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Learning Impact Blog


Community leadership for more effective use of technology in service to education

On Monday, August 15, at the IMS Global quarterly meeting at Utah Valley University, the leaders of the Advanced Distributed Learning (ADL) initiative, responsible for the Experience API (xAPI), came together with the leaders of the Caliper Learning Analytics Framework (Caliper) from IMS Global.  ADL has joined as a Contributing Member of IMS Global and the parties are committed to exploring a unified path for xAPI and Caliper.  This may mean alignment at some level or potentially even convergence. 

There were roughly 50 experts in the room for an entire day on August 15, and I believe it is fair to say that both ADL and IMS were very pleased with the eagerness of participants to cooperate and depth of discussion. Presentations from the meeting are posted here and there should be a synopsis of the comparison posted soon. 

At the next IMS quarterly meeting November 7-10, 2016 at Arizona State University, there will be a follow-up session on Wednesday November 9 open to the public (registration required).  I expect it to be another great session that should lead to some tangible prioritization and next steps. On November 8 there will also be a day-long Summit on Creating an Educational Analytics Ecosystem.

IMS and ADL are committed to collecting and achieving public input as the process moves forward.  We are likely to create a public forum to encourage the public community to comment and also help crosswalk the information models. Stay tuned to ADL and IMS announcements and twitter feeds (IMS twitter feed is @LearningImpact).  Currently there is a survey for those that have views on the potential convergence of the specifications here if you would like to participate.

I attended the entire August 15th session and would like to provide my sense of the big picture.  I’m not the technical expert, but I have a long history in the applications of standards, including those that evolved into SCORM, and of course the dramatic growth of IMS standards adoption the last 10 years in the education sector. 

I am extremely impressed with both the xAPI and Caliper work. While they are perceived by many as “solving the same problem” my own take is that this is largely because there is still quite a lot of variability in the Learning Analytics field in general.  Thus, almost any set of technical work that deals with transcribing, sending, logging and analyzing data during any form of e-learning is considered “learning analytics.” From my perspective, while xAPI and Caliper certainly have some overlap, they are largely complementary at this phase in their respective evolution. 

At the risk of over-simplifying things, my impressions of the strengths of each specification are captured in the table above (while there are four “strengths” shown for each specification they are not meant to be compared in four dimensions - the above are just lists of the primary strengths).   The strength of xAPI is as a way for a single application to log freeform natural language statements and for that data store to be retrievable by the logging entity.  The strength of Caliper is as a way to aggregate agreed upon events across a set of applications to enable processing across the aggregation of data.

It is also very clear that while neither specification “requires” the body of work from which they came (SCORM for xAPI and IMS standards, like LTI and OneRoster for Caliper) that these foundations greatly influence each. For instance, in the case of Caliper the co-existence of the other standards in an implementation means that Caliper can simply complement a slew of outcomes and context data that are already flowing via LTI.  Again, because the Learning Analytics field is rather loosely defined at this point with widely varying “use cases” one can easily get confused about whether they even need Caliper or should just be using LTI to it’s fullest potential (for instance, LTI can already send data to an endpoint that is not the LMS).

I will also note that in the IMS Communities of Practice relating to data and analytics in IMS, we are seeing a very high priority need to simply be able to see all the data visualizations in one place.  The level of data processing may be fairly minimal – but the humans in the equation need a better way to integrate visualizations that may already be available from various products they are using.

Bottomline, in my humble opinion, is that as we move forward on alignment and/or convergence of xAPI and Caliper I think we need to consider the use cases more carefully and, in essence, better define the “categories” or “scenarios” of Learning Analytics.  While that may seem like “a step backwards” well, I think we need more clarity.  The good news is that I don’t believe we will have any problem given the wealth of actual implementations we are working with in IMS and ADL.

Our goal in IMS is to enable serious school districts, higher ed institutions, states and nations to implement high impact learning analytics use cases and to enable a plug and play ecosystem of products that provide the data needed to solve those use cases.  Either specification is good enough to begin doing some work.  But, in order to do what we need to do we need a very large interoperable ecosystem of products, users, and researchers that can all invest together to get to the understanding we wish to collectively achieve.  I would see elements of xAPI and elements of Caliper as both being essential in that goal.

#7 and final post of a series in preparation for May 2016 Learning Impact Leadership Institute

In the previous posts of this series I have reviewed the requirements driving next generation digital learning environments, looked at the anatomy of interoperable educational apps and considered the realities of sector trends in learning platforms and products.  Episode #6 concluded that the evolution to NGDLE will be driven by a combination of high value use cases enabled by an interoperable product ecosystem.

The Critical Importance of Sector Leadership

First a bit about the sector leadership required in getting to the NGDLE.  From where I sit, education sector leaders need to decide if NGDLE (or whatever comes next) is something that is happening to us or something that we are going to make happen? 

To explain further, tech innovation in the consumer world tends to “happen to us.” Apple iTunes is not something that consumers invented.  If consumers had invented Apple iTunes I’m sure we would have chosen to make sure all those tunes and apps would work on any mobile device we chose, not just Apple devices. Or, why is the Apple library limited to use on 5 devices?  That is not very consumer friendly.  But, individual consumers don’t have much influence in terms of the platform strategies of high tech companies.

But, the education sector is different.  While historically there has been a steady pattern of what I call the "alien invasion" theory of edtech adoption, there is huge potential for institutions that can work together to shape the ecosystem, and therefore the platform strategies of suppliers, going forward.  Indeed, we are at a period in time right now where not only institutional leaders, but leading suppliers are largely agreeing that vendor-specific ecosystems are NOT the way forward in the education sector. No single vendor can provide the diversity of digital resources, tools, apps and platforms.  And no single vendor can provide the sales channel to dominate education revenue generation.

