Higher education leaders have shifted focus from reducing costs and driving efficiencies toward using technology to enhance competitive advantage and support emerging business models — and ultimately, the institution’s main missions of education and research, according to Gartner, Inc. Gartner forecasts that worldwide higher…
SYDNEY, Australia, Feb. 25 — Higher education leaders have shifted focus from reducing costs and driving efficiencies toward using technology to enhance competitive advantage and support emerging business models — and ultimately, the institution’s main missions of education and research, according to Gartner, Inc.
Gartner forecasts that worldwide higher education sector spending will grow 1.2 per cent to reach $38.2 billion in 2016.
For institutions to thrive in the increasingly competitive education ecosystem, they must become more innovative and it is often technology that will underpin that innovation.
“Higher education is still mostly considered a conservative and slow-moving industry, with the majority of innovation coming from outside the traditional education IT organisation,” said Jan-Martin Lowendahl, vice president and distinguished analyst at Gartner. “However, it is only a matter of time until all this innovation will impact the institution and, ultimately, the CIO.”
Gartner has identified the top 10 strategic technologies for the higher education sector in 2016 and provides recommendations to education CIOs and IT leaders regarding adoption and benefits. “It is not a list of what education CIOs spend the most time or money on, rather it is a list of strategic technologies that we recommend higher education CIOs should have a plan for in 2016,” added Mr. Lowendahl.
- Adaptive Learning
Institutions are increasingly looking to adaptive learning to help solve the challenge of providing scalable personalised learning. Adaptive learning dynamically adjusts the way instructional content is presented to students based on their responses or preferences. It is increasingly dependent on a large-scale collection of learning data and algorithmically derived pedagogical responses. It takes two major forms: (1) textbooks, where algorithms are packaged with content from a publisher for an end user; and (2) platforms, where end users add their own content to an adaptive learning environment.
- Predictive Analytics
Predictive analytics involves extracting an analytical model from multiple sources of data to predict future behaviour or outcomes. Predictive analytics are seen by higher education leaders as a key part of strategies to improve student success and save money through improved retention. A majority of the higher education analytics tools currently on the market claim to use predictive analytics, but there are relatively few tools that truly implement predictive analytics.
Customer relationship management (CRM) is now a widely recognised tool for tracking and managing relationships with constituents, including prospective and current students, parents, alumni, corporations, benefactors and other friends of the institution. CRM systems have two primary objectives — automating and improving student-centric business processes, and gathering data to produce analytics to improve institutional decision making. CRM technologies can be implemented to support all phases of the student life cycle — recruitment, enrolment, engagement, retention, alumni, career services and continuing education.
Exostructure strategy means acquiring the critical capability of interoperability as a deliberate strategy to integrate the increasing numbers of partnerships, tools and services in the education ecosystem. When done right, an exostructure approach enables institutions to leverage services from the cloud, rather than having to bring them inside the campus walls. Enabled by standards, it can allow the institution to adapt faster. With the increasing interdependencies in the education ecosystem, Gartner sees it rising in importance for at least the next decade. The future belongs to exostructure rather than to infrastructure.
- Open Microcredentials
Microcredentials in the form of various badges or points have existed for some time in digital social environments in general, and in learning environments in particular. A key problem is that these environments are proprietary, which makes it difficult to display achievements outside of them. The aim of open microcredentials is to remedy that problem. For education institutions, issuing open microcredentials is a low-cost, high-value, technology-based capability that will provide more value and motivation to students. Open microcredentials is still relatively immature as a technology, but it is gaining traction in the education community. Gartner sees it as a clear strategic technology with a relatively small investment involved, thereby making it a low-hanging fruit with good ROI.
- Digital Assessment
Digital assessment refers to the application of digital technologies to create, administer, report and manage tests and examinations. It is an increasingly important aspect of online learning as it feeds into a number of growing areas such as analytics, adaptive learning, competency-based education and new regimes of scrutiny, transparency and accreditation. Many institutions are making increasing investments in new assessment technologies. Often the impetus for these investments is coming from disparate parts of the organisation, driven by different assessment needs. Assessment tools are becoming a critical aspect of achieving personalisation at scale.
- Smart Machines
Smart machines are an exciting new trend on the list that promises to take adaptive learning and analytics, for example, to a new level that approaches algorithmic education. As globalisation and political belief in a market force approach to higher education continues to increase competition, smart machines will be a key differentiator in helping the institution articulate its value, as well as deliver value to a student, leading to building a better brand. Smart machines can be used for analytics, student and faculty advice, as well as in improving research productivity.
- OER Ecosystem
Open educational resource (OER) ecosystems are pieces of educational content and media that are findable, freely available, and increasingly include tools and services to improve quality and production of open content. The OER ecosystem is not new as such, but is increasing in importance to help drive down costs for students and increase control of educational content and channels. OERs exhibit the five characteristics of openness — that is, users can retain, reuse, revise, remix and redistribute the content freely. CIOs have typically not been closely involved in supporting content used as textbooks or lecture material, but this is changing as the use of OERs expand.
- Listening and Sensing Technology
Listening and sensing technologies are a broad collection of virtual capabilities that range from social listening and sentiment analysis through capture and interpretation of social activities, such as tweets to technologies that operate in the Internet of Things. In higher education, the use of social listening tools and social harvesting tools is in a very nascent stage, and when employed, it is most often used to aid in recruiting and enrolment. However, there is potential for it to play a significant role across the entire student journey. However, most institutions are at very low maturity levels with these tools.
- Collaboration Technology
The need to find people and ideas and communicate and collaborate on a global scale has always been fundamental to the higher education community. Collaboration technology is a sweeping definition of technology that facilitates research, education and outreach effectiveness for a team. It is certainly not a new trend or capability. However, it has increasing importance in a globalised online education ecosystem where many team members are geographically scattered.
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