eLearning Roadtrip

20 "eLearnings" From Two Months on the Road(trip)

Been a busy couple of months of elearning road-trips. From EDUCAUSE to Online EDUCA, from WCET to WICHE, from DevLearn to AECT (with a little bit of virtual Sloan-C tossed in for good measure). Literally thousands of plenaries, presentations, and poster sessions from which to choose, along with hundreds of vendor stands and trade show booths. Here are some of my big take-aways:

• Hooray and congratulations! This distance/online/elearning thing we do has tipped into mainstream consciousness. Let's give a cheer for the researchers, the teachers, the authors, the artists, the technologists, the producers, the analysts and the evaluators who have made this happen. We rock.
• We matter enough that governments want to regulate us. Congressmembers rail against us. No more flying under the radar.
• Analytics are hot, hot, hot. Learning analytics, content analytics, web analytics, engagement analytics, to name a few.
• Speaking of analytics...mathematically speaking, a learning outcome is pretty much the same as a point of sale. (Thank you, Phil Ice.)
• Second Life is dead, dead, dead. Sorry.
• Mobile is the future.  Smartphones and tablets and readers, oh, my.
• Game based learning has a long way to go before people take it seriously.
• High quality video conferencing is making a comeback.
• We may get inspired by big ideas, but we are moved to action by fear, uncertainty and dread.
• 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.
• People really need to quit thinking that "open" is the same as "free".
• It's a lot easier to pontificate about the importance of change than it is to do things differently.
• There is a lot of research out there. Some of it is useful. 
• Empirical evidence doesn't need to be quantitative...but it does need to be a little more robust than simply pointing to people who are doing the same things.
• Quality is rarely absolute. It's contextual and situational. It may make more sense to think about "effective practices" rather than "best practice".
• Practitioners who make big sweeping statements without doing any background work on what others may have already been doing, saying or thinking end up sounding just a little bit naive and foolish. C'mon, people...use The Google.
• On the Internet, nobody knows you're a dog...but EVERYONE knows if you are not prepared.
• One can pack a lot of snark in 140 characters.
• Learning is as natural as breathing. Learning really isn't the problem. Enabling meaningful, intentional outcomes and creating experiences that engage and inspire without costing an arm and a leg and without killing our interest and enthusiam for learning is the problem. 
• Sometimes you just need to show up.

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.

 

Big Data Comes to US Higher Education

WCET, the WICHE Cooperative for Educational Technologies, today announced the successful federation of datasets from the six institutions participating in the PAR (Predictive Analytics Reporting) Framework proof of concept project, just four months after the project’s early June launch. The goal of the PAR Framework is to identify variables that influence student retention and progression and to determine the impact of various demographic data on factors influencing loss and momentum. The data will be used to explore patterns that emerge when the datasets from considerably different institutions are analyzed as a single, unified sample. 

The dataset includes over 640,000 anonymized student records and over 3 million course level records, focusing on 33 common variables. The institutions represent public/private, two-year/four-year, and publicly-funded and proprietary institutions. 

“We have been using analytics as a tool for improving student retention and progression for several years,” said Dr. Phil Ice, vice president, research & development, American Public University System, and principal investigator of the PAR Framework Project. “Unifying records from multiple schools has the potential to expose generalizable patterns that can provide guidance to institutions across the board, regardless of their internal level of analytics expertise.” Ice continued, “In higher education, no predictive analytics project has been able to use a multi-institutional sample of this size. As a researcher, having a sample size of this number changes everything.” 

The WCET member institutions engaged in the PAR Framework project include American Public University System, Colorado Community College System, Rio Salado College, University of Hawaii System, University of Illinois Springfield, and the University of Phoenix. Each institution obtained IRB (Institutional Review Board) approval. All data was anonymized and encrypted to ensure that no data are personally identifiable. 

