Virtual Roundtable

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9 Ed Tech Trends To Watch in 2015

• 01/22/15

The New Year is a time for both reflection and resolution. We've channeled a little bit of both with our annual look at the hottest tech trends in higher education: In the following virtual roundtable discussion, five IT leaders from around the country share their thoughts on everything from analytics and personalized learning to badges and gamification.

What trends would you add to the list? E-mail us!

1) Learning Spaces

Kyle Bowen: Traditional learning spaces are a classic example of efficiency through replication — as if there were a classroom machine that has been punching out the same room over and over for decades. A number of concepts have emerged for the design of new learning spaces: those that enable a specific form of teaching; those that enable teachers to teach how they want; and those that enable students to learn how they want. Technology is now a key component of this learning environment, enabling teaching and learning in ways not previously possible — moving beyond just a projector in the classroom, for instance, turning the projector into a community canvas that is shared by the entire room. This is an excellent time to explore a new generation of learning spaces that are as creative as the faculty who teach in them. At Penn State, we are increasing focus on research and experimentation around classroom design, providing a studio for faculty to experiment and a platform for research that will make it possible to scale new approaches without killing the magic that made them possible in the first place.

Josh Baron: In the last decade or more, there has been a tremendous amount of research on new learning space designs and examination of how they can transform the teaching and learning process. Although I think this work will continue into the future, I see a growing need for and interest in applying some of these design concepts to the online spaces that we in education are deploying on an increasingly regular basis. At Marist, we are actively exploring how we can use new open academic collaboration platforms to create, in an online environment, the type of ad hoc "academic commons" spaces that are now so prevalent on physical campuses. We have come to recognize that environments such as the learning management system, while great at supporting structured teaching and learning activities, are not ideal when supporting more informal forms of academic collaboration. So in parallel with the LMS, we are deploying the Open Academic Environment academic collaboration platform, which is designed to give control back to the user — similar to the way flexible learning spaces on the ground are designed.

Pam McQuesten: The continuing conversation about learning spaces, while introducing new arrangements of people, technology and furnishings, does little to provide a deeper theoretical framework for why learning spaces should matter. In his book Cognition in the Wild, anthropologist Ed Hutchins describes distributed cognition as a process that involves not only the brain, but also the non-neural body in an environment that includes objects, other people, tool, texts, and physical and social structures. From this perspective, incorporating new spatial arrangements and technologies means creating an environment that is actually part of the cognitive process. If we begin to think of our campus learning spaces within a frame of cognitive design concepts, we may find that they become more like advanced navigation systems customized for the task, choreographed as a system of people, technologies, tools and texts.

2) Badges

Baron: I think this trend may be at a pivotal moment: We are starting to see some examples of badges replacing or at least supplementing other forms for formal credentialing. A good example of this is the partnership between LinkedIn and some of the major MOOC providers, which allows those who complete MOOCs successfully to have a badge automatically placed on their LinkedIn profile. Unlike other content that a user adds to his profile on his own, this type of badge can potentially be seen as more valid as it is independently added based on the integration of the MOOC platform and LinkedIn. Of course, such validation is far from a formal credential — but it is one more step in that direction.

Bowen: Recent trends in higher education have shown a pattern of reshaping the form and method of instruction. Learning opportunities such as entrepreneurship, activism and undergraduate research have become new ways to extend the classroom. And as learning opportunities grow more diverse, it is increasingly important to recognize learning in all of its forms. Grades, credit and transcripts have historically been used as blunt instruments to describe a student's education. Microcredentials, such as digital badges, provide a new way to visually represent learning, achievements, skills, interests or competencies that are linked to evidence in a way that creates a shareable portfolio of work. Ultimately, these types of customized credentials will help students differentiate themselves with postmodern learning transcripts.

McQuesten: I remain intrigued by badges, but probably not in the way that has led to so many conference presentations and blog posts. Sometimes I think badges will simply become another way in which we attempt to make externally visible what someone knows or is capable of doing. Perhaps this increasing pressure for "proof" at a micro level emerges from a more complex society in which the representative meaning of a diploma or degree or grade can no longer be seen as a common constant. As such, badges are well suited to respond to the type of automated keyword checking that is now the norm for so many HR systems. And I often wonder how the wider world, beyond the technology, gaming and education passionistas, views the usefulness of badges for a given situation. Will we see badges as part of profiles on dating and relationship sites at some point?

3) Gamification

McQuesten: Gamification is a design philosophy that identifies the user as a player in creating a structured and rule-based experience that builds upon a person's natural instincts for mastery, self-expression, socializing and competition. In most cases, this results in a gamelike experience tied to marketing, promotion and training. The effect of gamification can be seen as various efforts across the Web promise rewards and badges for persistence and participation.

There has been an increased interest on the part of some faculty in using the design principles of gamification to provide new experiential learning situations for students. In some cases, these are actual games, while others incorporate various reward mechanisms as part of the overall pedagogy in a course. This year, Southwestern will be experimenting with gamification and badges in learning opportunities that are not part of the regular curriculum. We are developing activities and modules focused on the development of research questions along with the information resources and technology tools that students use to produce scholarly work. This initiative not only enables students to develop stronger academic research skills, but also serves as a platform for experimentation with new types of learning tasks and pedagogy.