But, strong collaborative leadership is required to establish an open edtech ecosystem. The “system” of leadership that seems to be working are suppliers that can bring the product ideas and technical expertise while institutions bring the clarity of the high value use cases and the firm requirement for plug and play integration.   In IMS we have seen the combination of these two forces achieve some amazing things.  Leadership from both institutions and edtech suppliers in creating and evolving the ecosystem the NGDLE (as envisioned in the EDUCAUSE research and this blog series) is essential.

Use Cases and Emerging Product Categories that Will Shape NGDLEs

In IMS Global we definitely believe that necessity (aka compelling need and value proposition) is the mother of invention.  Exact timing of the cycle of adoption can highly variable based on a number of factors (see the discussion on filtering ideas based on the four major VC risk areas in the previous post of this series). In IMS we like to determine if the value proposition is strong, then establish a track of work and then let the market feedback help us sort out the risk factors and timing.

High value use cases for the NGDLE are those that enable flexibility, choice and personalization that lead to improved educational outcomes.  Here are some obvious winners:

  • Seamless user experience for teachers and students: Sorry if this one seems rather uninspiring but the reality today is that the user experience in navigating among apps and platforms is still not very good.  Making the user experience seamless is key to enabling the development of NGDLEs that are seen as a step forward, rather than backwards. Indeed, an obvious first and essential step in building further confidence toward the NGDLE concept is to achieve seamless integration of some of the core instructional applications already in use at most institutions (see a list in the previous post).
  • Curated digital resource choices with associated assessments: Student outcomes improvement ala Benjamin Bloom’s famous “2 Sigma Problem” is dependent on delivering effective differentiated instruction via a classroom cohort.  This infers well thought out instructional strategies and resources, especially assessment resources, that can support and inform those strategies. Also, as the number of educational “apps” and “digital resources” scales, the need for effective curating that combines easy access/integration with effectiveness becomes paramount. 
  • Digital resource recommendations: Ability to help automate the recommendation of educational resources from among the curated choices will provide high value to instructors, students and parents. This is a very advanced topic that will take many years to develop.  However, it is completely feasible that machine learning techniques could be applied to monitoring and capturing the recommendations of instructional experts.
  • Understanding the usage of digital resources: As the use of digital materials scales there are obvious high value questions that need to be answered concerning the usage of digital resources.  Which ones are being used, when and why? Which ones are not being used?  Why not? This information is of great value to suppliers and institutions alike. However, if it is not “easy” to get the data in one place and understand it, the adoption of digital resources will be hampered.
  • Optimizing and/or personalizing student pathways to a credential or degree:  The ability to understand student pathway options and choices, improve them and recommend them has obvious value. True personalized learning, an umbrella term that can encompass many things, is achieved when the outcomes are defined for each student. The true personalization occurs then across a set of courses or competencies.  Educational success and fulfillment are achieved through a balance of personalization and optimization of the path through courses and gaining of competencies.
  • Better understanding of student progress and risks:  For an NGDLE to deliver on student success it will need to do a better job of helping students understand their level of success and risks of failure.  The NGDLE must support real-time communication and dashboards across a variety of activities to help students measure themselves. An NGDLE will help students, advisors and faculty understand when self-service needs to be supplemented with high touch intervention.

We are observing emerging product categories and how they are fitting into the edtech ecosystem all the time in IMS Global.  I am going to refrain from mentioning specific product names here.  Rather, I will use abstracted definitions of the categories we see growing and emerging.  A very important note, that while the learning management system category is not listed, the LMS has the potential to enable or implement many of the categories below.  Whether or not it is a good business strategy to do so is another question.

  • Modular digital curriculum and assessment: Instructional material or curriculum as a “black box” in which the modular construction and progression are difficult to access and understand are becoming less attractive in the digital age. There is both huge opportunity and risk here for organizations that can structure their curriculum products to help solve the high value use cases above. 
  • Integrated adaptive assessment: While related to the ability to modularize assessment (previous product category) the category of assessment tools that can be readily integrated with a variety of instructional resources and approaches will be fundamental to improving digital learning outcomes. Assessment is a specialized science and quality assessment is not simply providing some test items. This category will combine ease of use/integration with high quality assessment with real-time feedback.
  • Digital curriculum mapping and management: Differentiated instruction, individualized instruction and personalized learning all require management of the pathways and options available to teachers and students. The management of the curriculum needs to take a step up from where it is today. This product category will enable that.
  • Learning resource catalogs, app stores, repositories: Perhaps Google or Amazon will be the answer to searching for educational resources. However, the search and integration of resources required to enable the high value use cases above is a lot more complicated than the sort of searching and recommendations that suffice for enabling Internet commerce.  This product category addresses the organizational and ecosystem integration features needed to enable better learning outcomes and ease of use.
  • Learning analytics processing and messaging: Learning analytics is a hot new product category. It is also something that many LMS platforms and tools offer in some shape or form.  As with assessment, learning analytics is a highly specialized field. And, analytics needs to be performed across many apps.  Therefore, I think it is likely that new products will emerge that are separate from existing products.
  • Outcomes and achievements management: Several new product types are emerging that are helping institutions manage how they structure and assess student progress in terms of competencies and micro-credentials.  Some of these products are incorporating the “integrated” assessment category.  This category will help institutions structure the relationships among the outcomes they hope to achieve with students. It is different but potentially related to curriculum management. It is a layer above.
  • Student pathway management: Products that can help advisors and students understand the path.  These products will help students plan and optimize their path to their learning and degree objectives.
  • Edtech research data collection and processing: An NGDLE will enable better research of the effect of technology and instructional approaches on student achievement and outcomes. Therefore, I anticipate that products that enable learning analytics correlation of edtech usage to student success will emerge.  This could be considered a subcategory of the “learning analytics” category above, but am calling it out separately as a vey important and necessary contribution that may not be covered by other analytics applications.

