Digital transformation strategies should maximise use of AI

However, the use of AI across UK campuses is not yet widespread. Only a handful of colleges and universities are using it to reduce staff workload, drive efficiencies in business operations and support learning.

But students enrolled at these early-adopter institutions are surely at an advantage: they will leave education with the kind of digital know-how and experience employers want.

There’s much education leaders and curriculum designers can learn from cutting-edge businesses that utilise AI and other advanced technologies of the fourth industrial revolution – or industry 4.0.

On the back of a successful visit in March to one such business – Siemens – we took a cohort of 11 further and higher education leaders to Amazon’s London headquarters in May. We heard about its vision for AI in organisations and its range of services that use AI and machine learning in education, see below.

Text description for Amazon's machine learning graphic

©Amazon via Amazon

A central circle features the words 'student journey' surrounded by services plotted against the different stages:

Applicants

Marketing & recruiting: customer segmentation, advertising optimisation, personalisation
Admissions and enrollment: optimise student mix, predict acceptance, forecast enrollment

Students

Learning content & personalisation: accessibility, localisation, metadata, course recommendations, personalised learning content
Student success & retention: identify at risk students, prevent churn, optimise advice and support

Lifelong learners

Research: leverage cloud to harness machine learning to accelerate research and drive discovery
Continual improvement: leverage data to generate predictions and insights across the enterprise

Amazon reckons that, ultimately, machine learning can “improve student outcomes and enable rapid modernisation”.

Like Jisc, it recognises that, because of the pandemic, education providers have adapted and must continue to adapt to rapid change. In part down to the rise of online and blended learning, change is also motivated by financial pressures that have, in turn, forced providers to innovate.

Machine learning, says Amazon, is powering this shift with high-quality data at its heart.

Admissions and learning

Amazon showed the HE and FE visitors how AI predictions can support marketing and planning for admissions. For example, it can help identify and group possible new students, personalise advertising to those groups and predict acceptance rates.

Once enrolled, AI technology can play a role in widening access to the learning process, for example translating text to speech and vice versa, which helps visually impaired students and those who are deaf or hard of hearing.

Using metadata extracted from learning content and digital collections, AI enables accurate content classification and search functions, which in turn support personalised learning, such as suggesting content for individuals.

Particularly for colleges, which have a duty of care around safeguarding, AI is in use to detect and moderate inappropriate content.

Student support

Many colleges and universities already use learning analytics platforms for multiple purposes. They keep track of attendance, progress and performance and provide all this information in one place to teachers and lecturers.

Vitally, these systems can identify at-risk students: when the system spots anomalies in patterns of attendance behavior or a dip in grades, for example, learning analytics systems can (with consent) be configured to automatically alert a form tutor.

A timely human intervention can then be made to check whether an individual student requires extra support. The system could also send advice to at-risk students, or supportive information, such as links to the organisation’s wellbeing services. All these interventions could reduce drop-out rates and potentially catch mental health issues early.

Beyond this, chatbots and digital assistants can also give meaningful support and reduce the need for staff to be available to answer common questions. Jisc’s national centre for AI in tertiary education is piloting a chatbot, based on Bolton College’s pioneering chatbot called Ada.

Ada provides students with answers to various questions about the college, including personalised responses related to timetables and grades. Meanwhile, Leeds Beckett University has a chatbot that navigates students through the clearing process.

Marking and feedback

AI is reducing workloads in other ways too, giving educational staff more time to spend with their students. AI-assisted marking software, for example, is going beyond what has previously been possible with multiple-choice software.

It’s becoming possible to use machine learning to provide detailed feedback and support, which can help students with their assignments.

Meanwhile, adaptive learning platforms that use AI in a similar way to music and TV/film platforms can recommend content or topics based on what it thinks students would benefit from learning.

From a student perspective, this translates to more learning opportunities and intensive support during times when a tutor isn’t available. From an educator’s perspective, it provides detailed insights into students’ strengths and areas for improvement - insights which they can use to tailor teaching.

Further information

The national centre for AI in tertiary education is working to accelerate the adoption of AI tools across the sector
To help members make good decisions around AI, Jisc has published a guidance document, ‘A pathway to responsible, ethical AI’
Jisc’s digital strategy review service can support leaders’ future planning