In 2002, Mike Rustici founded Rustici Software to help Learning Management Systems

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ABOUT MIKE RUSTICI (President, Rustici Software):

In 2002, Mike Rustici founded Rustici Software to help Learning Management Systems and e-learning content creators work well with each other using the SCORM standard. Rustici Software has grown to be an INC 5,000 company, and today, is the world leader in e-learning specifications.

Mike’s company is leading the world towards adoption of the Tin Can API, the successor to SCORM. Rustici Software wrote the first draft of the Tin Can API before handing it off to the community for industry-wide collaboration. Released in April 2013, over 70 companies are already using the official 1.0 version of the Tin Can API.


As part of our tenth anniversary celebrations, we proudly present ‘Crystal Balling with Learnnovators’, a thought-provoking interview series that attempts to gaze into the future of e-learning. It comprises stimulating discussions with industry experts and product evangelists, on emerging trends in the learning landscape.

Join us on this exciting journey as we engage with thought leaders and learning innovators to see what the future of our industry looks like.


1. Learnnovators: How is Tin Can API (or ‘Experience API’) going to revolutionize the way we learn? How do you think this learning standard will disrupt the traditional thinking of ‘learning’? 

Mike: Tin Can is acting as a market catalyst to drive innovation in the tools we have available for learning through technology. That doesn’t fundamentally change the way we learn, but it does provide us many new tools to use in the learning process. Tin Can will also cause us to think more analytically about our learning programs now that we have more data and visibility into a broader set of learning activities.

2. Learnnovators: What are some of the interesting possibilities of Experience API in making learning a more personalized experience? What would be some interesting stories and use cases (apart from the ones that you have on your website) to excite our readers?

Mike: At its most basic, personalization requires knowledge of the individual. Tin Can itself won’t create personalization, but the extra data it can capture will be a fundamental piece of the personalization puzzle. We can start to look at how people choose to learn vs. how they have been told to learn. We can then look at whether their chosen path is effective for them (perhaps they are misguided about how they learn best). We’re only just scratching the surface of what’s possible.

3. Learnnovators: In this age where most learning happens ‘informally’ (through on-the-job-learning and peer-learning), how well do you think the early adopters of Experience API support informal learning?

Mike: Early adopters are broken into two categories, traditional e-learning vendors and new market entrants. Traditional vendors are largely adopting at the SCORM parity level and using Tin Can as a better way to track formal training programs. New market entrants tend to be doing the more exciting things that open up new possibilities. I think we mostly know how to track informal learning with Tin Can now, but there is still a long way to go in making useful information out of all that data.

4. Learnnovators: In the middle of the Experience API-enabled world, we see learners excited about having their own personal learning space under their control. However, they are concerned at the amount of data that they are sharing with the world. How do you look at such data security concerns? What according to you would be the strategies to assess and mitigate these risks while implementing Experience API?

Mike: Much of what we do today is shared online in some form or fashion. Tin Can doesn’t change that, and the same privacy and security practices that apply to any other industry apply equally to us. People should always be in control of the data they choose to have recorded and shared. Tracking should be opt-in when possible. Users should be able to segment what is shared with which audiences. These aren’t unique concerns to learning data, but they are complicated by a series of expectations and regulations (especially on the education side) that other industries don’t always have to deal with (yet).

5. Learnnovators: What are your thoughts on the possibilities of extending the power of Experience API beyond ‘learning analytics’ to ‘talent analytics’ and other areas?

Mike: It’s a really interesting question. Tin Can was based off the Activity Streams specification precisely because it allows us to correlate learning data with other more general activity data. That is incredibly powerful. As you start to imagine what that can do for learning, it’s easy to then start imagining applying that back to other fields. But once you do that, we are stretching Tin Can beyond what it was designed to do and you start to encroach on well-established analytics and intelligence software throughout the broader enterprise. My hope is that Tin Can will position the learning department as leaders in analytic thinking that will spread to broader parts of the enterprise, with Tin Can becoming just one piece of that larger puzzle.

6. Learnnovators: As we understand, the real power of Experience API lies in its ability to work in conjunction with other data analytics systems and services. What are some of these systems and services that need to evolve along with Experience API in order to leverage the power of this standard?

