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NMC Horizon Report
2014 Higher Education Preview
NMC Horizon Report > 2014 Higher Education Preview
The
Horizon Project Preview is a high-level summary of an upcoming edition’s
findings used to elaborate on the particular definitions and framings to be used
in the report,
and to provide a snapshot of the topics that will be explored in the final
edition. The contents of this Preview are a work-in-progress.
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Key Trends Accelerating Ed Tech Adoption in
Higher Education
Fast Moving Trends: Those likely to create substantive change (or burn out) in
one to two years
Online, Hybrid, and Collaborative Learning ,
Social Media Use in Learning
Mid-Range Trends: Those likely to take three to five years to create
substantive change
The Creator Society ,
Data-Driven Learning and Assessment
Slow Trends: Those likely to take more than five years to create substantive
change
Agile Approaches to Change ,
Making Online Learning Natural
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Significant Challenges Impeding Ed Tech Adoption
in Higher Education
Urgent Challenges: Those which we both understand and know how to solve
Low Digital Fluency of Faculty ,
Relative Lack of Rewards for Teaching
Difficult Challenges: Those we understand but for which solutions are elusive
Competition from New Models of Education ,
Scaling Teaching Innovations
Wicked Challenges: Those that are complex to even define, much less address
Expanding Access ,
Keeping Education Relevant
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Important Developments in Educational Technology
for Higher Education
Time-to-Adoption Horizon: One Year or Less
Flipped Classroom ,
Learning Analytics
Time-to-Adoption Horizon: Two to Three Years
3D Printing ,
Games and Gamification
Time-to-Adoption Horizon: Four to Five Years
Quantified Self ,
Virtual Assistants
Key Trends Accelerating Ed Tech Adoption
in Higher Education
Fast
moving trend likely to create substantive change (or burn out) in one to two
years
Education paradigms are shifting to include online learning, hybrid learning,
and collaborative models. Students already spend much of their free time on
the Internet, learning and exchanging new information. Institutions that
embrace face-to-face/online hybrid learning models have the potential to
leverage the online skills learners have already developed independent of
academia. Online learning environments can offer different affordances than
physical campuses, including opportunities for increased collaboration while
equipping students with stronger digital skills. Hybrid models, when designed
and implemented successfully, enable students to travel to campus for some
activities, while using the network for others, taking advantage of the best
of both environments.
Fast
moving trend likely to create substantive change (or burn out) in one to two
years
Social media is changing the way people interact, present ideas and
information, and judge the quality of content and contributions. More than one
billion people use Facebook regularly; other social media platforms extend
those numbers to nearly one third of all people on the planet. Educators,
students, alumni, and even the general public routinely use social media to
share news about scientific and other developments. The impact of these
changes in scholarly communication and on the credibility of information
remains to be seen, but it is clear that social media has found significant
traction in almost every education sector.
Mid-range
trend likely to take three to five years to create substantive change
The shift continues towards becoming a creator society. Today, society is
increasingly mobile and continues to demonstrate evidence that creation is
gaining traction over consumption. The Maker movement, user-generated videos,
self-published eBooks, personalized domains, and other platforms have all seen
steep increases in recent years. Higher education is now in a position to
shift its curricular focus to ensure learning environments align with the
engagement of creator-students and foster the critical thinking skills needed
to fuel a creator society. Courses and degree plans across all disciplines at
institutions are in the process of changing to reflect the importance of media
creation, design, and entrepreneurship.
Mid-range
trend likely to take three to five years to create substantive change
There is a growing interest in using new sources of data for personalizing the
learning experience and for performance measurement. As learners participate
in online activities, they leave a clear trail of analytics data that can be
mined for insights. Learning analytics is a collection of tools to process and
analyze that data stream, and use it to modify learning goals and strategies
in real time. As the field of learning analytics matures, the hope is that
this information will enable continual improvement of learning outcomes.
Slow trend
likely to take more than five years to create substantive change
There is a growing consensus among many higher education thought leaders that
institutional leadership could benefit from agile startup models. Educators
are working to develop new approaches based on these models that stimulate
top-down change and can be implemented across a broad range of institutional
settings. The Lean Startup movement that is currently taking place in Silicon
Valley is offering
such a path toward using technology as a catalyst for building and measuring
change in a rapid, cost- effective manner. Pilots and other experimental
programs can be developed for teaching and improving organizational structure,
and then evaluated quickly using scientific methods.
Slow trend
likely to take more than five years to create substantive change
Asynchronous voice and video tools are humanizing online learning.
Historically, one of the major concerns people have expressed about online
courses is the lack of interaction. People desire digital learning
opportunities that mimic face-to-face experiences. Learning management systems
and other services are beginning to incorporate recording features that allow
both faculty and students to communicate more authentically online. For
example, Canvas includes audio recording from text and Blackboard enables
recordings that upload directly to YouTube. Media production and sharing is
already inherent in a host of other free, easy-to-use social media platforms,
such as Vimeo, Instagram, and Vine. Increasingly, faculty are creating videos
for more than just lectures; they are using them as tools to introduce
themselves, make announcements, and provide brief background or examples of
assignments.
