Trends Glossary

We asked about 39 IT trends in this year's research. The 2018 trends apply across a number of different IT domains.

Adaptive learning: In adaptive learning models, when a learner interacts with instructional material, the software adapts to the student's learning needs, modifying the content and method accordingly. In this way, adaptive learning provides learners with individualized instruction and, in some cases, improved learning outcomes.

Agile approaches to change: Agile software development calls for adaptive planning, continuous improvement, and rapid and flexible response to change. These concepts can also be applied to change management in general. The software design strategies of flexibility and continuous improvement are finding their way into efforts related to strategic planning, desktop management, IT governance, and infrastructure planning.

Applications and implications of artificial intelligence to higher education: The incorporation of artificial intelligence capabilities (such as natural language processing and cognitive systems and analytics) into applications, smart machines, and robots carries various implications for instruction, research, student services, admissions, administrative services, and the higher education workforce.

Bimodal IT: Traditional IT service focuses on stable operations, while an agile or emergent model emphasizes speed and innovation. The premise of bimodal IT is that both types of service delivery are needed in order for IT operations to create value for the underlying institution.

Blending of roles and blurring of boundaries between IT and academic/administrative areas: CIOs and IT organizations are being pushed into new, more integrative roles. Meanwhile, almost all strategic discussions around academic transformation presume the need to integrate a variety of campus organizations to further the teaching and learning mission. Entailed in this blending and blurring of roles are new job titles, new governance models, new skill sets, and new demands for professional development.

Business process redesign: Examining and redesigning work processes through business process management can uncover opportunities for greater efficiency, possibly allowing for cost savings or reallocation of resources. Because processes tend to span functional unit boundaries, strategies in this area are most successful when they include multiple units at an institution. Business process encompasses workflow design, systems capabilities, motivation, human resources, policies, rules, funding, and other resources.

Campus safety: The safety and security of campus students, faculty, staff, and visitors is a priority for higher education institutions. Institutions regularly evaluate their campus operations to strengthen and improve them. Similarly, the security of campus resources, including IT resources and data, is a concern. Institutions must regularly review and improve IT operations to ensure the security of IT systems and data resources.

Changing enterprise system architectures, integrations, and workflows: Colleges and universities run a large set of enterprise-wide computing systems, and options for these systems are expanding and becoming more specialized. In addition, many institutions now choose cloud options, resulting in a mix of systems from different vendors, some on-premises and some in the cloud. These changes require IT to focus on system architectures, integrations, and workflows to ensure adequate interconnection between systems and data, enabling computer systems to effectively share information, automate data-sharing workflows, and efficiently support task workflows for students, faculty, and staff.

Changing faculty roles: New instructional models and the innovative use of technology have resulted in faculty serving as coaches, software developers, advisors, and instructional leads to sizable cohorts of adjunct faculty. Team-developed courses and demands for increased access to education that can be delivered in various ways have led to an increased focus on the quality of instruction and the rise of the instructional design profession. The faculty transformation continues as an evolving competitive workplace, and rising higher education costs place new demands on the relevance of higher education.

Climate change: Institutions are taking steps to mitigate the magnitude of climate change through green and sustainable technologies, even as they are adapting to the impact of increased severe weather events on areas such as operations, risk management, disaster recovery, and travel.

Complexity of security threats: The security threat landscape is increasingly complex, with cloud applications, the Internet of Things, complicated technology architectures, and sophisticated emerging threats, requiring a flexible and layered institutional approach to information security. Finding new tools and technologies to help identify and mitigate these threats is of great importance to IT professionals.

Compliance environment: The regulatory environment impacting higher education IT systems and the data contained in those systems can seem labyrinthine. Data elements in many IT systems may be protected by a number of federal, state, and local laws and industry regulations. The complicated regulatory environment can be difficult to understand, making it even harder to secure IT systems in a compliant manner.

Concerns about institutional sustainability or survival: Higher education institutions are facing a range of pressures, including competition from for-profit institutions, alternative educational models, decreased revenue from tuition dollars, and, in the case of public institutions, decreased state budget allocations. Combined with internal demands to provide the best educational experiences possible for students, these difficulties may undermine the long-term stability of colleges and universities.

Contributions of IT to institutional operational excellence: Information technology is increasingly being used to improve operational efficiency and effectiveness, through activities such as automation, personalization, mobile access, outsourcing, shared services, and process improvement.

