Report on Personalized Learning Ithaka S+R has been steadily producing studies and reports on the state of higher education. The most recent is of particular interest to those of us concerned with the role of adaptive learning: "Personalizing Post-Secondary Education: An Overview of Adaptive Learning Solutions for Higher Education". It reviews thirteen adaptive learning providers, focusing on the high-level technical and pedagogical characteristics of their solutions; business models, content models and partnerships. More here: Personalizing Post-Secondary Education.  http://www.sr.ithaka.org/research-publications/personalizing-post-secondary-education The Presidents Speak Two recent events, one at the Brookings Institute, the other sponsored by ACE, included talks by university presidents about the shifting conditions of US higher education. Above average stuff.  "Higher Education Reform: Affordability, Accountability and Value". Keynote: Purdue University President Mitchell E. Daniels, Jr. & "Information Technology and the Future of Teaching and Learning." Stanford University President John L. Hennessy (The 2015 Robert H. Atwell Lecture) The 2015 Atwell Lecture: Stanford President John L. Hennessy Examples of Innovation Nature magazine collected some very interesting examples of innovations at universities. Inspiring efforts. Check out The University Experiment: Campus as Laboratory. More here. The University Experiment: Campus as Laboratory  

Kevin Carey is an American higher education writer and policy analyst. He is serving as Director of the Education Policy Program at the New America Foundation, a non-profit, non-partisan research organization based in Washington, D.C. We asked Kevin about his recent, provocative book, The End of College: Creating the Future of Learning and the University of Everywhere.  :: Before we get to the substance of the book, I’d like to ask about its reception. If you’re like most writers, you are surprised by some of the interpretations of your work. What responses did you not anticipate?  Most of the book takes place in the past and the present, telling the story of how American colleges and universities became what they are and how information technology might allow them to become something new. In the last two chapters, I present some ideas about what the future might bring. As I see it, some students will learn mostly online, particularly as human-computer interaction and digital learning environments improve. But many will continue to attend in-person institutions that provide direct relationships with peers, teachers, and mentors. Those institutions won’t, however, have to be colleges as we know them today. In other words, the future of higher education won’t be solitary, with everyone but an elite few learning alone in front of machines. Some of the criticism of the book has left out that last part, which is disappointing. Then again, it’s been out for less than a month, so maybe people haven’t gotten all the way to the end yet. The future of higher education you present in "The End of College" places more responsibility on individual learners to design and follow-through on their own studies. Self-direction has long been an instructional ideal - we want students to take responsibility for their own learning. But there’s a fear that they simply won’t, at least not to the extent required in the scenario you’ve laid out in "The End of College".  People vary a great deal in their educational skills and motivational constructs. Some of them need a lot more support, or different kinds of support, than others. Existing colleges are often impersonal and cookie-cutter in how they treat students, and I think the future will provide more opportunities for customization, personalization, and variation in organizational philosophy. Traditional colleges are less diverse than they like to believe — they share a great deal of the same organizational DNA.  I also think there’s an important distinction between "design" and "follow-through." Pretty much everyone needs guidance on the design of their studies. Effective pure auto-didacticism is rare. In many ways, that’s the very definition of education: creating an environment and set of relationships that deliberately guide people in the acquisition of skills, knowledge, and habits of mind. On the follow-through side, I think simply being better will accomplish a great deal. Good education challenges people to work hard and move out of their comfort zones, but doesn’t push them past the threshold of total frustration. That’s crucial and not easy to accomplish, which is exactly why people like the cognitive tutor designers at Carnegie Mellon are working to solve the problem. So there’s no reason to believe the future of higher education will reduce the amount of necessary support that students receive. Quite the opposite. It’s been suggested that your vision for higher education is best suited to well-supported, above average students - leading to a sharper class divide. Poorer students get MOOCs, and the 1% get 4 years at Yale. How do we ensure that this isn’t the case?  Only the 1% get 4 years at Yale now. That’s the way it has always been, and always will be, as long going to Yale means living in a faux-Gothic building in New Haven, Connecticut. So the question is, can we radically expand the number of people of people who have access to the educational riches of Yale, and institutions like it? The answer is clearly "yes." You can already access the lectures, courses, syllabi, assignments, and exams at Yale, for free. That problem has been solved. The question, then, is what additional educational resources does Yale offer, and can we provide them to many students at an affordable price? The existence of organizations like the Minerva Project, which is just as selective as Yale and also provides a rich liberal arts curriculum, for about one-third the tuition, suggest that we can. There can be many more organizations like that. A common characteristic of discussions about change in higher education is the tendency for lines to be drawn between commentators and initiatives from within higher education (e.g. faculty) and those outside (e.g. think-tanks, entrepreneurs). Several of the people and initiatives you highlighted in the book are from outside higher ed proper (even some of the MOOC providers felt compelled to step outside of their institutions to bring something to the masses). And you, as an analyst at a think-tank, might also be considered an outsider. Is this divide significant? What might be its’ origins?  