06
Sep

Adaptive Learning to Personalized Learning

Written by Blog Editor. Posted in Academic News

Computer-driven adaptive learning has been around for decades; in its most basic form, it is simply the computer program branching the learning path based upon responses the student makes. Some learners may be best served by materials delivered in a different format — for example, case studies rather than theoretical study. Others may need refresher learning for underpinning skills, principles and theories upon which more advanced learning is built.

Computer-assisted instruction (CAI) has enabled this kind of learning program for half a century and more. I recall working with others in the 1970s as we programmed simple lessons that would quiz students and branch their learning path based on right answers as well as wrong answers. Simple coding in the PLATO TUTOR language would allow programmers to branch to different review or new materials based upon which answer was selected.

More sophisticated adaptive-learning programs that have been developed recently aggregate much more data from the learner to better adapt the learning path. These data can include stored prior learning experiences and performances; self-expressed student preferences in modes of delivery; analytical prediction of likelihood of success for the individual student through different modes of delivery; and much more.

For the past half dozen years, Khan Academy has developed and enhanced their flow-of-learning model. These and other like programs can more finely and accurately identify and address gaps in learning. Coupled with effective support modules, they can fill in the gaps on an individualized basis. “Particularly in high-enrollment classes, adaptive learning can provide tailored support and guidance to all students,” says this primer from Educause. Adaptive learning has effectively been used by many publishers for their online homework and supplementary materials.

Adaptive learning, while it has provided an important step forward in helping to assure that all learners get the material that they need to achieve learning outcomes, has fallen short in cultivating full engagement with the individual student. That’s where personalized learning takes the next step. It is defined by the Glossary for Education Reform as:

The term personalized learning, or personalization, refers to a diverse variety of educational programs, learning experiences, instructional approaches, and academic-support strategies that are intended to address the distinct learning needs, interests, aspirations, or cultural backgrounds of individual students. Personalized learning is generally seen as an alternative to so-called “one-size-fits-all” approaches to schooling in which teachers may, for example, provide all students in a given course with the same type of instruction, the same assignments, and the same assessments with little variation or modification from student to student.

This takes student-centered learning to the next level. It goes beyond simply responding to requests from students. Instead, students become part of the process of defining the learning outcomes, pedagogy and practices of the learning experience. Until recently, it has not seemed feasible to meet student needs in this way. To customize learning for each of 30 or 40 students in a class, monitor their individual progress and provide meaningful feedback just is too time-consuming.

Now, machine learning can synthesize the huge volume of data needed to more fully deliver student-centered learning. It can assemble the background, take input from the individual learner regarding their self-determined needs and expectations, identify learning deficits and needs, and produce and present the learning path to best accomplish those goals.

In this case, the role of the faculty member shifts from directly delivering materials and grading based on a single syllabus to advising, assisting and assessing personalized learning that meets the needs of both the individual and the prescribed outcomes of the program. Certainly, this is a change for the faculty member. It is no longer administering a one-size-fits-all class. Instead it is a much more personal, individualized mentoring of each of the students while AI assembles the learning stack for each student.

Have you incorporated any of the adaptive-learning tools in your classes?

Are you preparing for the next step of personalized learning?

Are you preparing your faculty colleagues for this process?

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Inside Higher Ed | Blog U

13
Aug

Privatization and Kazakhstan’s Emerging Higher Education System

Written by Blog Editor. Posted in Academic News

Since the introduction of neoliberal reforms, government spending on higher education has decreased dramatically.

Inside Higher Ed | Blog U

13
Jul

Guest Post: Reclaiming Assessment’s Promise

Written by Blog Editor. Posted in Academic News

New guidance from the Department of Education could help. A guest post from David Eubanks, Vice President of Insitutional Effectiveness at Furman University.

Inside Higher Ed | Blog U

27
Jun

Considering the alternatives

Written by Blog Editor. Posted in Academic News

Considering the plethora of lower-cost (in both dollars and time) alternatives to the traditional degree, it is no surprise that enrollment at the bachelor’s level in higher ed has dropped for the past half-dozen years. Sure, a robust economy has contributed to the decline, but applications to the University of California system and other major universities, as well as most midsized and smaller colleges, are down for 2019.

The situation is not getting better. Students are weighing alternatives in terms of cost, time to completion and employability. And the alternatives are proliferating. One website, Alternatives to College, matches prospective students to 200 different boot camps, apprenticeships, code academies, income share, online short courses and more. Many of these are agile small start-ups that can release new programs just in time to meet employer needs and student demands.

Then, of course, there are the giant MOOC providers offering courses, certificates and degrees. Coursera recently revealed that it is valued at well more than a billion dollars. And, with nearly 40 million students, the company’s momentum is massive. Udacity and edX are also thriving while reaching tens of millions of learners.