“We had been warned that we could never find six schools willing to collaborate on something as sensitive as an institutional student and course level data federation project,” noted Ellen Wagner, WCET Executive Director. “It’s exciting to see how forward-thinking WCET member institutions are bringing the power of “big data” to post-secondary education in the US. The magnitude of the data set unprecedented and the diversity of the participating institutions will provide us granular insight into similarities and differences across higher education institutions in the for profit, public and community college segments.” 

A summary of first findings are scheduled for presentations at the 23rd Annual WCET Conference in Denver, Colorado October 27th (https://wcetconference.wiche.edu/).

Thought You Might be Interested...

...in some of the thoughts I shared with my WCET crew today about learning analytics and lessons we can learn from Moneyball. It's an extension of my eLearning Roadtrip post on the same general topic.

I suppose this gives you an idea of what is top-of-mind for me these days. Well, that and wanting to raise the bar on online learning excellence. Simple pleasures.

If you are interested in taking a look at my WCET post, please click here. 

While there, please take a look around at what the fine folks at the WICHE Cooperative for Educational Technologies are doing these days. If you happen to care about accelerating the adoption of learning technologies innovation in practice you might find that WCET is engaged in work that matters to you.

As a matter of fact....WCET's Annual Meeting is being held in Denver October 26-29. We will be sharing some of the preliminary results from our Predictive Analytics Reporting Framework, along with lots of other information about learning analytics and other emerging topics of interest to online learning and learning technology professionals. Might be a great time to come see what the WCET buzz is all about.

When I Think of the Future of Online Learning

I am attending a Summit later this week. The University Professional and Continuing Educational Association and the Association for Continuing Higher Education are co-hosting a sold out invitational meeting to consider the Future of Online Learning. Many dozens of learning leaders will be in attendence. I am looking forward to hearing what everyone has to say.

As a long-time online learning / elearning / distance learning / teletraining kinda gal, these kinds of events please me in an odd, parental sort of way. It is quite satisfying to see how over the past more than 25 years of grinding their way into teaching practice, learning technologies now routinely extend the reach of the traditional classroom. Online learning has tipped into mainstream consciousness, even if mainstream exceptance continues to be somewhat elusive. 

Since I DO have some skin in this online learning game, let me tell you some of the things I hope we will hear about during the next few days:

• I hope we will hear that it is time to move past online learning as a technological analog of the traditional college classroom.
• I want us to talk openly about getting serious about high quality, online learning experiences that scale.
• I want to hear how more students will have the opportunity to achieve the dream of a college education.
• I want to hear more about the $10,000 degree. Or the $5,000 degree. Either one.
• I want to hear how we will make sure that online students can quit being ashamed to say they got their degree from an online school.
• I want to revisit how adult learners demonstrate that the knowledge they have accrued outside the classroom is a legitimate part of competency certification.  
• I want to hear how the campus learning portal / LMS is being deployed in new and innovative ways, 
• I want to hear how online learning professionals are going to use descriptive, inferential and predictive analysis of de-identified student records to better predict when students might benefit from a bit of extra help to stay on academic track.
• I want to hear how institutions are going to make online learning experiences more compelling,  engaging, personalized and professionally relevant.
• I want to hear that there is room for informal collaborative learning moments in every student's program of study.
• I want to see more attention paid to interactive digital learning content - PDFs and digital textbooks, apps and learning objects - that students produce and publish.
• I want to understand how OER will sustain itself.
• I want to understand how mobility is changing the online learning game, and how social media bring real-time interpersonal interactivity to our conversations.
• I want to see the use of game mechanics and gamification extend our thinking about how to motivate and engage learners without turning games into the next generation of crappy elearning.

From everything I can see on that horizon these issues are all going to be part of the future of online learning. With respect, they are already part of the present. IMHO, it's time to make dealing with these issues part of our practice. Looking forward to what comes next.

 

WCET Receives Grant for Groundbreaking Higher Education Analytic Research

I am pleased to share the following good news.