Cross-institutional and international scholarly and research collaborations: Research collaborations are increasingly the norm, and institutions need to be ready to support a greater quantity of increasingly complex collaborations, working across institutional and international lines. Collaborating with colleagues beyond the institution is getting easier through a variety of options that include enterprise-level collaboration tools as well as free web-based tools. Enterprise tools offer more assurance of privacy and security through the institution's identity management system.

Cross-institutional partnerships and consortia: In an effort to be as efficient as possible with enterprise IT systems and services, many institutions look to cross-institutional partnerships and consortia as a way to reduce costs or gain efficiency. In a purchasing consortium, a group of institutions develops a contractual relationship that allows for collective cost savings and the opportunity to work more closely with system and software vendors, including cloud vendors.

Data-driven decision making: Data-driven decision making aims to derive meaning from data and determine the best actions to take. This approach to decisions can be incorporated into existing planning and management activities and processes; it can also be programmed into applications to generate real-time, personalized triggers, alerts, and advice for students, faculty, advisors, and other constituents.

DevOps movement: DevOps efforts focus on building a collaborative relationship between development and operations staff to improve efficiency and provide better service. Strategies may include streamlining operations by automating and standardizing repetitive tasks and creating self-service applications. An institutional strategy that considers DevOps can take advantage of past work and save time on testing, potentially freeing resources for other activities.

Digital enterprise strategy: Some institutions are pursuing an enterprise strategy that emphasizes the use of technology as a competitive differentiator through innovative and often personalized applications to teaching and learning, student services, advising, research, admissions, alumni relations, fundraising, facilities management, etc.

Digitization of scholarly and research data: Data today are increasingly produced, used, manipulated, and studied in a digital format. Data management practices must accommodate digital resources throughout their life cycle. Higher education IT must provide researchers with the necessary tools and resources to work with and manage these data, including discipline-specific tools and practices, data visualization, interdisciplinary research support, and more.

Diversity, equity, and inclusion: Higher education benefits from a diversity of opinions and insights from myriad sources. Technology can be a key enabler of diversity, equity, and inclusion, allowing all voices to be heard. Another dimension of diversity is accessibility, and both the Department of Justice and the Department of Education have become increasingly active in this area. For the IT organization, diversity/inclusivity issues are relevant to staffing and IT workforce issues.

Evaluation of technology-based instructional innovations: The need to know which innovations have the greatest positive impact is more acute than ever. ECAR research on faculty and IT shows that the greatest motivator for faculty to incorporate technology into their teaching is evidence of its benefit to students. Due to the complexity of measuring pedagogical impact, a variety of evaluation methods must be employed to produce the evidence persuasive to key stakeholders.

Incorporating open standards into enterprise IT architecture: Getting the typical institution's wide variety of complex enterprise systems to interconnect is difficult. Most enterprises adopt an existing framework to integrate complex business workflows, data architectures, and communications standards between systems. For example, the Open Group Architecture Forum framework for enterprise architecture is a widely adopted set of standards, methods, terminologies, business workflow descriptions, and tools for standardizing systems-planning language and methods and for avoiding dependence on proprietary vendor solutions.

Incorporating risk-management approaches into IT strategy and service delivery: "Risk management" is a mechanism for managing uncertainty by identifying and assessing risks that threaten goals and then prioritizing and addressing those risks. As IT strategy and service delivery models evolve, addressing IT risk strategically involves focusing on IT's impact on institutional goals rather than on the simple identification of risks related to physical inventories of assets in isolation.

Increasing complexity of technology, architecture, and data: The pace of change in technology continues to increase. As institutions try to keep up, they find that the environments they manage are becoming more and more complex. New technologies need to be incorporated into the environment, older technologies need to be updated, and end users expect it all to work seamlessly. As the IT environment grows, and as cloud services are added to the environment, IT complexity increases.

Institution-wide data management and integrations: Next-generation enterprise IT provides agility, scalability, and cost-effectiveness through a combination of applications, architectures, and sourcing strategies. However, it also complicates the challenge of making disparate systems communicate with each other. To provide useful information from many different systems and applications, IT needs an institution-wide strategy for data management that accounts for multiple stakeholder needs, as well as an intentional focus on data integration across many types of systems.