Want to read about specific products along these lines? The best place is the IMS Learning Impact Report, which we publish annually, and which we consider to be ongoing research into the product categories that are leading the way to next generation digital learning.

Finally I will leave you with a simple idea and figure (shown here) to help illustrate the road we are on in terms of a maturity model of edtech products and the evolution toward next generation digital learning environments.  At the base level, an educational institution should be able to support the use of technology to support teaching and learning. This is stuff like BYOD and Google Apps for Education or Microsoft Office 365. The next level up is the enhancing of productivity using technology. Herein lies the success of LMSs and many other tools and technologies. However, one should not think it trivial to get to this 2nd/middle level because there are loads of examples of digital tools, and lack of integration of those tools, that have made life less productive for teachers and students. The “top” tier are emerging applications that have the power to improve student achievement and learning outcomes. Some of these are new product categories and others are existing products that are used in ways that clearly support better outcomes.  But the key point is that for an NGDLE, the expectations are evolving from the perspective of the customers – the students, the faculty, the institutions and society in general. 

The motivation for collaborating on NGDLEs is to enable a more effective ecosystem of educational platforms, apps, tools and resources that have measureable impact.  I hope to see you at the Learning Impact Leadership Institute where a unique collection of sector leaders gathers to further this important collaboration.

#6 of a series in preparation for May 2016 Learning Impact Leadership Institute

In the previous posts of this series I have provided a high level overview of the potential goals of next generation learning environments.  In the last several posts I have taken the perspective of what it might mean to be an “interoperable app” in the context of next generation digital learning environments. 

Now it’s time to come back to reality and look for clues from the market in terms of how we are likely to evolve to next generation digital learning environments.

Today is the First Day of Your Journey to NGDLE

One of our conundrums in getting to the next generation is dealing with the current generation.  Educational institutions are already dealing with “sub-optimal” integrations (I’m being kind here) of systems, platforms and applications that teachers and students touch every day.

Indeed, I would be a much less grumpy person, and more importantly, faculty and students would be much more satisfied with technology, if the following products, typically found in a majority of classrooms today, were better integrated:

  • Digital textbook (interactive)
  • Library digital resources
  • Summative testing
  • Formative testing
  • LMS with Gradebook (or separate Gradebook/outcomes assessment & tracking)
  • Classroom capture
  • Classroom response
  • Classroom management
  • Interactive whiteboard
  • Other digital resources and applications

This is a pretty limited set.  But if just a subset of these applications were really nicely integrated into a seamless and easy experience for students and faculty, technology would be a lot more appreciated in the education sector. Although in K-12, the “other digital resources and apps” are typically in the hundreds – even today.

The following types of products are also in the mix already.

  • Online class conferencing
  • Assignment grading system
  • Adaptive learning tool(s)
  • E-portfolio
  • Course evaluation

And don’t forget basic shared IT infrastructure:

  • Student information systems
  • File storage and sharing
  • Video management
  • Content authoring
  • Calendaring

And then there is the potential for integrating those mobile apps that come to educational institutions courtesy of the Apple, Google, Amazon or Microsoft consumer Internet app platforms. 

Learning Platforms Are Evolving

Now let’s consider the evolution of the “learning platforms” themselves.  In IMS we use this term rather broadly.  In the future I expect we will be characterizing the subcategories of learning platforms better. But for now a learning platform is essentially an integration point for learning resources that may provide as little functionality as single sign-on and 1-click launch.

News alert!  If you’ve been following IMS recently you will know that there are more than 400 products that have passed conformance certification.  There are over 70 LTI learning platforms and a couple hundred LTI tools in that mix – which probably represent about 1/3 of the actual adoption of the LTI standard in the market.

Indeed in K-12 school districts we are seeing easily 20-50 LTI tools or content series being integrated in districts (1+ million learning objects via thin common cartridge) that have gotten their LTI act together.

One question to ask is, “Are the more sophisticated learning platforms in tune with the stated requirements of the NGDLE?”  Back in October of 2015 I did a featured talk at OLC (Online Learning Consortium) in which I highlighted some of the directions toward NGDLE.  In preparation for that talk I reviewed the web sites of several of the leading learning management systems looking for messaging that might be consistent with the NGDLE requirements.

The figure here shows what I was able to ascertain.  Apologies to all concerned that this is dated now – and therefore may be different today.

While this comparison is a very crude analysis, I do think it reflects several market realities in getting to the NGDLE:

  • Analytics (however it might be defined) is clearly the area of the NGDLE that is getting the most attention, interpreted as, “there is strong customer interest and money to be made there.”
  • Accessibility as a standalone category is not getting the attention that all of us would hope it would be getting, although personalization (which I have connected to accessibility in this series – see discussion on user preferences here) is getting some play (but I expected more).
  • Collaboration gets a fair amount of coverage, but it is not the hot item that the NGDLE research seemed to indicate it should be – perhaps because, as in the world of IMS, collaboration of various types can be supported via a wide range of apps.
  • There were a range of other key marketing themes that did not get too much attention in the NGDLE research, including usability, reliability, mobile, content management, course building, grading and competency-based education (CBE).
  • Perhaps most interestingly, is that the marketing of the so-called “lynchpin” of the NGDLE, interoperability, was very uneven and, form the perspective of IMS, pretty weak. 

While again, this is a very crude analysis, I think the market is giving us some important messages about NGDLE.  One could take a “glass half empty” of “glass half full” interpretation.  The glass half-empty view is that the product providers are not in tune with those institutional leaders participating in the NGDLE research.  The glass half-full view is that the product companies are focused more on marketing to higher value themes – like product usability, student success, competency-based education, etc.