WICHE, the Western Interstate Commission for Higher Education, announced today that WCET, the WICHE Cooperative for Educational Technologies, has been awarded a $1,000,000 grant from the Bill & Melinda Gates Foundation to fund an initiative to unify student data from six U.S. institutions and demonstrate the effective use of predictive analytic methods for improving student outcomes. The goal is to identify variables that influence student retention and progression, and guide decision-making that improves postsecondary student completion in the U.S.

This grant for the Predictive Analytics Reporting (PAR) Framework will aggregate data representing more than 400,000 student records from across six WCET member institutions: American Public University System, Colorado Community College System, Rio Salado College, University of Hawaii System, University of Illinois Springfield, and the University of Phoenix. Each participating institution has been exploring or implementing descriptive, inferential or predictive analytics projects on their own student data; the PAR Framework expands on this work through exploration of patterns that can be derived when the six institutional datasets are considered as a single, unified sample.

The principal investigator is Phil Ice, Ed.D., American Public University System (APUS). The project will incorporate many of the best practices and award-winning predictive analytical methods for which Phil has been recognized by the Sloan Consortium and for which project partner Dr. Vernon Smith, Rio Salado College, has won the prestigious WCET Outstanding Work (WOW) award. WCET has appointed Beth Davis, WCET, to serve as the project director.

The WICHE Cooperative for Educational Technologies (WCET) is a cooperative, membership-driven, non-profit provider of solutions and services that accelerate the adoption of effective practices and policies, advancing excellence in technology-enhanced teaching and learning in higher education. More information about WCET’s institutional membership resources, services and common interest groups can be found on here.

eBang Theory, Say "Hey" to High Quality Online Learning That Scales

Once upon a time, equity analyst Howard Block, Ph.D. wrote a report entitled The e-Bang Theory: Education Industry Overview 1999 Illuminismo, Volume 2  (San Francisco: Banc of America Securities Equity Research, Montgomery Division, September 1999). This report is the one credited with igniting the explosion of interest in financial markets that legitimized what is known today as eLearning.

In this report, Block outlined the tenets of his theory that explained why and how investing in businesses that featured technology to facilitate online learning would probably make investors and the companies in which they invested a lot of money. 

I attended a meeting at SRI International in Menlo Park, CA just after this report was released. I still remember the electricity, the "e" in the air. Probably tells you a lot about the times that everyone devoured anything from analysts that talked about investing opportunities using web technologies and the related products and services that accompany them to market, to school and to work.

In making the case that 1999 was the time for a new model of education - elearning - to appear on the horizon, Block noted that:

• "The economy is quickly becoming dependent upon human capital, which forces all of us to increase our aptitude at managing and productively employing human capital, a task incumbent upon all of our learning systems.

• "Political initiatives are inviting more businesses inside the school house door than every before in the history of public education. these initiatives include charter school legislation and voucher programs.

• "The inexorable technological revolution continuously overhauls the workplace, thereby forcing workers to treat learning as a basic part of their job description. Technology is not only a driver for more learning but it is also an enablers of electronic learning (e-learning). The intellectual demands of the economy are outstripping our capacity to satisfy it. (Block, 1999, P.3)

(Danger, Will Robinson. We seem to have slipped through a hole in the time space continuum. Isn't this the same things we are still talking about today??)

Block went on to define elearning as the convergence of the internet and education and identified 15 unique benefits associated with it:

