eLearning Roadtrip

(tap, tap) Hey, is this thing still on?

During the past 6 years I have had the remarkable experience of taking an idea about predictive analytics all the way from brain-storming with smart, crazy people who wanted to try something new and different with big data techniques, to getting multiple grants from the Gates Foundation to see if our idea worked. It involved founding a not-for-profit organization to validate our ideas in the commercial ed tech marketplace, to being acquired by Hobsons, an international commercial software provider.  

Not bad for someone who had really just wanted a voice in the learning analytics conversation that was more focused on students than VC.

Now that I've had a chance to get settled in a new research job at Hobsons,  I've been reflecting on whether or not this work I've been doing in analytics still counts as elearning.  I'm thinking that it does.  I'm thinking that now, more than ever, using digital tools to extend out expectations of learning is exactly the next phase in learning innovation we elearning advocates have been waiting for.

There are some who continue to describe elearning as the activities utilizing electronic technologies to access educational curriculum outside of a traditional classroom. In these cases, people are typically referring to an online course, program or degree. I get that. It helps define elearning as something distinct from other cognitive or pedagogical pursuits. Some people think of elearning as authoring, or collections of webcasts.  I've seen some people say that elearning is dying because mobile learning is about to replace it. 

For me, elearning is about leveraging technologies in support of designing, creating, producing, evaluating, distributing and managing learning experiences that engage and inspire, regardless of physical location or time. It's a much bigger tent than content or courseware.

My new job at Hobsons is a research job. I'm exploring learning impact and efficacy in the P-20 learning systems we depend on in the US to prepare our citizenry for college and and career success. I've been working on reports describing the impact of dual credit for accelerating college completion, on the impact of upward transfers from community colleges to completion institutions, on online learning efficacy, on the value of exploration and engagement in early childhood, the things we can do to support learning success among non-traditional students. 

I'm amazed to see, in all these discussions, the degree to which elearning has evolved beyond content and courseware. Today elearning is more about personalized, interactive, responsive experience.  If ed tech is where we concentrate on better tech tools, these days elearning encapsulates all we have learned to do to extend digitalization into our teaching and learning, education and training practices, constructs and values.

All this reflection made me realize I need a place to reflect on the transformative evolution of our practice as tech changes our expectations of our learning lives.

Looks like it's time to get back on the eLearning Roadtrip.

 

 

 

For my .EDU friends: Here's How Venture Capital Works

The education sector's current fascination with innovation, distruption and entrepreneurship is being fueled by the emergence of start-up commercial ventures that create new products and services as solutions for big hairy audacious problems plaguing today's schools and students. 

An April, 2014 post by CB Insights noted that investments in education technology hit a record high in Q1 2014 as investors poured more than $559 million across 103 deals in the first three months of this year.  Of note, Ed Tech funding in Q1 2014 represented nearly 45% of total funding to the sector in all of 2013. The record quarter comes after Ed Tech investments hit $1.25B across 378 deals in in 2013, the second-straight year of over $1B invested across the Ed Tech sector.  With everything from MOOCs to tutoring marketplaces to standardized APIs for K-12 schools getting funding, investors are clearly bullish on the education industry.

So what could possibly be wrong with getting rounds of other people's money to help you grow your big educational idea into a product that becomes the NEXT BIG THING?

Well, nothing...except you need to pay back all the money that everyone had given you. With interest and at a prenegotiated rate of return. That means that once you take someone else's money as an investment in your hot shot edu-preneurial company, EVERYTHING you do is going to be focused on paying your investors back. 

Aral Balkan recently blogged about his experience with a new social media platform called Ello. His post caught my eye because it included a pointed summary of how venture capital works. Having just spend the past several months at various educational technology meetings and trade shows where the buzz over acqusitions and investments is ever-present, I found myself sharing the following paragraphs with my friends from education who may not have had the experience of working with investors:

"Here’s how venture capital works: you go to an investor, before you’ve even built the thing you’re building and you tell them how you’re going to exit. It’s called an exit plan or exit strategy. You tell them, for example: “Hey, we’re going to get 100 million people using our new platform in two years time, how much will you give me for 100 million people?” And they go “Umm, we’ll give you this much for 100 million people because we’re pretty sure we can get that amount back several times over when we sell those 100 million people in an exit either to another company or in an IPO.”

"When you take venture capital, it is not a matter of if you’re going to sell your users, you already have. It’s called an exit plan. And no investor will give you venture capital without one. In the myopic and upside-down world of venture capital, exits precede the building of the actual thing itself. It would be a comedy if the repercussions of this toxic system were not so tragic.