Significant Challenges Impeding Ed Tech
Adoption in Higher Education
Urgent
challenge that we both understand and know how to solve
Faculty training still does not acknowledge the fact that digital media
literacy continues its rise in importance as a key skill in every
discipline and profession. Despite the widespread agreement on the
importance of digital media literacy, training in the supporting skills
and techniques is rare in teacher education and non-existent in the
preparation of faculty. As lecturers and professors begin to realize that
they are limiting their students by not helping them to develop and use
digital media literacy skills across the curriculum, the lack of formal
training is being offset through professional development or informal
learning, but we are far from seeing digital media literacy as a norm.
This challenge is exacerbated by the fact that digital literacy is less
about tools and more about thinking, and thus skills and standards based
on tools and platforms have proven to be somewhat ephemeral.
Urgent
challenge that we both understand and know how to solve
Teaching is generally (or at least often) rated lower than research in
academia. In the global education marketplace, a university's status is
largely determined on the quantity and quality of its research. According
to the Times Higher Education's World University Rankings
methodology, research and citations account for 60% of a university's
score, while teaching is only half that. There is an overarching sense in
the academic world that research is first, while teaching is an obligation
that must be performed. Because of this way of thinking, efforts to
implement effective pedagogies are lacking. Adjunct professors and
students feel the brunt of this challenge, as teaching-only contracts are
underrated and underpaid, and learners must accept the outdated teaching
styles of the university’s primary researchers. To balance competing
priorities, larger universities are experimenting with alternating heavy
and light teaching loads throughout the school year, and hiring more
adjunct professors.
Difficult challenge that we understand but for which solutions are elusive
New models of education are bringing unprecedented competition to the
traditional models of higher education. Across the board, institutions are
looking for ways to provide a high quality of service and more learning
opportunities. MOOCs are at the forefront of these discussions, enabling
students to supplement their education and experiences at brick-and-mortar
institutions with increasingly rich, and often free, online offerings. At
the same time, issues have arisen related to the low completion rates of
some MOOCs. As these new platforms emerge, there is a growing need to
frankly evaluate the models and determine how to best support
collaboration, interaction, and assessment at scale. Simply capitalizing
on new technology is not enough; the new models must use these tools and
services to engage students on a deeper level.
Difficult challenge that we understand but for which solutions are elusive
Our organizations are not adept at moving teaching innovations into
mainstream practice. Innovation springs from the freedom to connect ideas
in new ways. Our schools and universities generally allow us to connect
ideas only in prescribed ways — sometimes these lead to new insights, but
more likely they lead to rote learning. Current organizational promotion
structures rarely reward innovation and improvements in teaching and
learning. A pervasive aversion to change limits the diffusion of new
ideas, and too often discourages experimentation.
Wicked
challenge that is too complex to even define, much less address
The global drive to increase the number of students participating in
undergraduate education is placing pressure across the system. The
off-cited relationship between earning potential and educational
attainment plus the clear impact of an educated society on the growth of
the middle class is pushing many countries to encourage more and more
students to enter universities and colleges. In many countries, however,
the population of students prepared for undergraduate study is already
enrolled — expanding access means extending it to students who may not
have the academic background to be successful without additional support.
Many in universities feel that these institutions do not have sufficient
time and resources to help this set of students.
Wicked
challenge that is too complex to even define, much less address
Many pundits worry that if higher education does not adapt to the times,
other models (especially other business models) will take its place. While
this concern has some merits, it is unlikely that universities as we know
them will go away. There are parts of the university enterprise, however,
that are at risk, such as continuing and advanced education in highly
technical, fast-moving fields. As online learning and free educational
content become more pervasive, institutional stakeholders must address the
question of what universities can provide that other approaches cannot,
and rethink the value of higher education from a student's perspective.
Important Developments in
Educational Technology for Higher Ed
Technology to Watch: Time-to-Adoption: One Year or Less
The flipped classroom refers to a model of learning that rearranges how
time is spent both in and out of class to shift the ownership of
learning from the educators to the students. After class, students
manage the content they use, the pace and style of learning, and the
ways in which they demonstrate their knowledge, and the teacher becomes
the guide, adapting instructional approaches to suit their learning
needs and supporting their personal learning journeys. Rather than the
teacher using class time to lecture to students and dispense
information, that work is done by each student after class, and could
take the form of watching video lectures, listening to podcasts,
perusing enhanced e-book content, collaborating with their peers in
online communities, and more. Students can access this wide variety of
resources any time they need them. In the flipped classroom model,
valuable class time is devoted to more active, project-based learning
where students work together to solve local or global challenges — or
other real- world applications — to gain a deeper understanding of the
subject. Teachers can also devote more time interacting with each
individual. The goal is for students to learn more authentically by
doing, with the teacher guiding the way; the lecture is no longer the
expected driver of concept mastery. The flipped classroom model is part
of a larger pedagogical movement that overlaps with blended learning,
inquiry- based learning, and other instructional approaches and tools
that are meant to be flexible, active, and more engaging for students.
