Tin Can: Potential to Transform Learning Services and Programs

On April 27, Tin Can API 1.0 (the Experience API), was released and learning product vendors are quickly adopting the standard which will certainly succeed SCORM. So what is Tin Can and why does its quite emergence signal the beginning of a transformational change for learning services and programs?

Unlike SCORM, Tin Can is able to record user transactions in content outside of courses and extends reporting variables beyond the limited set of SCORM variables. For the first time, instructional designers can track learner actions across vast information landscapes that will inform design. Organizations will now be able to peek over the shoulder of their members as they roam distributed knowledge environments that include web pages, apps, online videos and so on.
 
“More data, so what,” you may ask. By the rumblings of learning professionals who attended the ASTD International Conference last year, I’d say that you’re not alone. So let me connect a few points and I hope that you’ll agree that “Wow” is more in order. First, however, let me share some basics about Tin Can that will help set the stage.
 

What is Tin Can?

Tin Can is a protocol that captures someone’s identity, the action that they’ve performed and the object on which the action occurred. A statement such as “John Smith opened Article X is a simple example. I could have just as easily decided to capture how long John spent on a page or whether John added a comment and if so what comment did he make.

The Tin Can statement is generated by the application in which the transaction occurs and is passed to a learning records store (LRS) which resides independently on some server. Here, once again, Tin Can differentiates itself from SCORM, by allowing statements to be generated and stored on devices that do not have an active browser session and then submits such statements to an LRS when an Internet connection is reestablished.

Having applications generate statements instead of courses is a significant advancement, however, it still presents a serious constraint. This approach limits the applications from which statements can be collected. At present, learning organizations will likely be confined to collecting information from their internal knowledge platforms and tools that are both Tin Can compliant and accessible to them so that they can tailor statement generation as required. This constraint left me wondering what we could do if instead we had a way of deploying a persistent Tin Can statement engine that was attached to a user instead of an application.


The beginning of the end of formal accreditation

Okay here’s where the fun begins. First, let’s imagine that we create a Tin Can app. Users can download the app from a service provider such as Google Play, which in turn ensures that all of their registered devices also have the app. This app runs in the background capturing all digital transactions such as websites visited, email exchanges, blog posts, even phone calls. Upon upload to the LRS, an ID validation service such as VeriSign or Microsoft confirms that it’s their transactions and then updates their experience profiles. As such, we’ve now moved Tin Can statement generation to an individual and as Orwellian as this may first appear, I believe that we will take steps in this direction as surely as people are willing to capture their relationships on public platforms, such as Facebook or LinkedIn

 At this point we can do a few interesting things, such as automate transaction-centred award systems to provide behavioral credentials. The emergence of this capability can already be seen in enterprise knowledge portals and applications like Kobo that award users with merit badges for posting content or reading. The difference with our scenario is that it spans information sources and aggregates transactions across a population so that comparisons can be made. We will have a quantitative way to compare members of a community to determine what types of behaviors produce specific outcomes. Yes, interesting, but not yet transformational.

Real transformation starts when we start applying semantic technology to qualify the value of the transactions being captured. Semantic technology allows technology to understand the meaning of digital content. It will allow a system to scrub your posts, emails, calls and even evaluate the knowledge capital of your social networks to not only count the number of times you do something, but to understand whether what you did demonstrated a novice level of understanding or whether you are demonstrating pioneering thinking. A natural language processing and learning machine, IBM’s Watson, has already demonstrated that it is possible for technology to read through and understand volumes of free text. Watson, who displaced Jeopardy! Champion Ken Jennings, in 2011, is now being deployed for business application, including assessing health insurance claims. Such technology platforms will increasingly be able to posture a question, examine arguments and counter arguments, and position an answer. Asking a computer to assess whether or not someone is a smart as Albert Einstein now seems plausible. If a computer can do that, then a computer can just as easily rank expertise and assign the appropriate credentials. At last, informal learning can be formally recognized.

So the question, I’m left with and the one that I will leave you with is this: How will this affect academic and professional institutes as well as corporate training departments? Could it be that in their current form they will become obsolete?

Massive Open Online Courses: Emerging Business Opportunities

With today's student debt exceeding US$ 1 trillion in the US alone, only 10%-20% of graduates in developing countries considered employable by international standards and increasing pressures for older workers to remain employable longer, the World Economic Forum (WEF) calls for an educational reform. In its report, Education and Skills 2.0: New Targets and Innovative Approaches, the WEF points out that Massive Open Online Courses (MOOCs), which hold promise of increasing access to education, has as of yet failed to provide a comparable alternative to pay-for-credit education. MOOC courses tend to focus on lecture and material reference and lack the type of interactivity and assessment offered by traditional education. The same report, however, identifies the opportunities that is presented by MOOCs to academic institutions that seek new revenue sources. For example, online learning programs which can be moderately priced and offered to significantly larger prospective client-base, as well as credit transfer processing fees to allow students who take online courses from MOOC offerings and who wish to apply the course to an accredited program. Still, however, significant obstacles stand before MOOCs; namely costly investments required to provide rich learning experiences and the reluctance to recognize online learning within the educational industry.

With the advancement of natural language process technologies, machine learning and analytics it is possible to overcome such barriers to redefine educational models and open up new business opportunities within and outside of traditional learning institutions. In fact, businesses will likely be the champion of new approaches given the increased global competition for talent, their capacity to inject investment into MOOCs and the potential return that MOOCs present. Through Co-ops, joint training programs and research partnerships, businesses have demonstrated a willingness to partner with academia. However, MOOCs are not partnerships but distinct businesses that in addition to securing talent can help organizations claim training investments against capital assets, elevate revenue and improve cash flow. At the same time, new revenue sources will arise for academic institutes that position themselves as governing bodies in a new educational network to provide program accreditation, administration and record keeping, course development and facilitation services. Further, learning will become increasing accessible through virtual learning solutions and learners will be presented with new options to finance their learning (e.g., professional membership fees).

The natural evolution of today's educational system under current economic pressures and advancements in technology will result in businesses offering accredited programs. Companies will make the investment to build MOOCs on advanced network technologies to reduce transactional cost and scale quality education to the masses. These programs will be just what business ordered and will remain connected to existing eductational standards by placing educational institutes at the governance helm. Students, whether in developed or developing countries, whether entering the workforce, in the workforce or transitioning from one workforce to another, will no longer have to pay tuition up-front, but instead companies can offer a pay-it-upon industry entry or secure ongoing membership dues to retain degrees. The logistics of administering such a payment plan may have been unthinkable prior to advanced networks, but today it's completely possible.

Perhaps the biggest obstacle is breaking free from conventional thinking and beginning serious discussion regarding what educational reform looks like. Companies that can invest in infrastructure to help MOOCs realize their potential are perhaps the best positioned to take the lead in an industry that is larger than all other information industries combined, $7 trillion in the US alone.

For more information on the state of global education please see http://www.weforum.org/reports/education-and-skills-20-new-targets-and-innovative-approaches