"Let me put it bluntly: if a company has taken venture capital, you have already been sold. It’s not a matter of if, it’s simply a matter of when. (Unless the company goes under before it can exit, that is.)

"A venture-capital funded startup is a temporary company that has to convince enough people into using their platform so that they can make good on the exit they promised their investors at the very beginning. It is the opposite of a long-term, sustainable business." (Italics are mine).

You can read Aral Balkan's complete "Ello, Godbye" blogpost by clicking here.

I draw your attention to this article because every time I hear someone confide that their platform provider is a rising VC funded firm that is going for its next round of money, I wonder if these education customers understand the degree to which EVERYTHING their vendor provider must now do is focused on meeting their investors' expectations.

Alan Greenberg: Blackboard Reboots

I admire and respect Wainhouse Research analyst Alan Greenberg, so was quite interested to read his recent post in which he reflects on changes that Blackboard introduced at this year's Blackboard World. I, too, was impressed with the "new Blackboard" while at Blackboard World this year, and am really looking forward to diving into some of the work we (the PAR team) will be doing with the Blackboard team.

Please refer to Alan's newletter for the complete article and especially for his take on why Blackboard's changes are a big deal.

Here are a few "nuggets" from his post to whet your appetite for more......

Blackboard Reboots @ Blackboard World
Alan D. Greenberg 

In an effort to give institutions and schools more value and greater exposure to its technology sets, Blackboard has completely revamped its product line, now integrating together its product portfolio with a totally new user experience (UX) and a declared focus on learners. All teaching and learning solutions will now include Blackboard’s “base” learning management system (Blackboard Learn) and provide a full-featured online environment with course delivery, synchronous collaboration tools, mobile apps, and integration with and access to content. Technology adoption services are also included.  

A tiered set of solutions are aimed at helping the educational user community address challenges such as retention, student engagement, learning analytics, communications and standards preparedness. There are four higher education teaching and learning solutions, four higher education campus commerce and security solutions, and five K-12 solutions that center on teaching and learning and community engagement. The company is considering adding more solution sets for international markets.

Blackboard also plans to launch a new version of its learning environment that is delivered via the public cloud. Now the company is providing customers a full set of options: self-hosted, hosted in Blackboard’s private cloud, or via the public cloud. Word is this public cloud offering will be fully available sometime this month or in September. Being piloted in the public cloud is Blackboard’s Open Education powered by Blackboard, also announced at Blackboard World. This is a course platform that allows teachers and faculty to run public online courses and/or Massive Open Online Courses (MOOCs).

The company has created a customized learning and analytics offering available to the 259 higher education Internet2 members. The Internet2 NET+ offering will not only provide access to Blackboard’s solutions, but also will include robust analytic and learning outcomes tools, a cloud-based, cross-institutional content repository that supports most competitive LMS’s, and help desk and adoption services. Cornell University; the University of Nebraska — Lincoln; the University of Maryland, Baltimore County; the University of Texas at Arlington; and Virginia Commonwealth University had representatives who guided and shaped the Internet2 NET+ certified solution.

At the core of the offering, which is fully deployable now, is Blackboard’s Learning Insight solution, which is a full-featured online and mobile version of Blackboard Learn LMS and Blackboard Collaborate.

(Ellen's aside: yes, this means that Collaborate works in the browser. NO more Java downloads!)

FOR MORE, click here and scroll down for Alan's full article.

Karen Swan and the Amazing Multi-institutional PAR Student Success Matrix

Back in June 2013 the PAR Framework openly published an intervention assessment framework called the Student Success Matrix to help PAR members figure out how to respond when confronted with predictions of which students were likely to drop out. "What should we do to respond to these predictions showing our students at risk?" our members asked.  At that time Dr. Karen Swan, Stukel Distinguished Professor of Educational Leadership at the University of Illinois Springfield, reminded us that there are already lots and lots and lots of things that academic advisors, faculty and other student success professional already do to help students succeed in school. Going back through the professional literature, she and Dr. Peter Shea, SUNY-Albany, helped us find models of student engagement and participation relevant to our work at hand.

Karen proposed a framework to map interventions using predictor behaviors of success and points in the academic completion cycle.  Over the past year Karen and Peter have worked closely with Sandy Daston, PAR Framework Director of Student Success and the entire PAR SSMx working group (Hae Okimoto, University of Hawaii System; Jennifer Freed, Dan Huston, and Fermin Ornelas, Rio Salado College; David Shulman, Broward College; Denise Nadasen, Jack Neill and Karen Vignare, UMUC; Patsy Moskal and DeLayne Priest, University of Central Florida; Michelle Wiley, Penn State World Campus; Mysti Reneau, Community Colleges of Spokane) to refine processes and tools for promoting intervention measurement. This group of experienced educational practitioners and decisionmaker has helped determine what can actually be done for student at risk - even down to knowing how to support those 37 students that are most likely to fail Math 101 this semester. 