Mike: Right now the short answer is “all of them”. Even though we have seen tremendous early adoption, this specification is still incredibly new and the number of adopters is tiny in the big scheme of things. When we help organizations adopt Tin Can, we always encourage them to start small and focus on one specific problem or capability. A considered process of identifying a question to answer generally leads to a straightforward list of systems that will need to make statements in order for us to answer the question. That often means outfitting systems providing educational experiences, but also systems that capture the behaviors and performance we are training for. For instance, as a result of a sales training program, we will capture data from a CRM to see if the training had any affect. When asking a question about compliance training, we will outfit the compliance violation tracking system to notify us when violations occur.

7. Learnnovators: We are amazed at the mere possibility of extending the power of Experience API to device data collection (such as Arduino devices). How do you look at the possibilities of using Experience API in the ‘Internet of Things (IoT)’ age of tomorrow? Do you foresee the LRS transforming to an ecosystem where humans and machines (their activity streams) co-exist? How is Experience API going to impact our lives in such a scenario?

Mike: I often say that our lives are increasingly pervaded and controlled by devices that know about our experiences and behaviors. As we look at the Internet of Things and the Quantified Self, that trend is only going to increase, thus enabling us to track more and more learning experiences. Machine learning applied to massive learning record store could allow us to develop tremendous insights into personalized just-in-time learning.

The ADL vision is actually looking this far out in the future. Being part of the DoD, ADL is considering how to provide soldiers on the battlefield with the information they need at the precise moment of need, thus increasing their performance in the field and saving lives. The Experience API is one of the very first steps towards that vision.

8. Learnnovators: One of the most exciting aspects of Experience API is the ‘statement freedom’ that allows anyone to define their own vocabularies for activity statements. Though very powerful, this could lead to non-standard ways of using the vocabularies, which in turn could lead to inter-operability issues in future. How do you plan to address this?

Mike: Absolutely. At the recent ADL Plugfest event, we identified creating “recipes” of best practices for statement structures as one the essential next steps for the community. At Rustici Software we are preparing to share a number of the recipes we have used in early Tin Can implementations and we hope that the community will collaborate with us to ensure interoperability amongst systems.

9. Learnnovators: Experience API is community-owned and community-driven. We understand that, in your journey, the community played a major role right from the beginning till date. How was your experience in evangelizing and getting inspired by the community?  How significant is this synergy in a standard development scenario? How do you think the community will drive further innovations in the standard?

Mike: The last few years have been a fascinating and, I would say, successful experiment into a different model of standards development (different at least to our industry). Developing a spec requires both community consensus and focused, rapid, and structured development. In my experience, broad consensus and focused development are quite at odds with one another. I’ve been involved with e-learning standards for well over a decade now and I’ve seen many community-focused, open efforts at standards development simply fizzle out, largely because they lacked an energetic and empowered leader to move things forward. When everybody is in charge, nobody is in charge and it is hard to make decisions to get things done. The community is often both a standard’s greatest asset and greatest obstacle.

In Project Tin Can, Rustici Software was empowered to provide focused effort and high-level decisions while still harnessing the power of the community. As a trusted independent party, we were able to gather requirements and use cases from hundreds of organizations and individual contributors. We took a lot of time to hear their voices, but then we shut out the noise, locked a few smart people in a room and spent a few months synthesizing all of those requirements into a cohesive solution. When we thought we had something good, we took it back to the community and asked what they thought. Turns out we got it mostly right, but we didn’t get it perfect. The community still had an important role to play in moving Tin Can from an alpha release to a polished v1.0 specification.

I think Project Tin Can is an exemplary model for other spec development to follow, since it harnesses the power of a broad community while avoiding the pitfalls of inaction that complete openness can create.

10. Learnnovators: What do you think is the future of this learning standard? How according to you will it evolve along with other emerging technologies (such as Google Glass)? 

Mike: I don’t know just yet. Tin Can has unlocked so many possibilities that will take us many years to fully realize. It’s hard to look beyond the big pile of opportunity already in front of us. The biggest areas of innovation will probably come as we have large amounts of data to analyze and we are able to mine and learn from that data.

11. Learnnovators: What are the limitations of Experience API? What according to you are the challenges ahead? What are your plans to address these? 

