a risk, and I would argue that for someone who continually needs new challenges and finds new interests, the risk of stultification in academia is no smaller than the risks of not being able to find a good job in industry.

You contributed heavily to the standards that formed SCORM (Sharable Content Object Reference Model). For developers building modern learning apps, why is understanding interoperability standards still vital even in an era of proprietary platforms?

Proprietary platforms could not run on computers, connect to the internet, and interact with other systems without standards. Learning technology standards, including SCORM and its successors, enable proprietary apps to exchange data, report results, and incorporate content and services from other apps. It is possible to build a great learning app that lives in isolation, but the market for it will be larger, and it will be of more value to its users, if it conforms to industry standards.

Before the current "LLM boom," what was the biggest technical hurdle in trying to automate the creation and tracking of online learning content?

The first big technical hurdle to tracking online learning content was figuring out how content could be developed independently of any learning management system (LMS) and still report data. This involved creating something that every LMS could find in the document object model of a web page. Once this was done, the next issue was cross-domain scripting, a security feature that prevented content delivered from one source to report results to another source. That was at the start of the industry. Fast forwarding to the time when we started working on automatic content generation, the challenge was the state of natural language processing (NLP). It is astounding to think that not long ago a task such as identifying and sequencing topics or auto-generating quiz questions from a set of documents was very hard. Now you just ask your favorite LLM.

You chaired the IEEE Computer Society Learning Technology Standards Committee for eight years. To a junior engineer, "standards" can sound bureaucratic. How would you explain the way standards actually drive innovation rather than stifling it?

Standards create the foundations that innovations build on. Standards can be regulatory in nature, but in the context of IEEE they are more often developed to solve problems that are blocking innovation or holding back an industry. A lot of engineering and creativity go into them. A junior engineer working on a product has an opportunity to affect one product. A junior engineer working on a standard has an opportunity to affect an entire industry and sometimes the entire world.

Your work supports competency-based approaches to workforce development. How can data-driven technology better map a person's actual skills compared to traditional degrees or resumes?

Traditional resumes are rough indicators of a person’s skills, experience, and behaviors designed to be read quickly. Even then, they take enormous tacit and contextual knowledge to decipher, which is often lacking or unavailable. Simply listing a course taken or job done is not enough. We want to know what skills were learned or perfected in the course or job and how those relate to the skills needed for the next course or next job.

A data-driven competency-based approach expresses what a person knows and can do as human-intelligible knowledge, skills, abilities, and attitudes (KSAAs) and uses data and evidence to identify or verify those KSAAs. It looks at the outcomes of courses taken and the skills practiced in a job rather than just a degree or the job title. In the context of IEEE, for example, if a member has presented a paper at conference, data-driven technology can identify the knowledge exhibited, and if a member has helped organize a conference, data-driven technology can use that as evidence of leadership skills. Great care must be taken to ensure that each person has sovereignty and control over their own data, but there are enormous benefits for individuals and employers in having a more granular and accurate competency-based picture.

When moving from a research idea to a patentable invention, how do you determine if an algorithm is truly "novel" in a field that moves as fast as AI?

When we apply for patents, our attorneys do searches, we do searches, and the patent examiners do searches to determine if there is “prior art”, and now AI is doing that.  It is an interesting point to raise your raise though, because for prior art to invalidate the novelty of a patent, it must be older than a year. When that criterion was put in place, its authors could not have imagined how fast a field like AI would move or how interconnected the world would be. Moreover, in a rapidly expanding field like AI, when you solve a problem, it is likely that others have the same problem and have found similar solutions. This may make novelty more of a legal concept (“first to file”) than a reality, but that’s something a patent attorney can address better than I.  

You contributed to the development of the IEEE Standards Association’s Open Source program. How do you see the relationship between formal international standards and the "move fast and break things" culture of open-source software?

The notion that open source has a “move fast and break things” culture is not entirely applicable to the way industry develops open source. Companies band together to develop open source to share the cost of development and improve the robustness of cod on which their products rely, and when they use externally developed open source, they want it to be stable and properly maintained. Both standards and open source are collaborative efforts that can reduce the cost of developing and maintaining common components and infrastructure and create foundations on which companies can build proprietary solutions and compete.

You served as CEO of Eduworks for twenty-one years. In an industry where "pivoting" is constant, how do you maintain a consistent long-term vision while staying agile enough to integrate technologies like agentic AI?

Eduworks’ focus was always on improving training development and delivery, whether through the application of standards, new content formats, competency-based approaches, or the use of AI. The “what” and the “why” never changed, although the “how” did in just about every way possible, from using different technologies to different business models and having different customer bases. Throughout, we tried to stay in touch with emerging technologies and how our customers operated, but most of all we had a very capable team who loved their work and believed in the mission, so agility was never a problem.  

With over 100 publications spanning mathematics to learning technology, your career is a masterclass in interdisciplinary growth. What advice do you have for an early-career professional who feels "boxed in" by their initial degree or job title?

Cognitive and affective skills and self-discipline matter more than specific knowledge. Once you learn how to learn and how to succeed, you can do it repeatedly. I think we all recognize people who have those abilities – they have a way of seeing things and a self-confidence that others lack – and if you develop that others will see it in you.

I will add that switching fields involves abandoning a professional community in which you have established yourself and made friends and operating in a community with a different culture and different values. I learned how to context switch early on, but if you are someone who has been laser focused on a goal and suddenly feel “boxed in”, my advice is to first realize that you actually can get out of the box but also realize that you need to prepare yourself for the social aspects as much as for the intellectual ones.