PAR institutions have begun the process of inventorying, tagging, describing measuring and evaluating literally hundreds of interventions currenty in use on campuses to help student succeed. Thanks to the SSMx we have accelerated the process of connecting predictions of risk to the interventions that will mitigate risk. 

This post is to acknowledge Karen's leadership and contributions to PAR's thinking about using predictions as cataysts for taking action, and for linking interventions to predictions to underscore the importance of linking predictions to action.

 

When I realized how easy is was to get started with learning analytics, I laughed out loud

I've always wanted to write a headline like that.  

If you are like me, any link suggesting that learning analytics can be easy is worth a quick look. Even if only to sneer at the temerity of whoever would say that. So, thank you for being curious enough to click. Now that I have your attention...

Getting started with a learning analytics initiatve doesn't need to be hard. What's hard is sustaining a learning analytics initiative IF one is only doing something, anything, as a pet project, an exploration, or a trial run because someone gave you free software. 

To paraphrase the incomparable Tina Turner, we're gonna start this learning anaytics conversation nice and easy (don't worry, no dancing required). Here we go. Five quick easy steps to get started:

(1) Start with a real problem to solve. Scope your problem statement so that you maximize your probabiities of  success. Do you have market conditions to address, sneaking suspicions that there might be trouble in River City that you'd better find out about before someone else does? Maybe places where you are pretty sure you can do a better job? You might want to think of something that will help you test the waters of change without putting yourself at risk of total humiliation if it doesn't work.

(2) Figure out who needs to be involved in creating the business case to get this problem solved. How much of a priority is solving the problem you identified going to be for others in your organization? Who need to be engaged and on-board to get this done? 

(3) Determine what you need to answer questions related to solving this problem. What information do you need? Who owns it? Where does it live? How are you going to secure it? How will it be analyzed? Who can see it, work with it, publish it? How will results be used? How long will the results live, and who will have access?

(4) Determine the necessary project talent to make sure you can get the work done. It's not just about having access to people who understand how to work with data. It's about having the right team in place across the board who can execute to plan and deliver results, and making sure that you have planned for enough of their time to be effective. How will you find them? What will you need to attract their attention and keep them engaged?

(5) Develop a bottom-up budget to see if you can afford to do what you want to do. Odds are, you will need more money than you have on hand. (Well... odds are that you will end up needing more money than you think you do, too, but that's a conversation for a later time). So, where might you find the funding to do what you want to do? Who else might be interested in getting involved in your great adventure?

Obviously each one of these steps can take on a life of its own once you get going, but as a place to begin these are a great way to get your arms around your big idea and see if its possible to move ahead.

NEW NSF REPORT: New Technology-based Models for Postsecondary Learning

In January 2013 I  participated in a workshop sponsored by the National Science Foundation to help establish a 10 year vision to reconceptualize postsecondary learning. This past week our co-convenors, Chris Dede, Harvard University and Eric Grimson, MIT, released the 47 page report that captured the results of that meeting. Entitled New Technology-based Models for Postsecondary Learning: Conceptual Frameworks and Research Agendas, this is a comprehensive overview of promises, opportunities and challenges that will keep all of we post-secondary learning stakeholders on our toes for the next decade.

You can download the working draft of this paper here.

The basic premises addressed include the following:

• Advances in technology and in knowledge about expertise, learning, and assessment have the potential to reshape the many forms of education and training past matriculation from high school.
• In the next decade, higher education, military and workplace training, and professional development must all transform to exploit the opportunities of a new era, leveraging emerging technology-based models that can make learning more efficient and possibly improve student support, all at lower cost for a broader range of learners. 
• Potential risks must be managed, including those arising from the disruption of established delivery economics in our current learning institutions, the variable quality of learning outcomes these new models offer today, and the technical and conceptual challenges of better understanding how to design, develop, and implement innovative capabilities in ways that reliably deliver on their promise.

Workshop participants developed a framework for understanding this sea change and sketched steps towards a research agenda for realizing its benefits while avoiding pitfalls.