Ed Chapel: The demographics make it clear that gaming (and thus gamification strategies) resonate with the undergraduate and, I dare say, graduate populations served by higher education. It provides a new model for motivating students and reinforcing key learning objectives by means of instructional design strategies that can be learning-outcomes oriented.
In addition, the incremental rewards and peer-based comparisons are a compelling alternative to traditional grading schemes.

4) Analytics

Bob Bramucci: "Analytics" is a catchall term that includes reporting; data warehousing; visualization; dashboarding; learning analytics; adaptive instruction; machine-learning-based early alert, recommendation and grading systems; as well as predictive analytics. There's a "gold rush" in many of these areas. Here are a few predictions: Data warehousing will still be necessary but no longer sufficient; reporting will increasingly move from tabular to visual, adding dashboards that link the present to the past; cloud-based big data platforms will become more accessible, with tools that combine structured with unstructured data, munge together disparate datasets, clean data and perform predictive modeling while offering upsells to preconfigured third-party data sources; analytics will be increasingly consumerized, delivered directly to students; there will be hunts for "dark data" to fuel efficiencies and spur innovation; and there will be battles over data ownership, ethics and standards. The bottleneck remains the scarcity of data scientists.

Chapel: Universities possess a treasure trove of information ("big data," if we must use this term) about our students that is rarely exploited in a holistic manner to support the overarching goal of student success. The many transactional systems touched by a typical student, including LMSes, ERP (especially student information systems), parking systems, access cards, dining solutions — as well as the limitless unstructured data events through social media channels — all accumulate to an information resource that should allow for compelling predictive models for student success. Solutions like Course Signals begin to do this type of thing, but the analytical tools for examining structured and unstructured data that have been used to predict consumer behaviors are just now being considered to help us refine our strategies for achieving our core educational mission.

Baron: I view analytics as being at a similar stage to where learning management systems were in the late 1990s: There is a lot of interest at the moment because of the potential it holds to transform education, but it remains an emerging technology that will need to mature over time before we fully understand its implications. One key to future success for analytics, and in particular learning analytics, will be the degree to which "openness" becomes a priority. Why? Well, in order to fully leverage the power of analytics (and "big data"), institutions will need access to all data produced through the education process — which today is all too often "locked up" in proprietary cloud-based systems. In addition, most of the predictive models in use today are also "closed," thereby preventing institutions from understanding how the predictions are being made or customizing these models to meet local needs.

5) 3D Printing

Bowen: Few emerging trends better embody science fiction writer Arthur C. Clarke's notion of technology that is indistinguishable from magic. While not a new technology, 3D printing has come of age. For the first time since the invention of paper printers, even novice users are able to transition digital information into the physical world. Beyond the advancement in technology, 3D printing is the technology of student innovation, engaging students in the act of invention — for themselves, to start a business, to support a cause, to pursue research endeavors. New management tools are bringing this technology to scale as institutions seek to create 3D printing labs in the same way that we create computer labs today.

Baron: This is clearly an important trend that has implications far beyond education. My main hope, though, is that we move beyond using 3D printing for the obvious — allowing learners to bring their creative ideas into reality — and seek out more transformative applications that create completely new learning experiences. For example, the use of CAD allows students to share and collaborate on designs, building on top of each other's work, while then being able to create the co-designed object in the real world. Such an approach would provide art and industrial design students with new ways to collaborate on a global scale.

6) Openness

Baron: From open access journals to open content to open source software, it is hard to overestimate the significance of the overall "openness" trend in education over the last decade. Today, many of these concepts are moving from "trendy" to "mainstream," but at the same time we are starting to see new related trends emerge as the technology landscape shifts and changes. For example, the introduction of cloud-based services has driven new models and challenges for traditional open source software development, and analytics has created new opportunities for open content. Those watching this space might find it valuable to consider how other trends being discussed here will impact on or be influenced by concepts of openness.

McQuesten: Open means so many things in education. The Open University in the United Kingdom is notable for its open admissions policy, growing over the past 45 years to an enrollment of 250,000. Sharing code, which gave rise to open source software, grew enormously in the early days of the Internet, with many of the participants located at universities with early connections to that growing network. Open access has emerged as an alternative venue for scholarly publishing, driven by the twin objectives of increasing access to information and addressing the continuing rise in journal prices. Open educational resources gained widespread attention with the MIT OpenCourseWare project and have grown through the ability to leverage the Web as a global discovery and delivery platform. And of course, massive open online courses have provided widespread access to education utilizing 21st-century technologies to extend their reach.

Whether open becomes the major focus in any of these areas in any part of education over the next year is, well, an open question. At this point, the goal of access is often positioned in opposition to quality — a hypothesis in search of serious research. Viewing open as a strategy for ongoing significant cost savings would seem to have a limited future across most institutions. This year, open may serve best as a conversation starter that touches upon the entire process of scholarly knowledge creation and dissemination. Engaging faculty and students in discussions about intellectual property, copyright and the entire emerging digital academic information ecosystem will help bring better-informed voices to the many social and political debates emerging around issues of access, quality and sharing.