My own view is that both interpretations are correct. In my thirty-five years of product development experience across a variety of sectors, I feel that there is no sector in which the product providers are more out of touch with their customers than the education sector.  The senior executives and marketing folks in a large number of product companies are not understanding as well as they could the desires of the end users.  On the other hand, I do believe that it will be very specific areas of improvement that will drive progress toward the NGDLE.  General ideas, like personalization, are not going to drive the suppliers and customers to work together to get to the NGDLE.  More specific ideas, like clearly better usability of technology to support teachers and students needs, will.

What Will Drive the Progression Toward NGDLEs?

Getting to next generation digital learning environments will happen because the high-value use cases require cooperation among a diverse set of digital resources, apps, tools and platforms.  Enabling specific high-value use cases is key. Where the “architecture” comes in is to be able to evolve the solutions to those use cases collaboratively across an ecosystem of suppliers and institutions – versus a much more slow and ultimately unreliable approach of big bets on one-vendor solutions.

To put it another way, the evolution to NGDLE will be driven by a combination of high value use cases enabled by an interoperable product ecosystem.

Up next in the series: In the next and final post of this series on next generation digital learning environments I will take my guess at specific use-cases and new product categories that are driving us toward NGDLEs.

#5 of a series in preparation for May 2016 Learning Impact Leadership Institute

After a 1-week pause to focus on the release of the IMS Annual Report, I’m back at the topic of the anatomy of an educational or learning app.

ASU GSV why can't we be friends: interoperability in school districts

In the previous post of the series I provided a high level overview of the interoperable inputs that an educational app might utilize.  Now it’s time to look at the outputs.  

It is interesting to note that last week I was on a panel at the well-known ASU GSV Summit entitled, “Why Can’t We Be Friends: Vendor Interoperability in Districts.” The salient takeaway for this post is that there was great agreement that while the sector is making some pretty clear progress on the input side of interoperability, the output side is pretty early in its development. So, get ready for the harder part!

As with my discussion on the inputs I am going to refer to the Anatomy of an Interoperable Learning App figure shown here.  And, I am going to focus on what makes these outputs “next generation” in comparison to today.

Anatomy of an Interoperable Learning AppFor next gen learning apps the objective is to enable better information outputs to understand progress, further personalize the learning experience and just in general understand the usage of various digital resources. Shown in the figure are some categories of potential outputs (on the right hand side) that are discussed further here:

Activity: Some IMS members call this aspect of digital resources “adoption.” As we evolve into the next generation of scaling the number and types of digital educational resources and applications one of the first questions that needs to be answered is, “Are teachers and students using these resources?” One function of this is for administrators, teachers and suppliers to get an understanding of what is being used, and perhaps be able to infer why or why not?  One of the major deficits of research into use of digital resources is the dependence on user surveys. It is much better to have ways to directly measure usage. And, once usage can be measured accurately it enables the potential that use of specific resources or combinations of resources may be statistically correlated with outcomes via various assessment mechanisms.  Activity information is also very important to the content creators/publishers because it enables a better understanding of how digital resources are being used and thus provide clues for improvement.

Outcomes:  The most effective educational platforms and apps will be those that can indicate to the student, parent and teacher how well the learning is progressing. Of course, the term “outcomes” can have a very broad definition in education.  However, the thought here is that the educational application will have some way to report progress, including scores to measure success on a specific activity, “gradebooks” that are compilations of scores, and even comparisons to the progress of other users.  The challenge is that different applications will measure progress differently, and thus be difficult to compare and analyze.  From the perspective of interoperability, one potential big win is a usable way to collect all the progress information on a single student on a single screen or other usable interface. Today, many tools may have various progress reports or dashboards, but they are resident “inside the application” and thus not readily looked at in conjunction with progress information from other apps.  Another big win is agreement on some common summary information across a wide variety of learning applications.  The holy grail perhaps, depending on your view of the viability of common learning standards, is an agreed upon approach for all apps and platforms to report on progress by specific learning standards.  Finally, another very important type of outcome data in education is assessment “item data,” which is the collected responses to assessment items.

Credentials: There’s a lot of talk these days about the potential advantages of micro-credentials in education.  Micro-credentials are ways to recognize granular achievements or cross-curriculum competencies that are highly valuable and typically not inferred by a higher-level construct such as a course grade or GPA. Such achievements or competencies may be extremely valuable in matching a person to a job or career.  In the educational context, micro-credentials might do a much better job than grades in determining if a student is “college ready” in terms of meeting specific prerequisites.  In the context of next generation digital learning there is the distinct possibility that a learning application may provide evidence toward a defined micro-credential or even a validation of such a credential.  The interoperability that will be required will be a way to combine or mash-up such credentials. IMS is working to apply open badge extensions and modular electronic competency and transcripts to enable credential validation and mash-up. The current state of the market is quite early and exploratory. So, we have a long way to go – but this is very important work for the future that may find useful application in those institutions that are doing a better job at micro-credentialing  and competencies.

Artifacts: This very important area of next generation learning is potentially related to credentials. It is about how to capture, in an effective manner, what the learner may have created during their interactions with the application.  While an artifact is not a credential, it can provide evidence of competency, creativity, agency, etc.  The ability to capture meaningful artifacts can help a learner reflect on and assess their own learning, reinforce past learning experiences and display their work to others.   An e-portfolio is a type of learning app that is designed for this purpose.  But, artifacts can be created in many other types of learning applications and platforms. Next generation learning requires not only interoperable publishing mechanisms, but also interoperable metadata to enable classifying, sorting and searching artifacts.

