The higher education edition of New Media Consortium (NMC)’s Horizon Report is an authoritative forecast report.

Often referred to as “the prophecy”, Horizon Report predicts new trends in the development of education and science and technology over the next five years, as well as the future challenges facing education and science and technology. In its previous reports, Horizon Report has repeatedly made accurate predictions. Its predictions about the accelerating integration of technologies such as social networking services, cloud computing, Internet of Things, open content, mobile devices, flipped classrooms and 3D printing have been realised or put into operation in higher education in recent years.

Which technologies does the 2016 higher education edition of Horizon Report predict? What types of technology will universities and colleges adopt in the future?

Medical university students applying virtual reality technology in an anatomy class

A robot teacher gives a class

Near-term technologies (time before adoption: approximately one year)

Bring Your Own Device

It is no longer unusual for students to bring their own smart devices into the teaching and learning environment, a phenomenon that has been predicted by Horizon Report many times. However, many universities currently treat smart devices with indifference, and domestic colleges and universities in China still prohibit their students from using mobile phones in class to avoid distraction. There is still a long way to go before students’ own devices are used effectively in teaching.

The intelligent teaching assistant is a lightweight application, making it easy for university teachers to achieve functions such as taking class attendance, testing, setting questions, and grouping. Even in a large class with hundreds of students, students can no longer hide in the background. They need to enter a code to sign in, complete in-class quizzes, participate in group discussions, and focus on answering random questions from teachers. They can also compete to answer questions first and be entered into lucky draws.

Learning analysis and adaptive learning

Learning analysis is the process of collecting and analysing the details of each individual student’s interactions with online learning activities. The goal is to develop better teaching methods, encourage students to learn actively, and identify student groups with learning difficulties, and also to assess the factors affecting academic performance and success. Adaptive learning technology applies software and online platforms in the analysis of learning and makes adjustments for each individual student.

Mid-term technologies (time before adoption: two to three years)

Augmented reality and virtual reality

Augmented reality and virtual reality have been hot topics over the past two years. Augmented reality has appeared in Horizon Report’s forecasts. Augmented reality is characterised by the infusion of digital information, including images, videos and sounds, into real-world spaces. Meanwhile, virtual reality can bring users into an immersive alternative world through computer simulations, creating a sensory experience. How can these technologies be applied in the field of higher education? Some reports have noted that these technologies can provide students with a picture of a future workplace so that they can benefit from learning and entrepreneurship training in the field of science and engineering. Technologies like these can also change medical education by simulating surgical operations in a virtual reality environment.


Makerspaces are an informal work environment providing users with a space for creativity and experimentation. Some universities create their own makerspaces to provide students with innovative and entrepreneurial opportunities. Through practical design and implementation, students can solve problems creatively and engage in deep thinking. A makerspace is often equipped with advanced equipment such as 3D printers and laser cutting machines. However, it should be noted that the concept of the makerspace is not just a collection of technology; rather, it emphasises learning by doing.

Long-term technologies (time before adoption: four to five years)

Affective computing

Affective computing refers to devices with the means to recognise, interpret, process, and simulate human emotions. How can this be applied in higher education? Taking Massachusetts Institute of Technology (MIT) as an example, MIT’s affective computing group focuses on emotion detection, using wearable sensors to measure the pressure people feel, in order to conduct pressure appraisals for students with strict time schedules and heavy learning burdens.

Robotics is not new, but its range is very wide. In the fields of teaching, learning and innovation, robotics may play the role of learning companion, virtual assistant or teaching aid.

Extended reading

Technologies will not only enter into colleges and universities, but also drive self-study examinations into a new era.

A series of explorations of new media, educational big data and learning analysis, MOOCs, micro courses and open classes, sensor technology, virtual reality, live broadcasting and so on, have created unprecedented new learning tendencies.

Educational training institutions have begun to explore the behaviours of integrating teaching and learning on technical platforms in order to reconstruct the relationship between teaching and learning. Lv Kai, COO of Suntech Agency, a famous Chinese self-taught examination training institution, stated that Suntech has established its own technical team to turn the knowledge system into PC software in order to collect learning data via the online classroom, the question bank, and the personal dashboard. The data will include students’ level of understanding of the knowledge points and their problems. Even during a live explanation of a knowledge point, whether a student stops watching or repeats watching, as well as whether they take notes or not, will be clearly displayed and measured. An automatic teaching service was eventually implemented based on an inductive analysis of the data. Each of the students’ knowledge loopholes will be automatically matched to the corresponding knowledge points, and special assignments will be provided to help the student learn targeted knowledge effectively. Furthermore, mass data from the analysis of the learning behaviours of students will also be summarised and submitted to the class teacher so they can adjust their teaching methods and points of emphasis in real time. This has truly realised the daily iteration and update of course products and lectures.

Furthermore, in response to the rise of mobile devices, Suntech’s mobile apps include daily and monthly reminders for upcoming courses so that, after logging into the app, students can find out their learning progress and the courses available that day, and select a past date to replay the courses. Lv Kai, COO of Suntech, pointed out that mobile apps greatly increased the convenience of learning. Students can finish all procedures including attending a lecture, reviewing, doing exercises, and homework. Teachers can follow the students’ learning progress on their phone, summarise wrong questions, and explain frequently misunderstood knowledge points.

By Beijing Daily

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