It’s significant, but it can be overstated. Anant Agarwal left a great, prestigious job as the director of the MIT Computer Science and Artificial Intelligence Laboratory to head up edX. This involved moving from a building on the MIT campus to a building located one block away from the MIT campus. I interviewed Robert Lue, faculty director of HarvardX, in his office in the Harvard natural sciences building. He hasn’t gone anywhere. He said to me, "HarvardX is Harvard. It is us." The West Coast MOOC providers have definitely stepped outside the academy into the world of for-profit, venture-backed companies, but that’s an incredibly porous border. The companies are located in Palo Alto and some of the founders still teach at Stanford. That said, it’s not surprising that people who are currently employed by colleges are only going to go so far in agreeing with the thesis of a book titled "The End of College." In a review of your book, Don Heller wrote the following: "In his claim that MOOCs and other online learning materials will replace colleges and universities, Carey also provides a very narrow view of the goals of higher education. A bachelor’s degree is more than just a collection of individual courses; college — when done right — also satisfies other developmental objectives, including extracurricular learning, developing interpersonal communication skills (of both the online and face-to-face variety), and instilling a sense of an individual’s role in a democratic society." This is a common criticism of online higher education. But it’s also odd given that online higher education didn’t set out to supplant all aspects of the traditional college experience - its’ focus is instruction. On the one hand, I recognize that meeting your spouse or having inebriated conversations with other students at the campus pub is important - it was for me. But isn’t also the case that these extracurricular dimensions of higher education are primarily accidents of history - rather than by design. Is it the case that our institutions set out to provide instruction, but these other dimensions then began to form around the core mission?  Per my response above — I have a lot of respect for Don as a scholar of education but I think his critique ignores some of what I say at the end of the book. I quote from some of the relevant parts of the book here http://www.edcentral.org/universityofeverywhere/ in explaining why. In short: there’s no reason why we can’t have the best of both worlds, online and in-person, for a lot less money than traditional colleges and universities charge today. If alternative credentials grow in stature and students gain access to more information about the actual learning gains that a particular provider can offer, are we setting in motion a highly competitive education market (i.e. informed consumers with choice)? Are our institutions ready for this? Will they allow it?  Yes, No, and It won’t be up to them. We need a competitive market in providing students a great education. We really don’t have one now. Educational institutions are complicated and hard to understand and most consumers are naive. There’s a dangerous conflation of price and quality. Existing institutions are theoretically in a great position to take advantage of this opportunity, because they employ a lot of smart, knowledgeable educators and have brand names that people trust. But many are deeply committed to not changing, are they are likely to struggle. They’ll fight opening up the market to new credentials, for obvious reasons of self-interest, but that’s not a fight that can be won forever. If you’re battling against better information, your days are numbered.  

The pace at which new ideas, initiatives and technologies are surfacing in higher education continues to quicken. Universities, vendors, philanthropists and non-profit organisations are responding aggressively to the growing pressure to improve student outcomes, reduce costs, and expand our capacity to serve under-represented student populations. However, a remarkable number of these efforts will fail to take hold. Some will run out of money. Others simply won’t work. But many — despite the benefits they may offer —  will fail because they don’t "fit". That is, the innovation isn’t aligned with the unique organizational structure, processes, reward systems and culture of our colleges and universities. Consider the LMS and MOOCs, two influential innovations from the world of edtech. Like a Glove: The LMS A quick scan of the original business plans prepared LMS companies will uncover a passage that reads something like this: "Our LMS . . . enables individual educators to create and deliver online education with limited technical expertise and minimal technical assistance". The technology allows individual educators to continue to create and manage their own courses despite the introduction of "high-tech" (as it was called then) into the teaching and learning process. The rapid (and now almost universal adoption) of the LMS in higher education was possible precisely because it fit into the existing organizational processes, roles, and hierarchy. It made it relatively simple for institutions to "put their courses online" without disrupting the existing institutional model. Yes, most institutions created service departments to provide technical and instructional design support, but these departments were designed to get the instructor working independently as soon as possible. A La MOOCs On the other hand . . . After a honeymoon of roughly 18 months, during which MOOCs were interpreted as either the end of higher ed as we know it or its saviour, this particular innovation began slowly backing away from higher education. Despite its historical roots in higher education, it’s now in search of potentially more forgiving venues, such as the retail and