It has the potential to better enable educators to design unique and
quality learning opportunities, curriculum, and assessments that are
more personal and relevant to students’ lives.
Technology to Watch: Time-to-Adoption: One Year or Less
Learning analytics is an educational application of “big data,” a
science that was originally used by businesses to analyze commercial
activities, identify spending trends, and predict consumer behavior. The
rise of the Internet drove research into big data and metrics as well as
the proliferation of web tracking tools, enabling companies to build
vast reserves of information they could study and apply to their
marketing campaigns. Education is embarking on a similar pursuit into
data science with the aim of improving student retention and providing a
high quality, personalized experience for learners. Learning analytics
research uses data analysis to inform decisions made on every tier of
the educational system. Whereas analysts in business use consumer data
to target potential customers and personalize advertising, learning
analytics leverages student data to build better pedagogies, target
at-risk student populations, and assess whether programs designed to
improve retention have been effective and should be sustained
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outcomes for legislators and administrators that have profound impact.
For educators and researchers, learning analytics has been crucial to
gaining insights about student interaction with online texts and
courseware. Students are beginning to experience the benefits of
learning analytics as they engage with mobile and online platforms that
track data to create responsive, personalized learning experiences.
Technology to Watch: Time-to-Adoption: Two to Three Years
Known in industrial circles as rapid prototyping, 3D printing refers to
technologies that construct physical objects from three-dimensional (3D)
digital content such as 3D modeling software, computer-aided design
(CAD) tools, computer-aided tomography (CAT), and X-ray crystallography.
A 3D printer builds a tangible model or prototype from the electronic
file, one layer at a time, through an extrusion-like process using
plastics and other flexible materials, or an inkjet-like process to
spray a bonding agent onto a very thin layer of fixable powder. The
deposits created by the machine can be applied very accurately to build
an object from the bottom up, layer by layer, with resolutions that,
even in the least expensive machines, are more than sufficient to
express a large amount of detail. The process even accommodates moving
parts within the object. Using different materials and bonding agents,
color can be applied, and parts can be rendered in plastic, resin, or
metal. This technology is commonly used in manufacturing to build
prototypes of almost any object (scaled to fit the printer, of course)
that can be conveyed in three dimensions.
Technology to Watch: Time-to-Adoption: Two to Three Years
The games culture has grown to include a substantial proportion of the
world’s population, with the age of the average gamer increasing with
each passing year. As tablets and smartphones have proliferated, desktop
and laptop computers, television sets, and gaming consoles are no longer
the only way to connect with other players online, making game-play a
portable activity that can happen in a diverse array of settings.
Gameplay has long since moved on from solely being recreational and has
found considerable traction in the worlds of commerce, productivity, and
education as a useful training and motivation tool. While a growing
number of educational institutions and programs are experimenting with
game-play, there has also been increased attention surrounding
gamification — the integration of gaming elements, mechanics, and
frameworks into non-game situations and scenarios. Businesses have
embraced gamification as a way to design incentive programs that engage
employees through rewards, leader boards, and badges, often with a
mobile component. Although more nascent than in military or industry
settings, the gamification of education is gaining support among
educators who recognize that effectively designed games can stimulate
large gains in productivity and creativity among learners.
Technology to Watch: Time-to-Adoption: Four to Five Years
Quantified self describes the phenomenon of consumers being able to
closely track data that is relevant to their daily activities through
the use of technology. The emergence of wearable devices on the market
such as watches, wristbands, and necklaces that are designed to
automatically collect data are helping people manage their fitness,
sleep cycles, and eating habits. Mobile apps also share a central role
in this idea by providing easy-to-read dashboards for consumers to view
and analyze their personal metrics. Empowered by these insights, many
individuals now rely on these technologies to improve their lifestyle
and health. Today’s apps not only track where a person goes, what they
do, and how much time they spend doing it, but now what their
aspirations are and when those can be accomplished. Novel devices, too,
are enabling people to track their lives automatically, such as the
Memoto, a camera worn around the neck that is designed to capture an
image every half minute. As more people rely on their mobile devices to
monitor their daily activities, data is becoming a larger part of
everyday life.
Technology to Watch: Time-to-Adoption: Four to Five Years
As voice recognition and gesture-based technologies advance and more
recently, converge, we are quickly moving away from the notion of
interacting with our devices via a pointer and keyboard. Virtual
assistants are a credible extension of work being done with natural user
interfaces (NUIs), and the first examples are already in the
marketplace. The concept builds on developments in interfaces across the
spectrum of engineering, computer science, and biometrics. The Apple
iPhone’s Siri and Android's Jellybean are recent mobile-based examples,
and allow users to control all the functions of the phone, participate
in lifelike conversations with the virtual assistant, and more. A new
class of smart televisions are among the first devices to make
comprehensive use of the idea. While crude versions of virtual
assistants have been around for some time, we have yet to achieve the
level of interactivity seen in Apple's classic video, Knowledge
Navigator. Virtual assistants of that caliber and their applications for
learning are clearly in the long-term horizon, but the potential of the
technology to add substance to informal modes of learning is compelling.
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