Technology sometimes makes people’s lives more impersonal. But in higher education it is leading in the other direction, as large group lectures are replaced with tutorials, digital resources and software-based coaching.
“We believe the technologies that are coming will reinvent higher education teaching,” says Paul Feldman, chief executive of Jisc, a membership organization that provides digital solutions for UK education and research. “We think it will turn the whole thing on its head.”
The key idea is that technology will release staff to spend more time teaching one-to-one or in small groups. “Blended learning,” wherein online resources such as on-demand videos support face-to-face teaching, is already common. The University of Northampton, which follows this approach, has no large lecture theaters in its new Waterside campus — the largest room can hold 80 people, with others averaging 40.
Five years ago the University of Leeds introduced a lecture-capture system and now approximately 80% of its lectures are recorded, either as audio and slides or as video. Professor Neil Morris, the university’s dean of digital education, says staff can repackage these recordings within online resources, combining sections of a lecture with added activities. This allows students to learn at their own pace, an approach known as “flipped learning” that gives contact time to focus on discussion and interaction. “When you come to class, we’ll do some problem-solving,” he says.
There are further developments in the pipeline. Several universities are experimenting with chatbots, which answer general questions, and others have systems that use data to identify students who are disengaging from courses. Jisc is working on how similar technology can support students’ mental health.
The next few years will see advanced learning analytics systems that combine chatbot-style interaction with extensive analysis of students’ personal data, using artificial intelligence (AI) technology that crunches large volumes of information to suggest what learning tools might work for individuals. Rather than identifying a few students who need particular support, these systems would be used by most or all.
Martin Hamilton, a futurist at Jisc, says that learning analytics could provide personalized support and advice, such as Amazon-style personalized recommendations on further reading and activities. He adds that there are questions over how personal data is used and analyzed, but if these can be answered, students could get much better support than they do at present. “With a couple of hundred undergraduates in a cohort, you don’t sit down with them for very long,” he says. “Can we use AI to give the lecturer superpowers?”
Feldman adds that such systems could engage with students without waiting to be asked questions, unlike today’s chatbots. “It’s a helping hand for students and staff,” he says. “You could think of it as a virtual coach or personal tutor supporting the lecturer, and as it evolves, the bot becomes proactive, guiding the student to meet his or her goals.”
The University of Leeds is working to join up the data it already gathers on students, but Morris thinks learning analytics systems will need to be used with care. This is partly to protect privacy and personal data, but also because data will only ever provide a partial picture of each student. “We’re looking at using data to inform a conversation,” he says. “This is never going to be a data-driven process.”
Care will also be needed over how students use learning-analytics systems, for example if data showed them they were in the bottom quarter of their group. “We are very concerned about presenting this data in a way that is supportive, nuanced and contextualized,” says Morris. There is also a risk of students’ uncritically following recommendations generated through AI, which are based on probabilities derived from data rather than human intelligence. “The role of universities is going to change. We’ve got to help our students to think more, be more independent, be more understanding of the benefits and limitations of digital technology,” he says.
As well as teaching, technology could improve the assessment process by spreading it throughout courses, reducing the need for final exams and the stress and workload associated with them. Taking a leaf from today’s plagiarism-detection systems, software could carry out preliminary marking of essays to see if key facts have been mentioned, freeing up staff to make more sophisticated assessments and give more detailed feedback. Some types of assessment, such as whether someone can carry out a defined task, could be entirely computer-assessed. This could allow students to practice until they have mastered key concepts, at which point they can gain a credit.
Greater use of digitized material and online meetings should also allow students to collaborate with and take courses at other institutions. Morris says this could lead to “unbundled universities,” with a blurring between those learning on campus and those working remotely, where both can gain qualifications by building up credits from a range of institutions. “I wouldn’t go as far as to say the degree is dead, but I do think that employers are pushing quite hard, saying we are not interested in the sum, we are interested in the individual component courses,” he says.
Technology-enabled changes in higher education are likely to have other benefits for employers and for graduates seeking work. “The jobs of tomorrow are going to be much more about analysis, assessment and interpersonal skills, and less about recall and pattern recognition,” says Feldman.
And although remote digital access is improving as an option, the increasing focus on personal tuition, group interaction and personal development will still provide a strong justification for younger students to attend universities and colleges. Developing interpersonal skills and adult independence is something students do best together, Feldman says: “You are not going to get that maturing online.”