Contributors to this report include Daniel E. Atkins, W.K. Kellogg Professor of Community Information, and Professor of Information and Computer Science, University of Michigan - Ann Arbor. Lori Breslow, Director, Teaching and Learning Laboratory, MIT. John Cherniavsky, Senior Advisor, Division of Research on Learning, NSF. J.D. Fletcher, Senior Research Staff Member, Institute for Defense Analyses. Diana Oblinger, President and CEO, EDUCAUSE. Roy Pea, David Jacks Professor of Education and Learning Sciences, Stanford University. James W. Pellegrino, Distinguished Professor and Co-Director, Learning Sciences Research Institute, University of Illinois at Chicago. Bror Saxberg, Chief Learning Officer, Kaplan, Inc. James H. Shelton III, Assistant Deputy Secretary for Innovation and Improvement,U.S. Department of Education. Russell Shilling, CAPT, MSC, USN, Program Manager, DARPA. Greg Tobin, President, English, Math, and Student Success, Pearson Higher Education and yours truly, Ellen Wagner, Executive Director, Western Interstate Commission for Higher Education Cooperative for Educational Technologies. Arthur Josephson, Harvard Graduate School of Education, was our researcher.

The Reason THIS EDUdotcom May Not Be As Different From Last Time As You Think

If there was ever any doubt that we are in the midst of a new dot.com boom for education, that doubt was removed at this week's SXSWEDU. The event brought entrepreneurs and educators to Austin, Texas for four days of panels and a competition for education start-ups. I had the great fun of participating in a panel discussion on "Are Courses a Commodity?" with Myk Garn, Mickey Revenaugh and Michael Horn. Vanessa Dennen and I helped Curt Bonk rehearse his "cage match" answers while sharing beers and ribs at one of the Cengage social events. I enjoyed hearing Bill Gates speak to the crowd about his vision for a transformed education system. It was definitely an interesting mix of energies.

Gotta say, not all of it felt all that good. This morning's Chronicle of Higher Education led with a headline that explicitly named the tensions between entrepreneurs and educators. You can read the Chronicle report here.

While I was there, I kept hearing that THIS dot.com is different because it's about education, and because the tech is better and data will inform us and investors are smarter and the market is ready, and there are business plans and people aren't just throwing exuberant ideas at the wall and hoping that something sticks. 

Really? 

I have to say that the confident assurances that this educational technology boom is different just didn't make me feel any less skeptical. Because in the same way that there are some who really DO believes that MOOCs are the birth of online learning, it is clear that there is an entire generation of investors and entrepreneurs who really DO seem to believe that the ideas thrown against the wall of the 1990s are somehow less legitimate than some of the ideas that are currently being thrown against the wall today.

So let me tell you why this particular new EDU.dot.com isn't as different as visonaries and investors would have you believe.

Ready?

It's because no matter how new your tech is or how great the idea is, or how impressive the possibilities are, or the circumstances or the bandwidth or the platform or the operating system we won't figure out how to crack the code on transformation until we change the most important part of the equation. And that is the human factor. Eventually it comes down to people being ready to embrace the change. The ability to ride out the hype cycle and get oneself to a true plateau of productivty will all come down to the degree we can induce people to change their ways, completely rethink their practices, and help them figure out how to use new tools toys, apps and the like deliver on their promises.

The excitement around innovative technology futures for teaching and learning has energized educational researchers to think broadly and deeply about the possibilities they represent.  The venture capital communities’ recognition that education may be ready for its “Internet moment” has also generated massive interest in developing promising ideas for products with commercial consideration.

Between these two exciting arenas of exploration live equally important opportunities for transformation that come from practice-focused solutions contributing to demonstrable improvements in student engagement, faculty performance, and institutional accountability. 

People. We've got to get ready, too.

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The Burden of Knowing

Important questions can get swept aside when the rumble of excitement about future possibilities are loudest. Nowhere is this more clear than in the emerging arena of learning analytics.

The fact that we can track information just about anytime, anyplace and on any device boggles the mind with possibilities. But it also begs a few questions: Does the fact that we will eventually be able to collect, track, link, visualize, tokenize, correlate, factor or parse data pulled through APIs mean that we should? When we can collect everything, will we know what to look for when applying various analysis technique among the research protocols? Will we recognize the answers we are looking for when we see them forming in the mists or hanging from the branch of a CHAID tree?

Perhaps even more to the point - will we be able to do anything meaningful with what we find? What are we going to DO, once we know?

The notion that all learning should be tracked, or that there is value to tracking activity stream level information, or that Hadoop-like pattern-seeking technologies will serve the needs of the learning enterprise in meaningful ways, must also consider what that capability is really worth to the enterprise. 

It  presumes that once we DO recognize new patterns of loss, momentum and opportunity that we are going to be able to do something about what has been found. 