Mike: I think the biggest challenge is the statement freedom addressed in question #8. We have a massive pile of data that we need to figure out how to understand. We also need a way to ensure that the people claiming to adopt that API are doing so in a way that conforms to the specification and associated best practices. These are the next two efforts that the spec group is tackling.

12. Learnnovators: What would be your advice to companies who want to start experimenting with Experiencing API? What is the kind of support you provide?

Mike: The biggest piece of advice is often to start small. It is so tempting to try to introduce all of the capabilities of Tin Can at once, but remember that this is all very new technology and there will be bumps in the road. We developed a methodology called the Watershed Method (http://watershedlrs.com/site/watershedmethod.html) that helps organizations identify opportunities for incorporating Tin Can into their learning programs. The Watershed Method takes a scientific approach to implementing Tin Can; it seeks to introduce a new capability and also evaluate its effectiveness. We help organizations construct this analysis and then we help them put the technical tools in place to implement it. We specialize in helping companies get started with Tin Can.

13. Learnnovators: As we understand, Experience API is a foundation around which it takes a whole lot of tools to make it work (right from the Learning Record Stores to learning analytics systems and others). How complex and expensive is the implementation for a typical mid-sized company? 

Mike: Right now, Tin Can is only for innovative organizations that want to be on the leading edge. It is a very new technology and still requires some hard work, coat hangers and duct tape to make it effective. A standard only becomes powerful when many tools have adopted it and support it natively. Adoption is happening rapidly, but market saturation is still a ways off.

For the cost conscious early adopters, we offer a free, production-ready LRS as part of our SCORM Cloud product as well as many open source resources on http://tincanapi.com to help you get started making statements. For larger organizations, we offer implementation projects of all sizes and scopes that include Watershed Method analysis through to perfectly tailored reporting and analytics in our new Watershed LRS platform.

14. Learnnovators: It must have been an exciting journey for you – right from idea conceptualization of the standard to its release (from Project Tin Can – to Tin Can API – to Experience API version 1.0). It could be considered a well planned and executed project where you were able to keep up your promises (with regards to the milestones, quality, etc.). How do you look at this experience? What would be your advice to others who may want to replicate this kind of success?

Mike: Project Tin Can has been the most rewarding experience of my professional career. It’s amazing that a few smart guys just outside Nashville, TN can change the world. Regardless of whether we actually make any money off of it, we have done something that is spreading throughout the world, something that is getting people excited, something that is spurring innovation, something that is changing an entire industry, something that might actually affect how my children are educated. That is special. That is an accomplishment I will be proud of for the rest of my life.

I think the biggest key to our success was to ALWAYS act in good faith and in the best interest of the specification and the community. ADL placed a lot of trust in Rustici Software in awarding the BAA research grant to define the Experience API. The community placed a lot of trust in us while participating in the project. Early adopters trusted us that this was real. That trust was earned by being honest, positive and generous contributors over the prior decade. ALWAYS acting as a responsible steward of that trust was absolutely crucial to the success of Project Tin Can.

15. Learnnovators: What is your vision for Rustici Software? What would you like to work on next? What are your dreams (we know that you forsook your childhood dream of becoming an astronaut to pursue expertise in SCORM and other e-learning related technologies)? Would building more Application Programming Interfaces (APIs) for the EDTech community be a priority for you to help education data systems break out of their silos and data lock-ins? 

Mike: My vision for Rustici Software has never been about SCORM, Tin Can, EDTech, or really any technology. The vision has always been about building a great place to work. I want to look forward to Monday mornings. I want to work with amazing people, create an atmosphere where we enjoy being around each other and work on solving interesting problems. SCORM and Tin Can have just been means to that end. We’ve largely succeeded in this regard. I love this company just the way it is.

That being said, I really do want to hop aboard a Virgin Galactic space flight, so we’ve recently spun up a new division of Rustici Software to pursue some of the opportunities created by Tin Can. Rustici Software will continue to help e-learning vendors implement SCORM, Tin Can and other e-learning standards through our OEM technology. The new Watershed division is helping companies adopt and understand Tin Can through our new Watershed LRS and the Watershed Method. We see the concept of an organizational LRS as a potentially transformative and disruptive technology to enterprise learning architectures.

Learnnovators: Thank you so much for sharing your valuable insights and experiences, Mike. It was wonderful interacting with you. We wish you and your team at Rustici the very best!

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