corporate training market. At least two obstacles stand in the way of MOOCs easily integrating into higher education: the economics of credentials and conventional understanding of the proper role and responsibilities for faculty. :: Until alternative forms of credentialing, such as badges, gain greater acceptance, the value of MOOCs is highly contingent on their being accepted for formal credit at colleges and universities. The path to credit for MOOCs is anything but straightforward — here are a few reasons why. Were MOOCs widely accepted for credit, the institutions offering MOOCs (at this time, primarily selective institutions) would be able to increase revenue, reach new learners, and extend the reach of the institution’s brand. In any other market, this would be ideal and straightforward. But extending access to an elite university credit in this way could, first of all, weaken the institution’s hard-won exclusivity — a core source of value upon which so much of its status is tied. :: At the same time, it’s unlikely that only a small subset of institutions would offer MOOCs, once widely accepted for credit. Other less prestigious institutions — motivated by tightening budgets and in pursuit of new revenue streams — would quickly follow suit. They’d have no choice, given the very real possibility that their students could now enrol in cheaper courses from more prestigious institutions. So, in time, the market for MOOCs would be flush with suppliers. The financial benefit to any institution, then, would require the total size of the market to grow as quickly as supply. Early indications suggest that almost all of the growth would be from students in developing nations. :: Competition in an open MOOC market may also force selective institutions to compete for learners on the basis of criteria for which they are not well-suited. US higher education is diverse and stratified. Institutions at the top of the heap are typically defined by high-levels of research productivity, award-winning faculty, high tuition ("sticker prices"), and tough admissions standards. These characteristics, though, don’t necessarily translate into a capacity to produce and deliver high quality online learning. Indeed, in a robust market of MOOCs, the advantage will — all things being equal — go to those institutions that have long invested in online learning and that, more generally, see teaching and learning as core to their mission. The current advantages enjoyed by elite institutions would be reduced in a competitive MOOC market. Once pulled out of its typical context, and its wares placed side-by-side with competing courses, a new criteria emerges. Here, institutions are forced to compete on the basis of instructional quality, relevance, production value, ease of use, and other digital-borne criteria. Of course, it’s entirely possible that elite institutions could use their relatively strong financial status to outspend the competition, but that’s not the basis of a competitive advantage. If this is a true marketplace, these additional costs will eventually need to be recovered. :: The issue of "fit" is also shaped by our common notions of what constitutes the proper role and responsibilities of faculty. While much has been made of the poor academic results of the Udacity pilot at San Jose State University, what’s less often discussed is the concerns among SJSU faculty about the effects of MOOCs on their vulnerability in the labour market. In a letter penned a letter to Michael Sandel, the Harvard prof who taught the MOOC, the faculty wrote: "Let’s not kid ourselves; administrators at the CSU are beginning a process of replacing faculty with cheap online education." Putting a slightly different spin on it, Gianpiero Petriglieri of INSEAD turned down an offer to participate in a MOOC, describing the project as a form of "academic colonialism" — whereby the powerful dominate the less prestigious faculty, weaker schools. Petriglieri put it this way: "It is far more similar to colonialism, that is, disruption brought about by ‘the policy and practice of a power in extending control over weaker people or areas’ and simultaneously increasing its cultural reach and control of resources." Theoretically, MOOCs could work around these organizational challenges. They could, for example, break the course into smaller units of instruction that could then be plugged into courses at other institutions, according to the needs and preferences of local faculty. Similarly, they could remove overt references to the faculty and institutions from which the course originated — "white-label" their work, in effect. But then this would remove what makes MOOCs, well, MOOCs. Affiliation with elite professors and universities (e.g. Michael Sandel at Harvard) was what made MOOCs newsworthy in the first place — as did the decision to package this intellectual property in the form of course. Both decisions support an equivalence between the MOOC and the "real" course offered at the source institution. I seriously doubt that MOOCs would have been discussed in the pages of the New York Times and in such glowing terms, had they come to us from the likes of Pocatello Community College — fair or not. :: The difficulty of creating education tools, programs and services that fit well in higher education has many origins. Most obviously and commonly, the culprit is a lack of knowledge of the unique characteristics of this institutional, but even professionals that work within higher education can get it wrong. I’ve become acutely aware of the importance of understanding organizational fit since joining Acrobatiq. The company is a by-product of a long-term research and development project of Pittsburgh’s Carnegie Mellon University. Unlike most organizations I’ve worked with over the years, the team at Acrobatiq comes from higher ed; they have decades of collective history working in higher education as faculty and administration. Indeed, some continue to work in universities. Higher ed is home turf and we are able to draw on our understanding of how higher education actually operates, what it needs to achieve its objectives, and what truly motivates the professionals that work in these institutions.