Ramifications on Next Gen Architectures

From the above, one can see that there are a broad range of possible outputs from learning applications and platforms.  As previously noted, interoperability of the outputs of learning applications is a complex topic that needs a lot or work.   It is also much more variable across different educational levels and types than the inputs. Highly variable areas that are early in their maturity are usually not good topics to attempt to get industry agreement on.  Therefore, we can reasonably make some conclusion regarding interoperability of outputs for next generation learning

  1. Interoperability of activity, outcomes and credentials will need to be structured to enable affordable collection of data that supports research on potential correlations. 
  2. A very high-level of cooperation will be required among suppliers of a wide range of products to establish the interoperability standards and enable the data exchange to achieve #1.
  3. For #1 and #2 to accelerate understanding of the impact of learning apps and platforms, industry must set up and sustain funding models for cross-industry research.
  4. There will also need to be some “quick win” areas for interoperability of outputs.  There are some ideas for such quick wins in the descriptions of the categories of outputs above.  By “wins” I mean providing value to institutions, users and suppliers.  Another way to state this is that “the road of establishing the interoperability for next generation learning must provide current generation benefits to all market participants.”

Next up in the series:  What education sector realities are telling us about the likely evolution toward next generation digital learning architectures?

With the release this week of the IMS Global Annual Report 2015, I wanted to attempt to summarize some ways in which “our little engine of change” is helping to enable some potentially pretty profound stuff.

A little more than two years ago (December 2013) I was asked by Diana Oblinger (CEO of EDUCAUSE), to present, along with Jack Suess (CIO at University of Maryland Baltimore County),  a “game changer” webinar discussing the recently published EDUCAUSE Review article, “A New Architecture for Learning.”  We decided to entitle the webinar:  “Building the Connected Learning Platform – One Brick at a Time.”

Of course, it was flattering to be considered a “game changer” – whatever that term really means. Most people, including technology veterans, would probably think of interoperability standards (the work of IMS Global and important basis for above paper and webinar) as being “part of the game” rather than necessarily “changing the game.”  I would include myself in that group when thinking about the large majority of standards-setting activities. 

However, I did think it possible that the work of IMS Global could be a “game changer” when I became the CEO a little over 10 years ago.  Now I believe in the “game-changing” nature of IMS even more.  I’d like to enumerate here some of the specific ways that IMS has been and is changing the “edtech game” (albeit never fast enough for me!).

#1 Providing a foundation for collaboration that fits where the edtech sector wants to go in terms of diversity of platforms, resources, apps and tools. The rules of the game are different when an industry is dominated by proprietary walled-gardens then if there is plug and play interoperability of tools among a wide variety of platforms.  As consumers, we live all day long in proprietary walled gardens created by a few dominant platform suppliers with app stores and mobile devices. However, the education sector has figured out that the idea of just a few dominant platforms just does not make sense for the sector. For instance, most K-12 districts are compelled to support both Microsoft and Google. IMS standards, and more importantly the critical mass of IMS members leading the charge, don’t see a few dominate platforms as the future of edtech (to the MBA people out there that will say that every market moves in the direction of a handful of dominate providers, I just want to say that I know those arguments well, but the education sector is very, very different). I’m very pleased to report that the IMS community is leading a better way to build an ecosystem based on what the education sector requires, namely products that can actually work together to improve teaching and learning while keeping lock-in and barriers to entry low to spur innovation.

#2 Providing an interoperability development process that is based on engaging directly with suppliers and institutions. Much of the work on standards in EdTech has been very visionary and developed by some really brilliant people. And, my hats off to the great work.  However, the missing link to make this work payoff for all parties concerned is a necessary reality check of compelling sector needs and market adoption. IMS has added this extremely important element in the last 10 years.  For those familiar with venture capital or market development approaches, the IMS process is very much a funnel where lots of good ideas go in that are then processed through market validation.  So, to get out (become a published IMS standards) there has to be an acceptable combination of market, financial, people and technical risk (which are typically the four dimensions of risk that VC firms look at).

#3 Focusing on enabling the plug and play ecosystem that results in more investment on innovation. IMS is creating a major culture shift in EdTech standards, namely that the measure of a successful standard is that it helps to lift up the entire sector.  IMS sees our job as enabling an interoperable ecosystem – what has already become hundreds and in the future thousands of products that work with each other “out of the box” (or as close as possible).  Time and cost of integration goes to zero.  When that ecosystem happens it focuses investment on the innovation of the individual products themselves and also of what can occur when products work together. To anyone familiar with some of the more mainstream standards in the tech world that were huge successes, like Ethernet, the Worldwide Web, or wireless standards, you would most likely say, “isn’t that the point of most standards?” A good standard reduces cost while increasing connection into a large ecosystem, which means that suppliers are naturally motivated to adopt.

#4 Accelerating interoperability progress through synergies across K-12 and higher education.  I’ve gone on record many times that I believe there are many differences between the needs of K-12, higher education and corporate training. I know from actual experience that if you try to build a product for all of them you are unlikely to succeed with any of them. Thus, when the U.S. K-12 sector came knocking on the door of IMS about 5 years back I had an open mind, but was cautious about how it would work out. Well, it has worked out great! What we have found is that one sector can take work coming from the other sector, get use out of it, and then, amazingly, take it further in ways that have then gone back the other way to help the originating sector.  It has taken some very good market development and project filtering skills (see #2 above) to encourage the right focus at the right times. But, it is very clear that IMS is now a 50/50 partnership between higher education and K-12 – which of course means that each sector is leveraging the investment and ecosystem of the other. The bigger the ecosystem the more valuable the standards.