FutureLearn, a subsidiary of the UK Open University, is serving millions of learners in 18 countries with its 200 courses from 120 universities. And, China’s XuetangX now reaches 16 million learners and offers 1,900 classes from universities in China as well as Stanford, Berkeley and others. All of these alternatives provide credentials that are certified and badged, in many cases with learning outcomes carefully designed to meet employer needs.

Some very large employers are reassessing the need for the baccalaureate. Apple CEO Tim Cook says nearly half of Apple’s U.S. employment last year was made up of non-degree holders. He says most colleges don’t build the skills business leaders need most, such as coding. And, Siemens USA CEO Barbara Humpton says in the past the degree requirement merely helped hiring managers to identify a smaller qualified candidate group.

With the average new college graduate earning about $ 50,000, it is noteworthy that there are many job categories where non-degree holders start at more than $ 70,000 with no huge college loans to pay back, saving both time and money.

Institutions are responding in a variety of ways. The Brookings Institution has identified some of the key causes and responses:

Around the world, tuition at universities is rising at a much faster rate than inflation and challenging students’ return on investment. Reduced government funding and higher operating costs are driving the need for change at universities. The mismatch in employer needs and employee skills is leaving over seven million jobs unfilled in the U.S. … There will undoubtedly be on-going opportunities for new approaches and actors to innovate in higher education as the sector continues to face high costs, decreasing returns on investment, and skills mis-matches.

So, how do we make a value case to prospective students and employers? We can offer our own short-courses and professional education options. Certainly, the degree is far more than vocational training. The general education portion of our degrees cultivates both creative and critical thinking. Diverse communication skills — one of the top-rated areas desired by employers — is another area in which we can excel. These are just a few of the areas in which baccalaureate holders have an edge over their less-educated competitors. We must document these skills.

One group of 13 universities in the Virginia and D.C. area is doing just that. The institutions are collaborating with businesses to create a digital credential that certifies learning in a number of digital tech literacy courses. “It is neither a major, nor a minor, nor a formal certificate. It is, rather, a recognition that students have taken a short sequence of courses (five at GMU) that cover knowledge and skills in high demand.”

Considering the alternatives, we can no longer depend upon just our “good name” and reputation; prospective students and employers expect explicit proof that we are meeting their needs. To fall short of that expectation will feed continued decline in enrollments. What steps are you taking to demonstrate and certify to employers that your graduates have the skills and abilities that they need?

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19
Jun

Emerging Roles of AI in Education

Written by Blog Editor. Posted in Academic News

Don’t get me wrong, human beings are now and will be in the future at the core of our field — administering education, teaching and learning. But if we are the bus designers, bus drivers and bus riders, artificial intelligence is the engine of the vehicle that we are using and will be using more often in the education field. It will design, drive and assess our efforts in teaching and learning.

Nothing is infallible, especially emerging technology. So there will be mistakes, failures and glitches along the way. But even today, AI is improving our field in dozens of ways. In language learning, adaptive learning, math and technical field learning, and dozens of other areas, AI is engaged in making our teaching and learning better than ever before.

There is no doubt that AI is changing the way we conduct recruitment, admissions and retention of students. Over all, Wiley Education Services says that a college’s bottom line and reputational value will improve through the use of artificial intelligence tools to enhance the marketing, assessment of applicants and monitoring success of students.

As we move forward, the algorithms will become ever more sophisticated, predictive and autonomous. As next steps, the RAND Corporation reports, “AI has so far found a perch in three ‘core challenges’ of teaching: intelligent tutoring systems, automated essay scoring and early warning systems to identify struggling students who may be at risk of not graduating.”

Artificial intelligence is becoming so entrenched in societies around the world that there is a worldwide competition shaping up to see which countries, societies and cultures will control the future of commerce, education, entertainment and more. We are challenged to take the lead in providing the best educational opportunities to build a work force of AI developers. The Brookings Institution reports,

Control over the research and development of AI will become increasingly vital, and the winners of this upcoming AI-defined era in human history will be the countries and companies that can create the most powerful algorithms, assemble the most talent, collect the most data and marshal the most computing power. This is the next great technology race of our generation and the stakes are high, particularly for the United States. If American society is to embrace the full range of social and political changes that these technologies will introduce, then it is the education and training we provide our youth and workers that will fuel the engines of future AI, and therefore geopolitical success.

Forbes’s Bernard Marr suggests that personalized learning, universal access and smart tutoring are among the leading developments in education that we will see implemented in the near future. These will lead the way in an ever-expanding and more sophisticated suite of AI-driven tools to enhance the learning experience.

TeachThought goes even further to point to AI tools for education that may well change the role of teachers, give students the freedom to fail and try again, and change where students learn, who teaches them and how they acquire skills.