  Report: Few Women in Engineering and Computer Science "Currently, women make up just 12% of the engineering workforce and 26% of the computing workforce.  In 1990, women made up 35% of the computing workforce, a drop of 9%.  Women in engineering have increased slightly by 3%, from 9% in 1990.  Yet, women make up more than half of our nation’s population and 57.3% of enrollments in institutions of higher education, according to data from the National Center for Educational Statistics.  In the next several years, women are projected to be well over 60% of the enrollments in colleges and universities."  :: Kevin Carey - The End of College: Q&A with Kevin Carey We did a Q&A with Kevin Carey, author of the recently published, provocative book: The End of College: Creating the Future of Learning and the University of Everywhere. "[Universities) will fight opening up the market to new credentials, for obvious reasons of self-interest, but that’s not a fight that can be won forever. If you’re battling against better information, your days are numbered." :: How do you Design the Library of the Future? I love libraries. Or I think I do; I haven’t been in one in a few years. "Once Upon A Time libraries were the gatekeepers to most of the information students and academics needed. Books had the information and libraries had the books. Then one day the Big Bad Internet came along and made hundreds of millions of books, articles and manuscripts freely available to anyone with access to a computer. The library was no longer the only game in town. Most of today’s students have used computers since a young age and Googling is second nature to them. Why would they go to a library when they could find the answers from the comfort of their own home — or Starbucks?" :: Innovation in Higher Education: The Importance of Organizational Fit " . . . a remarkable number of these efforts will fail to take hold. Some will run out of money. Others simply won’t work. But many — despite the benefits they may offer —  will fail because they don’t "fit". That is, the innovation isn’t aligned with the unique organizational structure, processes, reward systems and culture of our colleges and universities." ::    

Eric Frank, Founder, Acrobatiq GSV-ASU Return on Education Innovation Awards Acrobatiq is a winner of the 2015 Return On Education (ROE) VentureED Innovation Award. Acrobatiq was singled out from among more than 270 presenting companies for its potential to dramatically improve learning outcomes and increase access to education. Sponsored by Arizona State University and GSV Capital, an investment firm, the annual Summit brings together more than 2,400 key stakeholders - educators, investors, policy makers, foundation leaders, business leaders, social and commercial entrepreneurs, and philanthropists - in one place to collaborate and drive change, and serve as a launch pad for new ideas and ventures. The ROE awards honor companies who demonstrate a high return on education by significantly increasing access to education; greatly reducing the cost for learners and/or learning institutions; dramatically improving learner outcomes; providing substantial leverage to learning leaders; and/or making a sustainable and scaled impact. This award follows our being named a Bill and Melinda Gates Foundation Next Generation Courseware Challenge Grant recipient. The Lumina Foundation: Stronger Nation The Lumina Foundation has released an update on US progress toward higher post-secondary completion rates. The foundation said 40 percent of working-age Americans held a two- or four-year degree in 2013, a modest improvement from the previous year’s rate of 39.4 percent. Read the full report. Employer Perspectives on Competency-Based Education A new report from the American Enterprise Institute. Key Points Employers’ overall awareness of competency-based education (CBE) is low, but the small minority of hiring managers already aware of CBE have a favorable view of the model. CBE programs generally employ student-centric marketing efforts,­ as opposed to employer-centric marketing messages, which may help explain the low levels of employer awareness. Employers rooted in traditional hiring approaches express significant misgivings that targeted skill-building approaches (as in CBE) may come at the expense of more general skills. Still, two-thirds of employers think that they could be doing better at identifying students with the skill set required for each job. Institutions offering CBE programs should partner closely with employers to help students attain the general and specific skills they need to succeed in the labor market without breaking the bank. Read the full report. Innovation Series Two instalments so far in our new series on innovation. First, an introduction and then notes on the nature of change in higher education. Innovation in Online Higher Education Change and Innovation in Online Higher Education    

What is adaptive learning? How about predictive learning? Where do learning analytics fit into the big picture? Like other fields, the education technology community is not immune to jargon and catch phrases. Understanding some of the basic terminology used today can help:   Describe current challenges and future goals Ask questions about how specific technologies and approaches affect learning outcomes Connect with the tools and strategies that have the potential to improve the online learning environment Navigate the ever-growing number of technology options on the market Below are just a few of the more commonly-used terms you’ll see referenced here on the Acrobatiq blog, and around the Web, with some specific detail on how we think about the term here at Acrobatiq.  While there’s no single source for definitions, these descriptions offer a good starting point as we think about innovations in online teaching and learning. Adaptive Learning: The application of technological tools that provide students with a customized experience based on their progress and previous accomplishments with the materials, practice activities, and assessments. Students are presented with more, or less, challenging items as they interact with the materials and respond to questions. How we think about adaptive learning: Our approach to adapting the learning experience is conservative by most standards, in part because of our roots in evidence-based learning. Rather than simply depending on a statistical algorithm to force students down different pathways based on what we think they know or don’t know, or down-sampling students to easier questions from those they answered wrong, we take a much more nuanced approach. First, its contextually useful to know that our curriculum development process begins with identifying a Skill Graph (also sometimes referred to as a Knowledge Graph)  that defines a set of learning objectives and skills for what a student should know and be able to do by the end of a learning module. As students work through interactive learning activities, we collect activity data that’s then combined with other statistical parameters to generate a robust learning estimate for each student against each learning outcome. This point is important because we often get questions about how and what we adapt. Having an underlying Skill Graph forms the "what" by providing a clear view into  