1. Available at any time. "It's always there!"
2. Accessible from any location "I can always get to it"
3. Multimedia content: use of audio, video, interactive chat, text, etc.
4. Accommodates individual learning styles: self-paced, asynchronous collaborative, synchronous collaborative.
5. Hyperlearning as contrasted with static text, elearning has the capacity to link with the other resources (simulations, other content, study groups, etc) that can enhance the learning experience and avoid the linear learning dictated by textbooks. The self-directed nature of elearning allows hyperlearning.
6. Blindness of the learning engagement: some learners who are inhibited in a classroom may increase engagement online
7. Learner-centered learning: The learner is not a passive participant but a proactive searcher and finder of information.
8. Modularity of presentation: The content's architecture is modular, which facilitates different construction of learning design in both design and length.
9. Manageable structure: The electronic infrastructure supports managed and measurable interactions between advisers and learners
10. Ability to measure the effectiveness of the program. eLearning software empowers administrators to track performance and measures ROI. In addition, monitoring usage by user is simpler, i.e., the number of downloads per user can be measured. This helps training managers to evaluate cost-effectiveness and provides assistance with license negotiations based on estimated use.
11. Simpler data management, The rapid rate with which new learning products are introduced and older products become obsolete creates a challenge for individuals charged with updating libraries. However, if a single version of each product is kept on a host, users get instantaneous access and updated components.
12. Cost savings: provides an efficient and cost-effective model for education
13. Revenue enhancement: provides a way for campuses to expand classroom enrollments without using bricks and mortar.
14. Greater storage capacity. The Internet has so much more capacity than most physical locations or a user's hard drive. This allows learners to access more products and lets the adviser mix and match courseware activities to fit specific needs. Learners can preview presentations of different courses prior to selecting one, or they can access a specific slide from thousands.
15. Individual education programs (IEP) can be generated from a combination of the historical record of the student's prior learning (from monitored usage) and the vast data stored on the server. As student's progress, information is delivered based on what they learned and how they've performed. For example, a student would log on to the learning server and a customized course would be generated from the content data base that knows which courses the learner took, how well she did, what her job description is, what problem is most pressing. This dimension serves to focus the curriculum on skill gaps, saving organizations both time and money. A by-product of IEPs, in our view, is increased motivation from the self-centered nature of the experience.

One has to wonder if maybe our agenda for the next gen of elearning, the Web 2.0 era, should be aimed at delivering on some of these promises that Block and the investment communities were making on our behalf as long as ten years ago. Because when I think about some of the big ideas that were shared among the participants of a fantastic think tank experience I had a few weeks ago at Rio Salado College in Tempe Arizona and what we can finally do deliver on these 15 promises described above...well, I have to say, I am excited about all the new opportunities that are startiong to emerge on the horizon.

And THAT brings me to my real subject of today's blogpost.

Imagine how excited I am that one of the hottest new emerging trends that is going to rock post-secondary education is a return to High Quality. Scalable. Online. Howard Block gave us the roadmpap more than a decade ago. And now, as we all try to figure out how to navigate in what Josh Jarrett calls "The New Normal", it seems as if High Quality, Scale and Online easily fit in the same sentence. Again.

There are  initiatives on the horizon that will challenge the way we think about our practice. Hopefully give us all some tools and techniques to think about achieving our goals in creative new ways. I have to say, when I think about where  the next waves of innovation are likely to emerge in my little slice of the education ecosystem I start getting butterflies in my stomach. Excited butterflies.  

Next stop on the journey to find high quality online learning that scales: We Go to Rio.

In Case You Missed This Part (with thnx 2 @oldaily)

Picking up a thread from yesterday...

I continue to believe that the most immediate opportunity for demonstrating the value of learning analytics in institutions and enterprises comes from mining existing pools of data in creative and thoughtful ways. But Stephen Downes was absolutely right in his April 24th critique of my post Data Change Everything. He said that the emerging learning analytics paradigms will benefit not from mining old data new ways, but in looking for better ways to collect new information.

Doing old things in new ways is an important step toward change. Transformation means doing new things in new ways.

Gamification offers one very exciting new possibility for doing just exactly that. The mobile web opens lots of data collection opportunities and there are bound to be lots more.

Just think about it.

When Learning Analytics Meet Gamification

Great minds are already at work on a very big idea: What if we morph the emerging fascination with massive N predictive learning analytics with a mechanism for collecting massive transactional behavioral data where millions and millions of subjects already willingly volunteer their input?

Learning Analytics, meet Gamification.