Internet of Things: The number of Internet-capable objects is expected to surpass 20 billion by 2020, two-thirds of which will be consumer-level devices, including wearables and other person-based devices that offer the potential for learning about behavior, particularly if they begin to automatically interact with institutional applications. Other opportunities include automating and enhancing infrastructure management. This enormous change will increase bandwidth needs, contribute to privacy and security challenges, introduce new computation needs, and potentially provide enormous opportunities for institutions as they begin to support smart campuses of the future.

IT as an agent of institutional transformation and innovation: IT can be the vehicle by which an innovation is realized. At the same time, new breakthroughs in IT can open the door for new innovations and opportunities. Moreover, the power of IT can greatly increase the scope and scale of current initiatives (e.g., the collection and analysis of greater amounts of data provide the basis for new directions for business modeling and technology-enabled student advising).

Managing mobility (of people, data, institutional resources): As mobile devices become ubiquitous, as the Internet of Things expands, and as stakeholders expect seamless connectivity through mobile devices to institutional resources and data, institutions need to consider a number of IT and business processes that cover the management, administration, and support for mobile services, finding a balance between access and control.

National and global political uncertainty: Political uncertainty brings implications for IT operations and investments, including areas such as information security threats, support for international and traveling students and scholars, state and federal institutional and grant funding, and potential new or changed policies.

Reduced reliance on service desk as the primary model for support: Knowledge management and automation are enabling IT organizations to provide alternatives to supplement the traditional call centers or walk-in service desk support. This helps offset growing demand for IT support, as faculty, staff, and students increasingly want to access institutional resources from their personal devices and environments. Web- or app-based self-help can supplement the hours of the help desk, as are outsourced IT service desks to either supplement or replace institution-staffed service desks.

Service management (ITSM, ITIL): ITSM (IT service management) is the practice of running the IT organization with a focus on delivery of services to constituents in a repeatable, measurable, and proactive way that is aligned with organizational needs. ITIL (information technology infrastructure library) is a framework of service management processes designed to optimize the internal operations of the IT organization. ITIL is a way to operationalize ITSM concepts. Other, complementary processes and frameworks that support ITSM include COBIT (for governance, audit, and compliance), Lean (for continuous improvement), Agile (for development), and DevOps (to integrate development and service delivery).

Shared services: Shared services is the provision of a service by one part of an organization or group rather than by multiple parts of the organization, offering decreased costs and greater value for the institution. In contrast to centralization, which typically emphasizes compliance and control, shared services focuses on collaboratively developing business processes and service level agreements that deliver value to the business. Strategies that include leadership engagement, good change-management practices, shared governance, and a long-term financial model will lead to greater success in shared-services efforts.

Strategic relationships with vendors: IT is increasingly a service broker and partner rather than a technology provider. This shift allows for a strategic conversation between the institution and vendors, bringing technology investments into closer alignment with institutional mission in the process. In the broker role, IT can ensure that cloud contracts meet institutional needs for data management, security, backup, and more.

Student success focus/imperatives: With an increased national focus on student completion, higher education faces a new urgency not only to innovate but also to collaborate across departmental silos to bring about institutional transformation. In an environment of big data, institutions are being called on to change the way they address student success, resulting in more students finishing what they start and developing the skills to contribute to society in and beyond the workplace.

Ubiquitous digital sources and streams: Institutional data stores, systems, and applications provide a wealth of information that can be used in analytics initiatives. Increasingly, data from sources such as social media, open educational resources, and the Internet of Things should also be considered potentially important information, presenting institutions with the challenges not only of collecting and harnessing so much data but also of dealing with policy, privacy, and cultural issues related to externally sourced data.

Use of algorithms to influence institutional and individual choices: There are risks and benefits of applying either homegrown or proprietary vendor algorithms to personalize and inform instruction, curricula, educational plans, student outcomes, staff hiring and evaluations, etc. Risks include the costs of maintaining homegrown algorithms, lack of transparency in vendor algorithms (and how student success metrics and triggers might be inadvertently affected by changing vendors), and fallout of potential false positives and false negatives.

User-centered design: Technology management best practices increasingly emphasize factoring end users' needs and experiences in the design, configuration, deployment, and support of IT services and applications. This has implications for current IT projects, services, processes, and staffing.

Vendor relationships that bypass IT: As cloud-based services become increasingly common, individual departments often bypass IT departments and negotiate directly with vendors to select and purchase technology-related services. This practice makes it difficult for IT staff to maintain standards for architecture and integration, and it complicates concerns for information security, compliance, privacy, data management, and data governance.