the relationships between learning objectives and sub skills. For students with low learning estimates, we adapt the learning experience by enabling more practice opportunities on one or more specific skills. It’s really that simple. And it is just that simplicity that makes the approach effective. For students with high learning estimates, we enable less practice so they can confidently move faster through the material. The benefit of this approach is that for faculty in blended or online learning environments, there is no "guessing" about how students progressed through the curriculum. Because of the underlying Skill Graph, it’s easy to see which skills students are mastering, and where additional help is needed. By adapting the learning experience with more practice at the end of each module for only those students who really need it, we can give students exactly the kind of personalized learning experience that helps get them "unstuck." Competency-Based Learning: Focused on mastery of specific knowledge and skills, competency-based models allow students to demonstrate their understanding and abilities via multiple strategies, e.g., exams, portfolios, and projects. This alternative to traditional academic classes is usually self-paced and provides each learner with the opportunity to earn credit or advance within a course or program according to his or her previous experiences and prior knowledge. How we think about competency based learning:  One critical component to effectively delivering CBL is the ability to understand and assesses students’ mastery of key competencies.  Like adaptive learning, understanding the component skills of a competency makes assessment that much easier.  Increasingly, because our curriculums have an underlying Skill Graph, CBL programs can benefit from the resulting data derived from measuring learning at this deep level.  Our ability to include human-graded rubrics in our statistical modeling of student learning estimates enables a wide range of project and portfolio-based learning possibilities. Courseware: Learner materials, activities, and assessments are organized within a system that not only provides instructional content and assessments, but also tracks details about student progress and allows instructors to review their progress, evaluate challenges, and make decisions about possible interventions. How we think about courseware: For many faculty, the notion of using "courseware" is not all that attractive, in large part because most courseware that’s available today can’t really be customized to fit specific course or program goals. At present, our curriculum (or courseware) can be customized only in that modules can be hidden or reorganized. Later this summer, however, we will be releasing a new authoring tool to support more granular levels of customization, including the ability to add locally developed content. For more on the faculty benefits of courseware, see Courseware: The Next Big Thing for Faculty. Learning Analytics: This term is used to describe a wide range of data collection, analysis, and reporting techniques that inform decisions about instructional strategies and interventions. In the context of online education, the software that runs learning analytics can include everything from tracking student performance to identifying complex learning trends and problems, and is often integrated into courseware and learning management systems. How we think about learning analytics: In our context, the analytics that we generate focus on measuring deep learning - or learning happening at the skill level. Formative and summative assessments are embedded in
the courseware and analyzed using a statistical model developed by learning scientists at Carnegie Mellon University. The theory of learning that forms the framework of this computational model takes into account a number of factors, including both observations of learning (number of right/wrong answers, number of hints revealed, number of attempts per question, etc.) in addition to cognitive processes like cognitive load, rate of learning, learning decay, etc. The result is an accurate, real-time assessment of each student’s knowledge state against a defined outcome (like, for example, a learning objective). Learning Optimization: The process of data collection and analysis informs a wide range of decisions about overall course design, including instructional strategy selection and implementation. Continued study of the benefits and challenges of various course features, functions, materials, and interactions allows for continued review and revision with a goal of offering the most effective learning environment for each student. How we think about learning optimization: Again, in the context of Acrobatiq, we optimize learning by using learning analytics we collect from within our courseware as the basis for powerful feedback loops. Data makes possible effective instructional interventions, course corrections, and detailed student feedback based on individual student learning performance.  Student activity data also helps inform course designers about how students are performing on learning activities so that the curriculum can be continuously refined to produce the best learning outcomes. Personalized Learning:  Similar to the term adaptive learning, personalized learning has been broadly used to describe a flexible approach to educational activities that can be tailored to meet the needs of individual students. This term is also used to describe learning environments that allow students to create their own paths to achieving learning outcomes. This can include choosing from among multiple types of interactions, activities, modes of delivery (e.g., online, blended, in person; video, audio, text), and even assignments. How we think about personalized learning: We think about personalizing learning first by understanding the desired outcomes of the learning experience, and secondly, by accurately being able to assess a student’s specific learning estimate against each defined outcome. Only then can we begin to ascertain what to personalize, and for whom and how. Predictive Learning: Through the application of systems that apply mathematical modeling techniques, educators can more readily identify potential challenges a student might face in a course or program, based on his or her characteristics and past performance. Being able to anticipate the challenges allows time for instructors to intervene with guidance and support, before the issue becomes a problem that prevents learning success. How we think about predictive learning: The Acrobatiq predictive learning model can be a powerful tool to help educators and others develop deep insight into student learning performance. By first understanding desired outcomes, and then developing opportunities for students to both learn new skills and demonstrate evidence of learning as they are learning, we can begin to use statistical predicative techniques. The benefit of this approach is that we can get out of front of students that might be at risk - and, conversely, accelerate students that might otherwise be slowed down in a one-size-fits-all learning environment. Follow the Acrobatiq blog for more information about innovations in data driven curriculum design and personalized, adaptive learning.