#5 Creating an EdTech ecosystem leadership community that will lift the sector in the sort term and is likely to endure in the long term.  This is really the most important impact that IMS is having. As I mentioned in a recent EDUCAUSE Review article, “Foundations Past and Future,” IMS is really all about education sector participants willing to lead a critical aspect of cooperation that will accelerate the innovation we need to improve education. There are, of course, many other critically important areas where cooperation and communities are developing with complementary foci. But, I do believe that interoperability is an underlying foundation for much of the rest that requires strong leadership collaboration.  The beautiful thing is that we are finding that those organizations, institutions or suppliers, that are investing time in leadership in IMS, are doing very well. It turns out that to be technically interoperable also requires organizational leadership that is interoperable. It’s a big claim to make, but I will make it. Namely that we are seeing IT, curriculum and instructional leadership and strategies getting to the next level when an organization works on and “gets” interoperability.  We are seeing a focus that goes way beyond the historical desire to just have the latest technology to being able to leverage technology toward personalized learning and other strategic goals.   As indicated in the figure, the net result is a financially strong (while still small compared to many education associations such as EDUCAUSE or ISTE) IMS organization that can play a substantial ongoing role in developing the EdTech ecosystem.

As a result of the above innovations, led by the IMS members, I do think the trajectory of EdTech is changing in a very positive way. I’m very proud of the IMS members stepping up to take on the challenge of working together on building an open and innovative EdTech ecosystem.

 

#4 of a series in preparation for May 2016 Learning Impact Leadership Institute

In the previous post of the series I laid out a perspective on interoperability for next generation digital learning environments from the perspective of an application being able to fit into a configurable constellation of educational apps.  I would now like to elucidate the key features that make said app and environment “next generation.” I will once again refer to the “Anatomy of an Interoperable Learning App” figure introduced in the previous post.

What might next gen learning apps know about the learner? What should they be allowed to know? What can be personalized in the user experience from that knowledge?

For next gen learning apps the objective is to enable better information inputs to allow the app to personalize the learning experience.  What is the information and what does the app do with it? Shown in the figure are some categories of potential inputs (on the left hand side) that are discussed further here:

Institutional context: This is the type of information that is typically found in a student information system (students, student grade level, courses, sections or other groupings). There are potential common languages for this from interoperability standards like OneRoster and Learning Information Services, as well as the Rostering (aka Membership) Services of Learning Tools Interoperability. While exchange of this sort of information is not especially “next gen,” enabling this exchange without the need for custom integrations and code writing is. The information is typically used to authorize use of the app as well as group users together (such as in a collaborative app). Information about who the user is can also be used to bring the student back to the place where they left off, store results in progress specific to the user, etc.

User context: This is information about the learning activities that the student is currently engaged in (reading, assessment, discussion, assignment, media, etc) when the app is launched.  User context is also information that the app can generate and output in the form of an activity description.  User context is an area that requires more work to develop a common language.  Standards work applicable to this is Caliper Analytics and Learning Design.  User context information could be used by the app to personalize how the app behaves. For instance, an assessment app might act differently if it is launched in conjunction with a reading activity, versus if it is launched as a separate assessment.  Again, this is a more advanced topic.  It is very “next gen” in that it enables an app to respond to the circumstances (activity sequence) in which it is launched.

User Preferences:  We all know that apps typically have some ability to allow the user to specify preferences.  For “next gen” digital learning environments to be personalized in a scalable way, there needs to be a way for the user to specify preferences one time and have that information propagated to all relevant apps.  These are not “app specific” preferences, but rather preferences that could be pertinent to most apps.  For instance, when a user interacts with apps on their smart phone they may have certain preferences for size of fonts, use of media, etc.  There is a rich body of interoperability work called Access for All that has developed a rich framework for describing personal needs and preferences (PNP).  Access for All is applicable to all users, but also has a rich foundation in accessibility (and has even been published as an ISO/IEC standard). PNP has been applied to high stakes assessment accessibility via the Accessible Portable Item Protocol (APIP) standard.  One of the most important preference areas in education is privacy.  While the “setting privacy preferences in every app” model of consumer app stores may make sense for that world, it does not make sense for education. Students or parents need to be able to set privacy preferences once in the context of their institutional experience and then have those privacy options set as defaults for every app.  Therefore, for “next gen” learning environments, our expectation is that the privacy preferences will be selected from an interoperable privacy framework that is provided as an input to each app for each user.

Learner Profiles:  One of the potentially most valuable interoperable inputs for next gen learning apps is a learner profile. This is information that lets the app know where the student is in their learning experience and progression. It can be used to provide a personalized experience for the student. In some ways, the learner profile is the “holy grail” of next gen learning in that the better a learner’s “state” can be described the more personalized the learning experience could be. The problem of course is that no one knows exactly how to describe what a person knows or doesn’t know.  A learner “state” must be generated and kept for every adaptive learning or assessment app.  Is that state record standardized or interoperable? No, not at this point. In fact, such a description is probably considered to be the “secret sauce” of such products.  If the products are tracking progress toward agreed upon competencies or learning standards (like the U.S. K-12 Common Core) then it makes the possibilities of exchanging learning profiles greater.  But there are still a lot of nuances.  More light will potentially emerge at the end of that tunnel as adaptive summative testing becomes more mature.  Such testing will require well-defined “levels” of mastery to agreed upon learning standards.  However, even in the short-term there are some interesting possibilities.  For instance, in IMS right now we see tow more tractable paths to building and exchanging learner profiles.  In higher education the IMS community is developing ways to exchange competency frameworks among cooperating products in the educational enterprise.  In K-12 the IMS community is looking at taking small, but potentially powerful steps looking at profile items like reading level.  IMS does have some past work on learner profiles and competencies as well that may become applicable: Learner Information Package, ePortfolio and Reusable Definition of Competency or Educational Objective.