I don't like the term gamificiation, either. But I'm not talking about the introduction of check-ins and badges to everything. THAT is something I would much prefer to call ... playing with games. Rather, I am talking about the benefits of considering the rich massive N data source for tracking the behavioral transactions of game play. And being able to subject that big pool of data to a battery of descriptive, inferential and predictive statistical methods to identify points of loss and momentum. 

Anne Derryberry, a 2010-2011 Fellow at the Reynolds Journalism Institute, University of Missouri School of Journalism, has been applying what she calls purpose-driven game design to journalism and journalism education. She has focused on games as an emerging medium and distribution channel for news-telling, particularly as a means to induce community engagement and civic participation.

Her research is also indicating ways to track and analyze behavioral transactions and player interactions of an online game to enable new ways to understand points of loss and momentum in communications- related endeavors. She's coined the term "journalytics" to describe how analytics and purpose-driven game design mesh to give journalism and news outlets the metrics they need to focus and adjust their interaction strategies.

Relevant for journalism. AND education. IMHO. Early and preliminary results. But still. We in the learning world can benefit from some of these ideas.

Anne will be quick to point out that America's Army and other MMOGs have been using game play for recruitment, community building and even into predictive performance advising and professional development guidance for a while now. She has been tracking serious games for learning, training and performance support for the past few years at her blog, I'm Serious.net. But she was fascinated at seeing if the things she saw in these game-based learning designs could be relevant in other disciplines. This past year she developed noozYou as a vehicle for testing some of her hypotheses about purpose-driven game design in journalism with Mizzou journalism students. 

She can tell you about this far, far better than I can. So I am going to suggest that you follow her on Twitter at @aderryberry and @noozYou. It's been fascinating stuff.

I WILL tell you she's been advising the Sage Road crew as we've been pushing our own predictive analytics horizons. We think this approach holds great promise and has immediate, direct positive implications for the new kinds of data collection opportunities.

I continue to believe the most immediate opportunity for demonstrating the value of learning analytics in institutions and enterprises is to mine existing pools of data in creative and thoughtful ways. But Stephen Downes was absolutely right in his April 24th critique of my post Data Change Everything. He said that some of the emerging learning analytics paradigms will benefit not from mining old data new ways, but in looking for better ways to collect new information. Here is one very exciting new possibility for doing just exactly that.

 

...And Another Thing (about Predictive Analytics)

Judging by some of the reactions I have been getting to my Data Change Everything blogpost last night, I would say I've touched a bit of a nerve. Good.

People get ready, there a change a comin'.

Just a few more random, ancillary analytical thoughts:

Predictive analytics are not just used in for-profit universities. While institutions like the University of Phoenix and APUS are investing in analytics tools to help them improve services and customize the experience of learning online, forward thinking publicly funded institutions including Rio Salado College and the Colorado Community College System are doing the same kinds of things.

Predictive analytics are also not just used with online learning (and, by the way, online learning is not the same thing as for profit education.) But with so many of the transactions of online teaching and learning captured in various technology systems, it does seem like fertile ground for finding out what learning analytics may be able to reveal. Which is why you are seeing so many researchers/companies/foundations moving into this space these days. Learning analytics are hot, hot, hot.

Some researchers respond quite negatively to predictive analytics in education. I've heard mutterings of Orwellian conspiracies and dismissive comments about how data-mining is so... ad hoc.  True enough. But remember, analytics aren't really about research, they are more about supporting decisions. That's different. And it's about reliability and convenience. That's also different.

I mentioned some of the most familiar uses of predictive analytics in consumer life - Amazon shopping and Netflix movies. iTunes Genius recommendations are another example. They help you narrow your search. Sometimes they suggest just the right thing. But I forgot to mention one of the most popular consumer use of predictive analytics.

Any guesses??

<drumroll>....Dating sites. Match.com and that ilk. No matter how you feel about online dating, here is an impressive statistic: 1 one of 8 American marriages come from an online dating relationship. 

Pretty good completion rate, if you ask me. 

That is all. For now.