Acrobatiq’s home field: Pittsburgh, PA. We often hear that "change comes slowly to higher education". There’s nothing inherently wrong with this; change isn’t always good, of course. But as the importance of higher education to the population grows and advances in technology pose ever-more tantalizing opportunities for us to rethink how we do our work, there’s a tremendous interest in understanding the obstacles to innovation in this sector. We can approach this on two levels: we can ask, first, what structural and system-wide obstacles are in place that make changes of any sort difficult, regardless of their intention, tactics, or context. We can also, though, "get into the weeds" and consider how specific innovations or attempts at innovations run up against specific obstacles. The answers are closely related, and are best tackled in tandem. Obstacles and Business Models Lloyd Armstrong, Provost Emeritus at USC, nicely deploys the framework of business models to look at the structural factors inhibiting innovation. His analysis cites: a regulatory (accreditation) scheme that polices institutions, but also serves to protect the current definition of post-secondary education, and by extension, the institutions that adhere to the standard model faithfully; the unique dual role of faculty, as both educators and institutional managers, enables them to challenge changes that might lead to re-skilling or de-skilling of their work and therefore, potentially weakening their labour market value. (Armstrong isn’t suggesting that faculty are unusually self-interested. Indeed, if faculty were to prop up changes that lead to diminishment of their labour market value, they might be the first occupation to ever do it); the difficulty and tendency to not aggressively measure value in higher education that, in turn, has resulted in an over-dependence on "surrogates of quality" that have only a limited impact on the quality of learning (e.g. research productivity of faculty; tuition - the higher the "better").  This can weaken an institution’s commitment to improving the quality of learning; people in successful organizations tend to internalize commonly held notions of what constitutes a great university; interpreting these practices, processes, and ideas as natural and best. Specific Innovations, Specific Obstacles We can take a second step and consider how the design and logic of our institution - it’s business model, essentially - plays out in actual instruction. As Scott Levine noted in response to last week’s post on Innovation & Change in Online Higher Education, we need to move beyond generalities and start analyzing the specific ways that innovation is limited and enabled. How can we use the framework of business models to help us understand precisely how innovation can and can’t work in higher education? Many consider online higher education consider to be an example of business model innovation (see Clayton Christensen). I think that’s the case, but it’s not the whole story or even the most interesting part. While a large number of our colleges and universities took the initiative to make online courses and programs part of their offerings, most did it without making substantial changes to how the institution operates; instructional technology was used to make incremental or sustaining, rather than radical or disruptive innovation. Technology was affixed to the existing, traditional business model of the institution, rather than using it with a new business model - which, according to Christensen and others - that have studied innovation, is the path to dramatic increases in value. The now ubiquitous LMS, for example, was designed so as not to alter the organizational DNA of the institution; it allowed instructors to continue to work largely independently and "own" their courses, as has long been the tradition - despite the oft-repeated contention that this one-person, "cottage model" limits what can be achieved in terms of the course design and development. Nor was the technology used to take greater advantage of the tremendous economies of scale that the Internet enables. Not surprisingly, the quality and cost benefits from instructional technology have been less stellar than first imagined. Unlike other sectors that have applied technology to new business models to reduce costs, improve quality or both, higher education remains largely subject to the ‘iron triangle’, in which any efforts to improve one objective - cost, quality or access - leads to a negative impact on one or both of the others. By understanding innovation in terms of the unique characteristics of higher education may be a useful place to start in order to better navigate around potential obstacles. So, how might specific types of innovations interact with obstacles that are endemic to higher education? Social media can serve as an example. Many educators have sought to leverage the tremendous popularity and functionality of social media for instructional purposes. But the way in which social media is designed, and the particular ways in which people seem to want to use it, are in some quite fundamental respects, out of alignment with how higher education is organized - for example: Social media is well-suited to facilitating open-ended exchanges between people - with no prescribed beginning and end. Users float in and out of conversations; they rarely have specific goals for these interactions, and they enter these spaces only when and to the degree they wish. Higher education, on the other hand, has very clear boundaries (e.g. course duration) and largely predetermined objectives (e.g. a fixed and standard set of assessments).  The content of social media is user-generated and leaderless; the line between "author" and "audience" is seriously blurred. This is one of its’ most compelling characteristics. Higher education, however, is inherently top-down and instructor-directed. The educator is the primary source of knowledge. Efforts to redefine the academic as anything other than the subject-matter expert - such as having them teach other people’s curriculum - are met with intense resistance.   Social media thrives when there are thousands, if not millions, of users within a single, overarching community. The high volume of users provides online communities with enough activity and content to ensure that each user finds what and who they want with sufficient frequency to make participation worthwhile. Twitter and Linked In have well over 300 million active users. Higher education instruction, by design, typically restricts participation to a single class (e.g. 40-100 students per course). Indeed, exclusivity and small class sizes are equated with quality. This is not to suggest that social media can’t be used effectively in higher education. They can, and they are. But the business model of higher education used by the vast majority of institutions will, on average, make their use less effective, more complicated, take longer to achieve, and cost more. Business models are the structures in which we work; they frame the possibilities. A wider discussion about the qualities of the institution’s business model can help us identify where the greatest opportunities for improvement lie.  :: This is the third piece in our "Innovation Series". The second instalment can be found here and the introduction, here.              

