Key Trends Accelerating Technology Adoption in Higher Education

The six trends¹ described in the NMC Horizon Report were selected by the project’s expert panel in a series of Delphi-based voting cycles, each accompanied by rounds of desktop research, discussions, and further refinements of the topics. These trends, which the members of the expert panel agreed are very likely to drive technology planning and decision-making over the next five years, are sorted into three movement-related categories—long-term trends that typically have already been affecting decision-making and will continue to be important for more than five years; mid-term trends that will likely continue to be a factor in decision-making for the next three to five years; and short-term trends that are driving educational technology adoption now, but will likely remain important for only one to two years, either becoming commonplace or fading away in that time.

While long-term trends have already been the topic of many education leaders’ discussions and extensive research, short-term trends often do not have an abundance of concrete evidence pointing to their effectiveness and future directions. All of the trends listed here were explored for their implications for higher education in a series of online discussions that can be viewed at here.

The NMC Horizon Project model derived three metadimensions that were used to focus the discussions of each trend and challenge: policy, leadership, and practice. Policy, in this context, refers to the formal laws, regulations, rules, and guidelines that govern institutions; leadership is the product of experts’ visions of the future of learning, based on research and deep consideration; and practice is where new ideas and pedagogies take action, in universities and colleges and related settings. Below are summaries of the six key trends that will be explored more in-depth in this section, with citations and resources included.

Advancing Cultures of Innovation. As campuses have evolved into hotbeds for entrepreneurship and discovery, higher education has become widely regarded as a vehicle for driving innovation. The focus of this trend has shifted from understanding the value of fostering the exploration of new ideas to finding ways to replicate it across a span of diverse and unique learning institutions. Research has been conducted over the past year to better understand how institutions can nurture the types of culture that promotes experimentation. A significant element for progressing this movement is the call for higher education to alter its status quo to accept failure as an important part of the learning process. The act of integrating entrepreneurship into higher education further acknowledges that every big idea has to start somewhere, and students and faculty can be equipped with the tools needed to spark real progress. In order to keep pace, institutions must critically assess their curriculum and implement changes to their evaluation methods in order to remove barriers that limit the development of new ideas.

Deeper Learning Approaches. There is an ongoing emphasis in higher education on deeper learning approaches, defined by the William and Flora Hewlett Foundatio² as the mastery of content that engages students in critical thinking, problem-solving, collaboration, and self-directed learning. To remain motivated, students need to be able to make clear connections between their coursework and the real world, and how the new knowledge and skills will impact them. Project-based learning, challenge-based learning, inquiry-based learning, and similar methods are fostering more active learning experiences. While deeper learning is proving to be effective for improving graduation rates in schools, its implementation in higher education settings is not as robust, pointing to the need for colleges and universities to make larger investments in quality teaching. As the enabling role of technologies for learning crystalizes, instructors are leveraging these tools to relate materials and assignments to real-life applications.

Growing Focus on Measuring Learning. This trend describes an interest in assessment and the wide variety of methods and tools that educators use to evaluate, measure, and document academic readiness, learning progress, skill acquisition, and other educational needs of students. As societal and economic factors redefine what skills are necessary in today’s workforce, colleges and universities must rethink how to define, measure, and demonstrate subject mastery and soft skills such as creativity and collaboration. The proliferation of data mining software and developments in online education, mobile learning, and learning management systems are coalescing toward learning environments that leverage analytics and visualization software to portray learning data in a multidimensional and portable manner. In online and blended courses, data can reveal how student actions contribute to their progress and specific learning gains.

Redesigning Learning Spaces. As universities engage with strategies that incorporate digital elements and accommodate more active learning in the physical classroom, they are rearranging physical environments to promote these pedagogical shifts. Educational settings are increasingly designed to support project-based interactions with attention to greater mobility, flexibility, and multiple device usage. To improve remote communication, institutions are upgrading wireless bandwidth and installing large displays that allow for more natural collaboration on digital projects. Further, universities are exploring how mixed reality technologies can blend 3D holographic content into physical spaces for simulations like experiencing Mars by controlling rover vehicles, or to enable multifaceted interaction with objects, such as the human body in anatomy labs, with detailed visuals. As higher education continues to move away from traditional, lecture-based lessons toward more hands-on activities, classrooms are starting to resemble real-world work and social environments that foster organic interactions and cross-disciplinary problem-solving.

Blended Learning Designs. Over the past several years, perceptions of online learning have been shifting in its favor as more learners and educators see it as a viable alternative to some forms of face-to-face learning. Drawing from best practices in both online and face-to-face methods, blended learning is on the rise at colleges and universities as the number of digital learning platforms and ways to leverage them for educational purposes continues to expand. The affordances blended learning offers are now well understood, and its flexibility, ease of access, and the integration of sophisticated multimedia and technologies are high among the list of appeals. The current focus of this trend has shifted to understanding how applications of digital modes of teaching are impacting students. Many findings showcase an increase in creative thinking, independent study, and the ability for the student to tailor learning experiences to meet their individual needs.

Collaborative Learning. Collaborative learning, which refers to students or educators working together in peer-to-peer or group activities, is based on the perspective that learning is a social construct. The approach involves activities generally focused around four principles: placing the learner at the center, emphasizing interaction, working in groups, and developing solutions to real challenges. In addition to improving student engagement and achievement, a key benefit of collaborative learning is bolstering openness to diversity, exposing students to people from different demographics. Educators also engage in collaborative learning through online communities of practice where ideas and insights are regularly exchanged. While this trend is rooted in pedagogy, technology plays an important role in the implementation; cloud-based services, apps, and other digital tools promote persistent connectivity, enabling students and educators to access and contribute to shared workspaces, anytime. Further, through adaptive learning and student advising platforms, data can be shared across an institution to illuminate student performance in order to inform improved instructional design and student advising.