II. Six Emerging Technologies & Practices
The 2020 Horizon Reports illustrates the higher education trends, technologies and practices shaping the future teaching, which the higher education professionals and experts are interested in and has become a tradition based on methodologies. In this section, the panel placed emphasis on describing impacts of emerging technologies and practices on postsecondary teaching and learning, with special focus on new major technologies. Six out of 130 candidates were selected through successive rounds of voting.
Adaptive Learning Technologies
Adaptive technology appears to be well on its way to becoming a major addition to the set of educational technology tools serving the broader educational practice of personalised learning. The wider adoption of adaptive technology in higher education commenced in 2011. It began to accelerate in 2015/2016, at a time when the technology was beginning to mature. Today, dozens of universities are using some type of adaptive instructional system to assist students in the learning process. It is important to distinguish between adaptive technology (aka courseware), personalised learning, and adaptive learning. Personalised learning is a general teaching and learning practice that seeks to more finely tune the course experience to the individual needs of the learners. Adaptive learning is one form of personalised learning in which adaptive technology plays a major role. The introduction of adaptive technology allows the role of the instructor to evolve, away from content delivery in the form of lectures during class and toward the roles of leader and coach during active learning exercises. Adaptive systems make this change possible by providing students with all of the instructional resources online and providing instructors with the learning data they needed to be more informed coaches and advisors.
AI/Machine Learning Education Applications
While machine learning (ML) is based on the idea that machines are able to learn and adapt through repetitive processes, artificial intelligence (AI) refers to the broader notion that machines can execute tasks intelligently. Both of these overlapping advancements are permeating higher education. We are beginning to see elements of them emerge throughout the enterprise, including in learning management systems (LMSs), student information systems (SISs), office productivity applications, library and admissions services, automatic captioning systems, and mobile products, to name a few. Although AI has not yet achieved self-awareness—that is, the ability to autonomously operate—it is able to support lower-order routine and repetitive cognitive tasks normally handled by humans. One of the many such technologies that colleges and universities are harnessing is automated chatbot services. AI-based chatbots extend off-hours student support and recruiting services and answer frequent and routine questions often posed by students and faculty. Meanwhile, Penn State University is leveraging ML algorithms to predict a student’s grade performance—even before courses begin. Using more than 8.5 million records culled from 2005 through 2016, the university developed a model to leverage data from the SIS, including transcript data and information found on admission applications. This predictive algorithm assists university administration in identifying students who might present with higher-than-average academic risks, allowing intervention strategies to be developed in advance.
Analytics for Student Success
The role of learning analytics has become increasingly important for global institutions to make strategic plans. Over the past decade, institutions of higher education have focused their mission, vision, and strategic planning on student outcomes and high-impact practices that promote student success. The availability of tools that measure, collect, analyse, and report data about students’ progress has given rise to the field of learning analytics for student success. Foundational data used for learning analytics include course-level data, such as assessment scores gleaned from the learning management system (LMS), and institutional-level data residing in student information systems, registrar records, financial systems, and institutional research units. The degree to which cross-functional (course- and institutional-level) data are used depends on a complexity of factors specific to individual campuses, such as the availability of technical tools, financial capacity, data availability, leadership support, and campus readiness to promote discussions and planning. The tools used to support analytics also range from vendor-based toolkits to the creation of customised campus applications. The Berkeley Online Advising project at the University of California at Berkeley and COMPASS, a project at the University of California, Irvine, are examples of learning analytics tools designed for academic advisors. These tools provide advisors with information that allows for proactive outreach and intervention when critical student outcomes are not met.
Elevation of Instructional Design, Learning Engineering, and UX Design
Additional responsibilities such as project management, learning analytics, educational research, faculty mentorship and collaboration, and more academic autonomy have elevated the professional identities and expertise of instructional designers. The instructional design role has seen growth and professional recognition beyond standard course design and development. New methods, processes, and scholarly work are emerging from teaching, learning, and technology communities, introducing new pathways and titles such as learning experience designer (LXD) and learning engineer. Many of these roles are well situated to be high-impact agents of change at their institutions, as they embody and promote student-centred and inclusive mindsets in their collaborations with faculty, students, and staff. A learning design ecosystem can include many roles, all of which serve the ultimate purpose of fostering student success in learning. Instructional designers and technologists are an integral part of learning design and technology teams. Learning designers (LDs) are skilled in a variety of methods, such as ADDIE and integrated course design, and they possess expertise in how students learn. A typical learning design toolbox is full of creative approaches and methods, evidence-based pedagogical strategies, student-centered activities, robust assessment plans, and innovative ways to use technology in teaching. The field is rapidly evolving through the influence of design thinking, user experience (UX) methods, systems design, advances in the learning sciences, and the emergence of learning analytics. Assessing how students learn, measuring user experiences, applying design thinking to course development, and providing faculty with new foundational digital skills and literacies are examples of additional functions that have boosted LDs into new roles. The merging of UX, design thinking, and cognitive psychology with instructional systems design gave rise to learning experience design. As teams shift toward holistic learning experience mindsets, they promote a student-centered ethos and better understand the entirety of the student experience.