Universities on the Brink of a Nervous Breakdown Ignore the misleading headline. Six pundits offer creative ways to improve the quality of learning. Interesting stuff. :: MOOCs keep getting bigger. But do they work?  Jon Marcus suggests that MOOCs need to make a greater commitment to measuring learning outcomes. We couldn’t agree more. Excerpt: "There’s just one hitch: Amid all this rush, no one really knows yet how much people learn in a MOOC. What research does exist shows that the success rate of online education, in general, is poor. And one high-profile experiment with MOOC-style teaching in particular has ended in disappointment." :: California’s multi-million dollar online education flop is another blow for MOOCs I never quite understood the assumptions behind this initiative. A review of the experiences of other institutions might have been helpful. "We spent a lot of money and got extremely little in return," said Jose Wudka, a physics professor at UC-Riverside who previously chaired the Systemwide Committee on Educational Policy of the Academic Senate, which represents faculty in the UC System." "The project, which cost $7 million to set up at a time when the state was cutting higher-education funding, aspired to let students take courses across campuses. A UCLA student, for example, would be able to take a UC-Irvine class online." :: Ohio State faculty reassert claim to scholarly research ownership  Intellectual property was always a lawyer’s dream - lots of grey areas. But with the expansion of formats, devices, and sharing models, it’s become a nightmare. Excerpt: "Ohio State University is assuring its professors that their scholarly works — books, articles, software and other works that can be copyrighted — belong to them." "That’s the arrangement that had been in place for years. But a policy proposed last month stoked fears that the university was trying to take control of those works. Some professors threatened to quit if it was approved." :: Tyton report highlights dearth of tech solutions for adult ed programs Another interesting report from Tyton Partners. (Something in the water in Boston.): adult learners and learning technology. Excerpt: "But a major segment of the student population has largely been left out of the innovation surge — adult students lacking basic math and literacy skills. According to a new report by education consulting firm Tyton Partners, there is demand for instructional technologies in this sector but very little supply." :: LinkedIn: Moving Into Online Education We’d need to be living under a rock for the past week to miss this news item: Linked In purchases Lynda.com for 1.5 billion USD. If you’ve attended an education technology related conference in the last year you’ve probably noticed that Lynda.com is trying to sell its growing line-up of online, life-long learning courses to colleges and universities. This deal with Linked In is interesting on a number of levels, not the least of which is the connection between the growth of public portfolio’s (like Linked In) and certification of learning.