Ramifications on Next Gen Architectures

Getting the architecture “right” for next generation digital learning presents numerous opportunities and challenges.  Here are some questions that the education community needs to think through:

  1. Is there a software application that is best suited to be the keeper and provider (in terms of interoperability) of learner profiles? Should the learning management system or student information system do this?  Or, perhaps a competency management product? What about the new category that the Gates Foundation has been encouraging, Integrated Planning and Advising Systems (IPAS). Yet another possibility is a competency-oriented assessment product.
  2. Same question for entering, storing and sharing personal needs and preferences, including the all important privacy preferences?
  3. What pragmatic steps do we take in moving our institutional or product architecture forward as we build toward this future?

Next up in the series:  Deeper dive on next generation digital learning environment (NGDLE) interoperability: part b: interoperable app outputs

 

#3 of a series in preparation for May 2016 Learning Impact Leadership Institute

Now we begin to get into some of the meatier topics when it comes to evolving from the world of today to next generation digital learning environments.

One of the challenges of even envisioning, much less implementing, a configurable constellation of educational apps (see previous post in this series on metaphors) is the notion that potentially “everything is connected to everything else.” How does that scale? I will consider the scale issues in a later post.  But, for now, let’s just consider the interoperability needed to enable next generation digital learning.

It is very tempting here to elucidate the various types of products, functions and services that must come together in the delivery of an institutional education experience. Indeed I have often gone down that road for the sake of making the discussion very tangible.  Shown here is a figure from the precursor paper to the NGDLE, A New Architecture for Learning, along those lines.

Another, more detailed treatment along these lines, has been published by IMS member SURF of the Netherlands. The paper, entitled, “A Flexible and Personal Learning Environment,” is a really great survey of ideas and realities from a functional (“components”) perspective.

For this post I am going to take a different perspective, namely looking at the anatomy of the interoperable educational or learning app.  If you’re into legos than this is akin to thinking about how the legos connect to enable personalized learning environments.

For this “app-centric” view I offer the following figure depicting the potential anatomy of an interoperable educational or learning app:

The view shown here is informed by numerous insights from many years of IMS members working on many, if not all, aspects of this challenge. However, it is also flavored by the “dimensions” enumerated in the Next Generation Digital Learning Environment research paper, namely:

  • Personalization
  • Analytics, Advising, and Learning Assessment
  • Collaboration
  • Accessibility and Universal Design

Ignoring the detailed information on inputs and outputs for a moment, the following overview statements apply to the figure:

  • An “app” is different than “content” in that content does not process inputs or outputs, while an “app” does
  • While not required, an app can “mash-up” other educational apps and content using the same structures shown (note the reference to mash-up per the NGDLE research paper:  “If the paradigm for the NGDLE is a digital confederation of components, the model for the NGDLE architecture may be the mash-up. The confederation-based NGDLE will be mashed up at both the individual and the institutional levels, as opposed to consortia forming to create open enterprise applications.”)
  • An app may also produce content or app launch links that can be mashed-up into other apps
  • An app does not necessarily support all of the inputs, outputs or management interfaces shown – only those required for what it supports
  • An app typically has a web back-end as well as a web or mobile client, however, some apps may be mobile only

What can be mashed up?  Again, mash-up support is not required but if supported enables an app to leverage the ecosystem of interoperable apps and content.  Based on IMS experience we see three categories of mash-up:

  • App interoperability: For example an app launched and integrated using LTI.
  • Assessment interoperability: For example assessment items using QTI.  Assessment items and tests are a very important and specialized category of content in education and learning that merits a specialized language for interoperability.  
  • Content & app manifest interoperability: For example common cartridge or thin common cartridge. A “manifest” is a list of the assets, some of which may be available locally and some of which are web accessible. Note that both varieties of common cartridge support LTI app launch links.

It is also worth noting the reference in the figure to “IMS App SDK and APIs.” While it is not the official or even necessarily majority view of IMS members that IMS will ever have a production-worthy developers kit, it is my own personal view that this is the direction that makes most sense for enabling high levels of interoperability and cost reduction. It is also an extrapolation of what is occurring in most IMS spec areas, namely development of APIs, code libraries, sample code, etc.

Again, the above is my attempt an interoperable app definition that we are building towards to enable the NGDLE.   We have seen over and over again that the evolution will take time and respond to market needs.

Next up in the series I will explore more explicitly how the interoperability features shown in the Interoperable App Anatomy support the NGDLE dimensions, including some potential ramifications on the enterprise apps required. 

#2 of a series in preparation for May 2016 Learning Impact Leadership Institute

In the 2015 EDUCAUSE Learning Initiative research paper on the Next Generation Digital Learning Environment (NGDLE) the familiar metaphor of legos is once again called upon to represent user configurable learning environments:

“Since no single application can deliver in all those domains, we recommend a “Lego” approach to realizing the NGDLE, where NGDLE-conforming components are built that allow individuals and institutions the opportunity to construct learning environments tailored to their requirements and goals.”

The reason I say “once again” is that the lego metaphor has been called upon many times before since the early days of e-learning (last half of 1990’s) when it was used to describe reconfigurable “learning objects” that could potentially be chained together to meet personal learning preferences and goals.  There was a lot of coverage and development around the learning objects concept - showing some magazine and articles here that I was personally involved with.

While the use of legos as a metaphor in learning is very convenient and one that IMS has used from time to time (for instance see the cover of the 2014 annual report), legos are really not adequate to describe what is really needed. Of course, it depends on exactly how one thinks of legos. I tend to think of them as preconfigured shapes that can be joined into a whole.  However, the connections are rather rigid and very localized.