Open Educational Resources
The United Nations Educational, Scientific and Cultural Organisation (UNESCO) defines open educational resources (OER) as a variety of materials designed for teaching and learning that are both openly available for use by teachers and students and that are devoid of purchasing, licensing, and/ or royalty fees. At the October 2019 UNESCO General Conference meeting held in Paris, multiple governments unanimously agreed to the adoption of a set of standards regarding both legal and technical specifications, thereby clearing a path forward so that open materials can be shared across international boundaries. George Mason University, for example, has developed an OER meta-crawler it dubbed “MOM” (Mason OER Metafinder) that allows faculty to search for open resources across a variety of disciplines and international indexes. The University of Minnesota has developed and curated the Open Textbook Library. EdTech Books provides a catalog of open textbooks that can be easily edited directly within the distribution platform, greatly simplifying the adoption and revision process.
Extended Reality Technologies
Extended reality (XR) is a comprehensive term for the environments that either blend the physical with the virtual or provide fully immersive virtual experiences. The two most common technologies are augmented reality (AR) and virtual reality (VR). Whereas AR overlays physical objects and places with virtual content, VR is typically a more immersive experience, involving manipulations of and interactions with virtual objects within an entirely virtual environment. Most commonly the immersive experiences are delivered by means of a headset, but AR often requires only a smartphone. Another kind of XR is holography, by which an object is imaged as a three-dimensional representation instead of a two-dimensional image. As a corollary, 3D printing, as the name suggests, reproduces physical objects in three dimensions using a variety of techniques and materials. Higher education is experimenting actively with XR technologies in the curriculum, and despite current hurdles (such as the cost of equipment and the effort it can take to create content), the potential for XR as a learning vehicle is high. The global higher education exploration of XR’s potential in teaching and learning already exhibits an impressively wide diversity, addressing curricular challenges and opportunities. The majority of the exemplar project descriptions mention that the institution has set up a lab or a center as the locus for initial XR explorations. These centers, either augmented makerspaces or new facilities, enable collaboration and the sharing of resources and expertise. There are also projects, such as Penn State’s immersive Experience Catalogue and North Carolina State’s VR Plants,that seek to identify and make available open XR resources for higher education. The University of Leed’s XR work in health care has not only provided hundreds of learners with the opportunity to learn skills for safe practice but also enabled work on a European Consensus Statement on guidelines for the use of immersive technologies in dental education. The University of Nevada Reno provided XR experiences to a student with cerebral palsy, which made the student feel like he was walking. The University of Waterloo created a 360 VR field trip as an equivalent for students unable to participate in a real-world 1.5-kilometer hike over uneven terrain. Gallaudet University, a school primarily for Deaf and hard-of hearing students, has been experimenting with VR to invent more efficient ways to calibrate new hearing aids.
The Horizon Report is released annually in spring. The Horizon panel employs a qualitative research method, recognising in its annual report emerging technologies and practices that are being widely applied in education, as well as the external trends shaping the current and future practice of education. The report discusses the potential impacts of technology in the field of education and their applications in teaching, learning, and creative exploration.
The previous macro trends predicted by the Horizon Report over the years reveal that these trends are not only influenced by the upgrading of technologies and higher education itself, but also from social, economic, and political factors. As stated at the beginning of the report, “Higher education doesn’t exist in a vacuum.” The Open University of China (OUC) is planning the construction of an integrated platform on a unified network that will facilitate the applications of modern information in teaching and management, including block chain, AI, big data, cloud computing, and 5G. As a new Internet+ university, the impact of emerging educational technologies on the OUC is far more apparent than regular universities. It is essential that the OUC keep up with the latest development trends and the progress of emerging educational technologies in order to advance the in-depth integration of information technology and education. To this end, the OUC Engineering Research Centre for Technology Integration and Application of E-Learning, Ministry of Education will pay attention to the Horizon Report and the development of new technologies, keep track of development trends, and continue to explore the applications of key technologies in education.
By Song Lizhe, Wei Fangfang, Wei Shunping, OUC Information Technology Department