As we retool with AI algorithms, making the right choices and implementing them as soon as they are reliable and ready will be key to keeping a competitive advantage. That will be art and science of effective use of this most powerful technology — applying it to the right tasks, assessing effectiveness and continuing the cycle of improvement.

All across the spectrum of higher education, we will see artificial intelligence emerge. From educating the work force to applying the technology to advancing the efficiency and quality of our core business of recruiting, teaching and certifying learning, AI will be our new partner in education. Prepare for this partnership by closely following the field and including AI in discussions and planning for the future of your students, your departments and your university.

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19
May

What’s So Special About That Purple Cow, Anyway?

Written by Blog Editor. Posted in Academic News

At this moment in higher education history, when achieving revenue goals has never been more consequential to more institutions, is being perceived as different than your primary competitors all it takes to win?

Inside Higher Ed | Blog U

11
May

Internationalization of Higher Education in the New Political Climate

Written by Blog Editor. Posted in Academic News

While funding remains the major obstacle to progress, funding increased for all internationalization activities during the last three years at a majority of institutions worldwide.

Inside Higher Ed | Blog U

25
Apr

Why We Disagree on OPMs

Written by Blog Editor. Posted in Academic News

The two of us disagree on the online program management industry.

Eddie is OPM critical. Josh is OPM optimistic.

We think our different perspectives on OPMs are a good thing.

The reasons for Eddie’s criticism of OPMs are many, but they are primarily rooted in his belief that universities should develop internal capacities to support their core educational missions. These capacities include instructional design, project management, media production, data and analytics, platform management, and learner support.

These are not just necessary capacities for online courses but for all courses at a school.

Once these core educational capacities are developed, they can be deployed in service of building and running online programs as well as hybrid and face-to-face courses. These capabilities are necessary for the future of higher education.

There are other reasons for developing and managing online programs internally as well. It’s far less expensive, a school doesn’t have to commit to a long-term revenue-sharing contract and courses developed by on-the-ground faculty and staff at the college will more closely align with the intellectual rigor and values of the school.

For Eddie, the ability to create online programs is a powerful reason to be cautious about OPM partnerships.

Josh, alternatively, is OPM optimistic. While he agrees with Eddie that core educational capabilities such as instructional design and project management and analytics and media should ideally reside within the university, he thinks that OPM partnerships can be a catalyst for developing those institutional capacities.

From Josh’s perspective, it is a mistake to narrow our conception of what OPMs are — and what university/OPM partnerships can be — down to a narrow set of arrangements. Instead, he sees room for nonprofit schools and for-profit companies to collaborate in creating shared value.

There may instances where the fixed and opportunity costs for a school to develop a new online program are prohibitively high. A partnership with an OPM provider, if structured around an institution’s long-term educational mission rather than a fixation on short-term revenues, can (if done well) create opportunities where none had existed.

Just as Josh is happy to partner with for-profit companies for many of the core things universities already do (e.g., every technology platform that a modern university depends on to run), he is willing to investigate if partnering with an OPM makes sense in a school’s efforts to build and run new online education programs.

This is where we disagree. Where we agree is a little simpler. We both acknowledge that there are capacities that may well be outside the scope of individual colleges to develop at scale. Marketing, for example, is often cited as one of OPMs great strengths. Rapid scaling is another.

Who is right? How do we know?

We have both have strong opinions. We think there is an opportunity to do more, though, to bring a scholarly lens to the question of the value — or harm — of the growth of the online program management industry in higher education.

How we would even structure this research on the efficacy of OPMs is an interesting question. We lack almost all the necessary ingredients for critical, objective and unbiased scholarship. Not only are the data not available, but we don’t even have a good idea of what data we would need. Student outcome data? Institutional financial data? Can we collect data from similar institutions who have made different OPM choices in their online program evolution — therefore providing something of a natural experiment?

What sort of time frames would be necessary in order to draw valid conclusions? How would a research deal with the heterogeneity in OPM partnerships? What are the theoretical frameworks that need to be applied — or developed — in order to make sense of the OPM data? What academic disciplines are the natural home for this scholarship? Or do we need to develop a new cross-disciplinary field to adequately research the OPM phenomenon?

These are all nontrivial questions that any scholar of OPMs will need to contend with. And our questions just barely scratch the surface of the challenges of studying how schools are moving to launch new online programs.

Where do you see the study of how schools go online occurring?

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17
Apr

Learning Innovation, Scholarship and the Carey Article

Written by Blog Editor. Posted in Academic News

Kevin Carey’s April 1 article, “The Creeping Capitalist Takeover of Higher Education,” in The Huffington Post ignited an intense online debate.

Responses to the piece appeared on Inside Higher Ed (here, here, here, here, here and here), in blog posts (here, here, here, here and here) and in countless tweets.

