Higher education is changing in terms of both teaching and research. More and more courses are being delivered online. According to Class Central, in 2018, there were 11,400 massive open online courses (MOOCs) offered by more than 900 universities delivering these courses to 101m students. Students’ assessments are submitted and graded online, and online platforms have transformed tutor–student communication.
Universities are setting their 2030 strategies with a strong focus on innovation, inclusion, diversity and excellence. However, one of the main accelerating external megatrends that is affecting higher education is technological change, which universities are having to respond to and embrace. These changes are pushing universities and higher education institutions towards offering academic programmes that are more relevant to students, personalised, affordable and flexible. New and innovative technologies will play an important role in implementing these strategies. The effects of this megatrend extend beyond teaching and learning; they are also expected to have a strong impact on research.
Artificial intelligence (AI) and robotics are among the most advanced and promising technologies that are expected to be used extensively in different industries. According to the International Federation of Robotics (IFR), the number of industrial robots worldwide is predicted to double by 2020, reaching a total of three million. These technologies might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation.
Job automation will affect roles in almost every industry, especially jobs that do not require a high education level. According to PricewaterhouseCoopers, three waves of automation are associated with the use of AI. First, the algorithmic wave, in the early 2020s, which will involve the automation of simple computational tasks and structured data analysis. Second, the augmentation wave, up to the late 2020s, which includes robotic tasks in semi-controlled environments. Third, the autonomous wave, up to the mid-2030s, during which we expect to see automated physical labour and problem-solving in dynamic real-world situations that require responsive actions.
We expect the potential level of job automation in the education industry to reach a higher level of maturity. We should prepare for a new era in higher education, in which AI and robotics will do some of the major tasks, and some roles will either be automated or see major changes in scope, revolutionising the industry. Universities are still at the early stages of adopting AI and robotics. In China and Germany, the first robot lecturers have recently been introduced. Although some students indicated that improvement is required, the experiment showed that there is potential for this technology to undertake some teaching tasks in the future.
AI will profoundly transform education. It will help to identify new forms of personalised learning that can support academics and tackle education challenges. These new forms of personalised learning for students will be tailored to their abilities and learning styles, revolutionising the student learning experience and changing academic job descriptions extensively. We can expect these technologies to carry out some of the core tasks in teaching and learning, including assisting academics in classroom teaching; designing and developing assessments; grading assessments; developing curriculum and degree programmes; and identifying gaps and areas for improvement in learning programmes. They may also develop more personalised learning plans to cater for students with different abilities and learning styles, including those with learning difficulties and disabilities. Moreover, learning analytics can be used to manage MOOCs more effectively by understanding and predicting students’ behaviour. We can expect the student learning experience to improve significantly. This fits well with the targets for inclusion, diversity, flexibility and excellence that universities have set as part of their 2030 strategies.
What might doing research be like in the 2030s?
We expect robots and AI to revolutionise teaching and learning in higher education during the 2030s, and research is no exception. As these technologies mature, they will change the shape of science. Open science will take off, aided by AI-enabled technologies and opening doors to new scientific discoveries. According to the Research Futures 2019 report, AI will give researchers a pool of data that can be analysed at high speed ready for use, which means that hypotheses will be data-driven. AI is also expected to improve the peer review process by checking that manuscripts are logical and comply with editorial standards for target journals. The issues of open-access research and sources of funding, which have been in debate for many years, are also expected to be less of a problem Hence, we can expect the speed and volume of research to increase massively with the integration of AI and big data analytics. Countries may experience this at different rates, however, as some are more focused on AI than others. For example, China is stepping up its funding and production of research. It is also a pioneering country in research on AI and robotics. On the other hand, the UK, which is known for its research excellence, is expected to experience a major shift in research as collaborations with foreign researchers may be decreased after Brexit. This may impact how advanced AI is used in research in the UK.
Can these technologies make academics redundant?
One of the issues around the use of AI in higher education is cyber security. The education industry ranks in the UK economy’s top ten for volume of data stored. With the use of AI, robotics and other advanced technologies, the volume of information that is stored about students will increase at an accelerating rate, thus introducing new and more sophisticated cyberthreats. AI is an excellent tool for improving life and education, and it is expected to be a good tool for improving cyber security, but it can also teach machines to carry out cyberattacks. Hence, AI could be one of the biggest threats to cyber security in education.
AI and related technologies have already outperformed humans in many areas, and their capabilities will improve further. However, despite the rapid advancements of these technologies, it will be hard to fully automate the role of university academics in the near future, as wisdom and the ability to inspire a new generation of students are important parts of the job. Human interaction – more specifically, tutor–student interaction – is extremely complex, ambiguous and subjective. In addition, at the heart of the academic’s role is the ability to inspire new generations to be the best they can be and to build a better, more optimistic future. While AI can advance emotions (such as empathy) in robotics, it is difficult to automate these aspects of the academic’s role, which require a human touch. Nevertheless, we must expect major changes to academic job descriptions and specifications.
Dr Nisreen Ameen is a lecturer in Information Technology Management at the School of Electronic Engineering and Computer Science at Queen Mary, University of London.
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