A lot of evolution has occurred in the last 20 years. Of course the learning “platform” (software that enables a learning experience and environment beyond simple interaction with content) has become a prevalent component in education.  But perhaps the most important evolution has been from “content that moves around from system to system” to “content that is hosted and accessible via a web interface.” That later category of content might also be called a web application or just “an app.” An app typically contains its own “learning platform” of some sort, meaning the web application is typically intertwined with the content and not as broad in its ability to support “LMS-like” features. 

In creating next generation learning environments the connections that need to be supported are among a cooperating constellation of these web applications.  How exactly they cooperate is of course key to interoperability, but a logical starting point is via the education institutional platforms, such as an LMS, a portal, an app launcher, a student information system, or some combination of these.  Thus, another metaphor we have used in IMS is a configurable constellation of connected apps.  I’ve been using that metaphor in IMS since 2007 – and shown here is one of those uses from a 2008 presentation made for ELIG in Europe.

It should also be noted that some things HAVE NOT changed much since the first use of legos in e-learning. One that is very important to keep in mind with respect to the vision of user configurable NGDLE is that even though the concept of fitting learning objects from different sources sounds good that it is nearly impossible to do in any automated fashion. There has been success in configuring personalized learning paths from content modules from a single source in an automated fashion (like an adaptive learning application) but generally all attempts at automating content reconfiguration across suppliers have fallen short because stuff has to be designed to really work well together.

The NGDLE research paper also comes to the conclusion that the architecture is a “confederation” and that the right model for the architecture may be a “mash-up.” This is a model that we like a lot in IMS.  Indeed, in the earlier days of Learning Tools Interoperability (LTI) Dr. Chuck Severance spoke a lot about the user paradigm for LTI being a “mash-up” of web applications, much like Google maps appears in any web site.  More recently we like the user paradigm of the learning platform that can be invoked across apps, like a familiar toolbar that floats on top of any app, rather than the container in which things must be placed.  We’ve seen a couple of nice early prototypes of this idea in IMS, including in the Learning Impact Award nominations.

In summary, what we have learned in the last 20 years is that users can sort of deal with a pallet of apps (like those on your phone or tablet) that they have chosen, and that suppliers, even publishers of content, like this approach to offering and selling products. But, configuring a set of independent apps is a lot easier than configuring a cooperating set of apps.  The interoperability needed is much more challenging and certainly in education there needs to be some “learning design” across the connections performed by a human (a teacher, an instructional designer, a student). In addition, the user interface/usability of this educational app mash-up of sorts is a really important aspect of the design.

Next up: What type of interconnections will next generation digital learning environments require?

#1 of a series

There is a lot of excitement and curiosity regarding the concepts introduced in the EDUCAUSE Learning Initiative (ELI) research paper on the Next Generation Digital Learning Environment (NGDLE), which was based on focus group interactions with some 50-100 higher education edtech leaders.  I attended most of the focus group sessions myself, which also had great representation from IMS member organizations.

The plenary sessions for the upcoming May 2016 Learning Impact Leadership Institute are going to focus entirely on next generation digital learning.   I am writing a series of short topic blog posts beginning this week for the next several weeks with some of my thoughts on next generation digital learning environments to help get ready for the big event.  In this weekly blog series I want to write about how I am thinking about NGDLEs – with the hopes of spurring thoughts from others inside and out of the IMS community.

The LILI16 plenary lightning talks will be grappling with the concepts and the realities of next generation digital learning. And, in true IMS fashion, we will also be hearing from a panel of institutional leaders to get their pragmatic take on everything that was said.

So, what would I like to cover in this first post of the series? I want to cover a bit on the road that led us here and the road ahead. 

One of the cool things about the work of IMS is that while we are improving connectivity of edtech products today we are also establishing the foundation for better connectivity of learning apps, platforms, and resources for tomorrow.  This point is brought home in the ELI NGDLE research paper:

  1. Interoperability is the linchpin of the NGDLE. The ability to integrate tools and exchange content and learning data enables everything else.
  2. At the built layer, the NGDLE will be a confederation of IT systems, including content repositories, analytics engines, and a wide variety of applications and digital services.  One key to making such a confederation work will be full adherence to standards for interoperability, as well as for data and content exchange.

In a recent EDUCAUSE Review Viewpoints column entitled Foundations: Past and Future I describe how the NGDLE follows a prior paper helping to set the stage entitled A New Architecture for Learning. In the same column I highlight several of the most promising areas of interoperability for the NGDLE, which I will summarize here:

  1. Seamless integration of learning apps and learning platforms: Arguably, without the success so far of Learning Tools Interoperability (LTI) it is unlikely we would take seriously the idea that the NGDLE could be a “confederation of systems” that can be “mashed-up” by users. However, LTI has some road to travel to fully support the NGDLE.
  2. Publishing, sharing and finding learning apps & resources: What is the success model for this today in the consumer app world?   Allegiance to a single platform from a pretty limited set of platforms.  In education, how do we leverage the power of LTI with truly cross-platform curating of educational resources?
  3. Cross-application learning analytics: Confederation of systems sounds great. But to enable better learning we need confederation of actionable data and information.
  4. Accessibility and personalization:  To support accessibility and personalization across a confederation of apps and systems there needs to be a common language across those systems describing accessibility and personalization needs and capabilities.

The summary?  NGDLE requires cross-platform and cross-application integration that goes way beyond what is typically happening today in either higher education or K-12 IT departments. 

Despite the successes of standards like LTI to date, there should not be any irrational exuberance about the likelihood of magical interoperability that will enable NGDLE tomorrow.  Instead, we need to consider carefully where we are going and how we are going to get there – taking into account the realities of the edtech sector. Thinking through that path is what this blog series is all about.

Next up in the series: What is the right metaphor for thinking about Next Generation Digital Learning Environments?  See you then.

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