This article is not another contribution to the debate on OPMs or Carey’s piece, though there is likely much more to say and explore. Nor is it an assault or defense of Carey.

We both tend to agree with much of his criticism of OPMs and the inequities that profit motives are creating in higher education, just as we agree that online education itself has become an underexamined straw man for Carey’s argument.

Instead, we wonder what it means to have this conversation — the conversation about institutional choices and online education that Carey catalyzed — on social media. Is social media a good platform for engaging in meaningful knowledge creation and exchange about higher education?

We wonder if discussions mediated on social media platforms can succeed in surfacing important ideas and debates.

In this specific case, one concern we have is that all the commenting and tweeting will serve to harden — rather than advance — whatever biases and beliefs that already exist. Further, we wonder if the format of the discussion — again mediated through online articles and blog posts and comments and tweets — will make it difficult for anyone who does not have strong beliefs on the topic at hand to form evidence-based views.

We are not arguing that debates on topics about higher education should not take place on social media. After all, we are ourselves active contributors to those online conversations. Rather, we’re arguing for complementing these social media debates with scholarship. We see value in discussions mediated by social media, but we also recognize the limitations of these platforms. Our goal is to lay an intellectual foundation for an academic inquiry into areas such as the growth of the online program management industry.

How might a scholarly and academic investigation on a topic such as OPMs differ from a conversation mediated by social media? We propose in the following three ways: a) hypothesis driven, b) theoretically grounded and c) evidence informed.

Hypothesis Driven

Scholarship, at least in the sciences and social sciences, is hypothesis driven, in that conclusions can never be definitively reached, only supported or discredited by the available evidence. If an idea cannot be disproved, it is not a candidate for scholarly research in these fields.

This does not mean that the researcher comes into the work as a neutral and dispassionate actor. Scholars, like everyone else, have their biases and beliefs.

What this does mean is that a researcher will energetically search for evidence in their search for knowledge regardless of whether it proves or disproves the original hypothesis. If the evidence ends up countering the initial hypothesis, then the researcher must faithfully report and actively grapple with that result.

What might be different about Carey’s piece and the responses if they were to start from a hypothesis rather than a perspective?

Theoretically Grounded

Theoretical frameworks are models of how the world works that help researchers in the sciences and social sciences develop hypotheses and interpret results. Theoretical frameworks assist in the development of testable hypotheses. In the humanities, theories serve often serve as structural models under which or in relationship to an analysis might be developed. The different approaches to theory between the sciences, social sciences and humanities is worth exploring at some point, as these differences may be illustrative of how we adopt certain perspectives.

Each of these areas, however, provides a framework in which we can situate individual events and discrete analysis. Without a conceptual framework, developments such as the rise of the OPM industry can seem disconnected from other changes occurring within higher education and across the broader economy and society.

One common theoretical lens through which higher education is often viewed today is Christensen’s disruptive innovation theory. Unfortunately, it’s rarely the case that disruption theory serves as a framework in which to test hypotheses. Instead, it more often than not serves as a talking point to help reify one’s general assumptions and opinions.

What is needed is the development or applications of theoretical frameworks that are derived from, or at least sensitive to the context of, higher education’s history and structures. We need to develop our own theories to understand higher education change, rather than retrofit existing frameworks (developed for different contexts) to make sense of the future of our colleges and universities.

Evidence Informed

The third reason that we argue that the debate about Carey’s piece playing out across social media is most likely to reinforce and harden current beliefs, rather than move the discussion forward, is the existence of evidence and data. The arguments made for and against the value of online education to students and schools, on both sides of the debate, have been mainly divorced from empirical evidence. When data are presented, they are shared to support a particular assertion.

There are a lot of data available. Social media tends not to be a great place to share these data.

Social media tends to serve multiple functions in today’s society. In our context, it’s just as (or maybe more) likely to serve as a marketing tool as it is a place for critical dialogue. Because of this complex function, it is not a level playing field for the exchange of data and evidence. Social media is too many things to too many people, and as such may not serve well as a place for disinterested scholarship.

We need better mechanisms to collect, de-identify and then analyze the data related to how colleges and universities are, among other things, moving online. These decisions involve dozens of competing factors, not the least of which include how students are learning and the affordances and constraints of an institution’s history and traditions. The objective of studying these data should be to create knowledge that can be shared widely. The conclusions about the impact the institutions make should be grounded in data, not in the preconceived biases of those who have a stake in the outcome of the research.

The question is who will do this research?

Watching the debate about Carey’s provocative story unfold is one of the reasons that we’ve been calling for a new cross-disciplinary field of learning innovation.

This field would bring together the hands-on knowledge of online program creation with the perspectives, values and methods of scholarly research.

How might we begin to evolve the social media debate on the value of OPMs to a research question worthy of serious, sustained and peer-reviewed scholarship?

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