Helping institutions improve course completions, particularly in high enrolling general education gateway courses, is at the core of what we do. Our robust, online learning environments, grounded in the science of how people learn, use real-time student activity data to generate fine-grained predictive estimates of student learning performance against outcomes. The benefit is threefold; faculty get deeper, and more accurate and timely insight into student learning without having to generate and grade numerous, periodic summative assessments; students get a richer, more active and engaging learning experience that helps them learn more effectively, often in less time, with better knowledge retention and transfer rates (measured by pre and post testing); and course developers get unprecedented insight into curriculum effectiveness by ensuring the tight alignment between content, activities and assessments and desired learning outcomes. Our curriculum development and continuous course improvement process is illustrated below: Until now, an Acrobatiq team of learning engineers, subject matter experts, data scientists, and technical professionals facilitated this process. And, once the curriculum was developed and "tuned" to the statistical model generating the predictive learning estimates, making changes to the curriculum risked negatively impacting the model and resulting learning analytics. Thus, faculty empowered with teaching these courses had to take the curriculum "as is" with only limited and periodic ability to customize or make changes. I share this as preface to our exciting road map news: we’re very close to beta on our new authoring environment for adaptive curriculum. In many ways, we’re again breaking new ground with this capability. Nothing exactly like this tool exists in the marketplace, and the demand for it is high, in large part because institutional leaders and faculty are looking for cost effective and high ROI strategies to improve learning outcomes. Developing adaptive, personalized learning solutions that generate meaningful data about deep learning is one strategy showing great promise. So let me highlight some of our key goals in developing the new authoring environment, illustrated with screen captures pulled from the dev environment. Development Goals: Simple and intuitive design: First and foremost, (and not unlike most new technology applications), our goal is to develop an authoring application that is simple to use, with intuitive navigation. Imbedded learning science: Developing highly effective online learning experiences proven to help students learn is made easier when you have the benefit of learning science to guide curriculum design decisions. Imbedded in our forthcoming authoring environment is the evidence-based design methodology from CMU’s Open Learning Initiative including tips and suggestions that helps faculty, curriculum developers and instructional designers use learning science research to create exemplary online learning experiences. Integration of dynamic media: Adding engaging and dynamic media often means opening custom applications like Captiva, PowerPoint or others. Now, it’s a click away using pre formatted templates. Just select the kind of dynamic media activity you want to add, customize the content, and publish it to your page. Skill Graph Development: Having clear, measurable outcomes in any course is important, but particularly in online courses, as it helps guide and organize student learning. In Acrobatiq courseware, the Skill Graph also forms the basis for how what’s measured gets measured. The underling Skills Graph (or Knowledge Graph as it is sometimes called), connects learning objectives and skills. Every learning objective is tied to component skills, and each component skill is then tied to practice. As students complete the practice, the Acrobatiq inference engine analyzes the activity data and produces a learning estimate for each LO. The authoring environment will help courseware authors develop a Skills Graph, tied to the inference engine so good student learning estimates against outcomes can be effectively measured. Adding activities and assessments: Developing good practice questions often takes practice. Embedded in the authoring environment is multiple activity type templates that save time by essentially functioning like mini-forms. Simply select the activity type and enter content in the fields.   Managing media: Engaging online courses often include a range of static and dynamic images, videos, and other types of media. Included in the authoring tool is a robust Media Manager that helps curriculum developers manage and organize all their media elements.\ The new authoring environment is currently in private beta with selected partners.  In the coming months, I’ll share more updates and screen captures as development progresses.  We’re tremendously excited about this initiative and welcome feedback and input.  If you’re interested in learning more about the authoring tools, or would like a demo, please contact us. 

New York City, Aerial View Fooled by Experience Excerpt: "We rely on the weight of experience to make judgments and decisions. We interpret the past—what we’ve seen and what we’ve been told—to chart a course for the future, secure in the wisdom of our insights. After all, didn’t our ability to make sense of what we’ve been through get us where we are now? It’s reasonable that we go back to the same well to make new decisions.
It could also be a mistake. 
Experience seems like a reliable guide, yet sometimes it fools us instead of making us wiser." Read the full article.  Think Tuition Is Rising Fast? Try Room And Board Excerpt: "Valerie Inniss took out $11,500 in student loans this year to pay for the University of Massachusetts, Amherst. None of it was for tuition. The 21-year-old is on a four-year, full-tuition scholarship, won on the strength of her high school test scores. And she qualifies for the maximum federal Pell Grant — $5,730 — for low-income students. But that and a campus job were still not enough to cover all her other costs and fees, from health care to books. The biggest expense? Nearly $11,000 for room and board, a charge that’s risen 15 percent since she started college four years ago." Read the full article.  What works and why? Student Perceptions of ‘Useful’ Digital Technology in University Teaching & Learning This research paper looks at eleven different "benefits" of instructional technology as defined by students, such as "reviewing, replaying and revising", and "organizing and managing the logistics of studying". Interesting. By Michael Henderson, Neil Selwyn and Rachel Aston. Read the full article.  Innovation in Online Higher Education: Navigating Obstacles Excerpt: "We can approach obstacles to innovation on two levels: we can ask, first, what structural and system-wide obstacles are in place that make changes of any sort difficult, regardless of their intention, tactics, or context. We can also, though, "get into the weeds" and consider how specific innovations or attempts at innovations run up against specific obstacles. The answers are closely related, and are best tackled in tandem." Read the full article. Funding of Higher Education (Report, Moody’s) Excerpt: "Over the past several decades, the growth in state funding for discretionary spending categories has declined at an alarming rate. Mandatory spending programs, specifically Medicaid, are requiring more and more state funds, which in the zero-sum world of state spending, has left fewer and fewer dollars for other programs. Medicaid spending, for example, was less than 10 percent of state sourced spending 30 years ago, but today accounts for nearly 16 percent. Taking all funding sources into account, Medicaid has grown to more than a quarter of total state spending. Higher education funding has borne the brunt of much of this crowding out, falling from around 14 percent of state sourced spending in the late 1980s to just over 12 percent today. Our baseline forecasts show that trend continuing throughout the next decade and beyond." Read the full article.