7) Digital

Bramucci: Here I'll use Gartner's distinction between digitization (converting analog processes to digital so they produce digital data streams that can be leveraged) versus digitalization, which creates value from digital assets. The first yields new data sources from which value may be derived to improve existing business models, while the second enables second- and third-order effects that can lead to new business models. For example, you can convert (digitize) a book from analog to digital, but digitalizing might mean creating a multimedia version of the book that spawns a robust online community.

McQuesten: The impact of digital (and networked) is beginning to be felt now in IT and libraries and will over the next few years spread to the rest of the functions of higher education. In the non-networked and non-digital world, students and faculty (as well as staff) had to organize their workflow around location-specific technology and resources. They needed to come to a computer center and then to a computer lab and then to a computer in their office to do their work. The same process was true with a library. You needed to organize your workflow around your ability to physically access the resources you needed. Thus the IT organization and the library had a limited interaction with the full process of academic work, teaching and learning.

In the digital, Web-scaled, mobile world that we have now, IT and the library need to organize themselves around the entire workflow of learners and teachers and researchers. That requires a reimagining of the very purpose of those organizations and the services that they provide, as well as new staff or retraining staff with new skills.

8) Consumerization

Bramucci: Used to be, enterprise tech filtered down to consumers. Now that's inverted: Increasingly, consumer technology trends are driving the enterprise, with the individual student the primary driver of product and service design for technologies that are increasingly personalized. That's one of the reasons we hire students for our software design teams. They participate in everything — design, user acceptance testing, usability testing, training and marketing. They've given us some of our very best ideas as well as kept us from doing things students don't want!

McQuesten: Inexpensive devices, widespread and inexpensive access to networks and the increasing availability of information in digital form make it possible for the individual to do work, teach, learn, entertain himself, etc., without relying on an institution to be the primary provider. So IT and the library and the institution itself will need to adapt services not just to incorporate the use of personal technology, but more importantly to support a "workflow" that moves seamlessly across institutional and personally accessed resources. The days of "we don't support that" will be replaced by concierge broker services that help students, faculty and staff assemble the right portfolio of technologies, services and resources to accomplish their work, no matter whether they are "owned" by the institution or not.

Baron: I see this trend manifesting itself in higher education's emerging strategic focus on the "user experience" (UX). Highly usable sites such as Google and Amazon have set expectations among users that systems should be easily used without training or big manuals to review. This consumerization of the Web is impacting how our students, faculty and staff expect to be able to use everything from the LMS to the ERP, yet higher education does not have the resources or, in some cases, the skills needed (in the form of experienced UX designers) to address this growing trend. As a result, IT may need to look at strategic investments in both people and new methodologies in order to remain competitive and meet our users' expectations.

9) Adaptive & Personalized Learning

Chapel: The MOOC buzz has died off a bit, thank goodness, but MOOCs and the multifaceted delivery systems and online educational resources at the disposal of learners today continue to call into question what higher education will look like over the course of the next two decades. All of these technology-based disruptions invite us to recognize that students/learners are on a spectrum of learning styles and preferences for how they wish to (and are able to) fully realize their learning potential and achieve their educational goals. This area warrants continued attention.

Bowen: The most exciting opportunities for personalized learning will be how faculty creatively integrate it within courses. Coupling personalized learning tools with hybrid teaching models, or as part of developing competencies demonstrated through digital badges, can help formulate new teaching methods. Providing a "choose your own adventure" approach helps students to focus on the areas of greatest need — aligning learning with their own interests or career trajectories. While personalized learning has emerged as an alternative to one-size-fits-all approaches, we should also recognize that personalized learning itself is not a one-size-fits-all solution.

McQuesten: The barrier to adoption of adaptive learning systems is emotional, not technological. Acknowledging the fact that a computer might provide a more consistent and correct analysis of learning mistakes, as well as offering an optimal set of content and exercises that could help someone learn from their mistakes, takes a great deal of self-confidence and courage if you have spent the better part of your life identifying as a teacher who does that task well. If we can help faculty see how adaptive learning systems can become part of an overall pedagogical approach, we may see more use of them in traditional higher education environments.

Baron: What would a look a "hot trends" in ed tech be without at least one crazy prediction, so here it goes.... Adaptive learning is a trend that has been slowly maturing over the past two decades and I believe we are approaching the point where such systems will be better at teaching core basic skills, diagnosing where a student is confused and determining how best to scaffold him to better understand the material, than a human being. This will be facilitated by the increasing sophistication of "knowledge maps" (which detail all of the prerequisite knowledge needed to understand a core concept — such as solving linear equations) and the underlying analytics that power the use of these knowledge maps. Plus, these systems are endlessly patient and cost-effective. Am I saying that they will replace teachers? Absolutely not, but I do think they will dramatically shift the role of the teacher from provider of information to facilitator of the learning process.