But most people do not understand how long it is going to take the learning world at large to think of data as his or her friend. To see the results of analyses as benchmarks for better understanding performance, not as red flags requiring an intervention. One can only wonder how many enterprises will be slow to collect learning data worrying that they can't afford the Burden of Knowing what their data will reveal. 

 

 

 

eLearning Isn't Software

One of the reasons I attend learning technology conferences is that they offer a highly efficient way to scan the horizon for emerging trends likely to affect learning technology adoption. Conferences also provide a chance to see which "idea seeds" took root from among last year's various trends du jour.  

In yesterday's summary of reflections from the past several weeks of of higher education, elearning, and learning technology conferences, I made the following observation: 

On the commercial front...Pearson intends to own our universe. Adobe has pretty much given up on us. Just about everybody wants to sell us an "analytics solution". Or a mobile app.

I seem to have gotten the attention of the Adobe elearning team. I think I may have hurt their feelings. Understandably. They will tell you that they are the market leader in elearning. There's Captivate. And Connect. And eLearning Suite.

I simply respond by acknowledging that those are fine products. But they are not elearning. Because no matter how much one might believe it to be so...elearning isn't software. eLearning is not a platform, unless one is speaking allegorically. eLearning is something people DO with software. It's a much bigger universe than rapid authoring, web conferencing, and content creation.

The fact that I am saying these words... well...

 

Lessons Revisited: RADAR, Pearl Harbor and Paying Attention to Evidence

One of our Sage Road Solutions LLC clients, the Western Interstate Commission for Higher Education, is holding its biannual meeting at the BYU Hawaii campus on the island of Oahu this week. Having spent the past several days in Denver hosting the annual meeting of the WICHE Cooperative for Educational Telecommunications, known as WCET), I'm still running on Mountain time. I woke up early, so I decided to take advantage of being in this glorious location to take a walk along the beach.

About 200 yards from the hotel an historical marker notes the location of the Opana mobile RADAR site. The story accompanying the marker offers an interesting object lesson for those of us trying to bring innovative applications of technology to the learning technology metaverse.

According to Wikipedia the term RADAR was coined in 1940 by the U.S. Navy standing for radio detection and ranging. It was brand new technology, showing enough promise that pilot programs were launched to test its utility. In 1941, a number of mobile radar trucks were deployed on Oahu to keep an eye on the skies near Hickam Field.

 

Early on the morning of December 7, 1941, two soldiers stationed at the mobile radar site near Opana Point saw electronic blips of what looked like many planes approaching the island. Reporting their findings, they were told that what they were seeing were *probably* planes expected from California, and not to worry about it.  Consequently this information was never reported to those in command. Shortly thereafter, the Japanese planes detected by the RADAR bombed Hickam Field and Pearl Harbor, destroying US ships and planes, leading to the US's declaration of war on Japan and igniting US involvement in World War II.

The historical information was certainly interesting in its own right. The narrative that accompanied the marker, however, was particularly striking:

"The failure to warn the Army or Navy command in Hawaii was not a failure of the technology as much as it was a failure of organization. While the technology of RADAR functioned as intended and detected the incoming planes, there was no way to accurately assess the information and communicate this knowledge to those in command." 

So, let's fast forward to October, 2011. On Thursday of this past week the WCET team working on our Predictive Analytics Reporting (PAR) Framework project revealed some of the first findings from our ground-breaking big data project. At the risk of sounding hyperbolic, the descriptive, inferential and predictive techniques being applied to this massive data set are providing some eye-opening perspectives on variables affecting student loss and momentum. As noted in a Forbes.com online article featuring Phil Ice, our project's principal investigator (who, by the way, really hates being called "the other Dr. Phil"...so please don't) these results are going to rock the way that educational decision-makers think about everything from college admissions, student services, technology investments and even "best practices" for online learning. 

Still, I have a feeling that these "big data" results will go through a period of being pooh-poohed by decision-makers who will have a hard time letting go of null hypothesis research methods. Traditional researchers' disdain for the so-called data mining techniques associated with pattern strategy and business intelligence used in other sectors are likely to get in the way. For many traditional researchers, educational data mining is a little bit like a stupid pet trick - even though these same folks really seem to like the convenience of Amazon shopping recomendations, Netflix movie recommendations and Pandora music recommendations.

I can't help but wonder if the findings about student loss and momentum that the cracker-jack research crew are sharing will be disregarded very much in the same way that Army and Navy command dismissed the evidence that Pearl Harbor was in harm's way because the techniques are too new to be taken seriously. I just hope that we can figure out how to help people pay attention to evidence before it is too late.