Co-designing with Jisc

Potential tech futures for education and research

(long read alert)

How might digital technologies transform education and research by 2020-2030?

As City is looking towards the coming decade in our newly-launched Vision and Strategy, Jisc are currently engaged in a consultation process to determine how best to advise and support institutions in preparing to answer this question.

Last month a couple of us from LEaD joined a meeting at their London office, made up of representatives from across higher and further education, to add our contributions to that consultation. Taking part in this conversation not only allowed us to contribute our ideas to the overall discussion and thus play a part in what emerges from Jisc, but also to better understand the implications of how these possible futures might impact on City and therefore also prioritise our own work.

The main challenge areas under consideration were:

• The intelligent campus
• Next generation digital learning environments
• Next generation research environments
• Digital research skills
• Digital apprenticeships
• Using data for improving teaching and learning

The co-design process

Co-design, Jisc’s collaborative innovation model, is steered by member priorities and designed to both exploit new opportunities and also address pressing technology-related issues affecting higher and further education. It has led to initiatives such as the Learning Analytics programme, which City is currently investigating further involvement with. This meeting was the latest in this ongoing series of member consultations.

I took part in discussions around the intelligent campus, and with my educational technology hat on, also took note of the discussions around next generation learning environments. This blog post recounts some of the conversational snippets from those two roundtable discussions and pulls out some of the main themes.

The intelligent campus

Overview

Is there a distinction between a ‘smart’ campus or an ‘intelligent’ campus? These terms are often used interchangeably. Although Jisc has used ‘intelligent’ as part of Co-design, I’ll use ‘smart’ in this post as this was commonly used around the table, plus it seems to be gaining more wider traction amongst institutions that are already embarking on these sorts of projects. Contributions from this roundtable discussion came from both interested parties and institutions that are already embarking on ‘smart campus’ projects, including Glasgow and Lancaster Universities.

The distinction between analytics and intelligence also came up. Anadiotis (2016) on ZDNet describes the struggles that many organisations are having with digital transformations in order to become ‘data driven’. He suggests that while the notion of analytics has become both widespread and therefore fairly well understood, what artificial intelligence (AI) means and how AI can be deployed for institutional gain is elusive and still much misunderstood. He describes an evolutionary chain towards using data to provide optimal value for an organisation that runs through the following stages: descriptive, diagnostic, predictive and prescriptive.

Anadiotis’s implication is that these stages of analytics are prerequisites for the implementation of AI. What does this mean for the smart campus? Perhaps that, in order to become ‘data driven’ organisations, the Learning Analytics work that Jisc is currently doing with the sector lays the foundation for greater use of AI within higher education later on.

Much of the smart campus discourse has so far tended to have an ‘Estates’ focus, given the potential gains in areas such as meeting a sustainability agenda or more efficient management of energy and resources in an era of ever tighter budgetary constraints. However, a dedicated focus on smarter estate management means missing the equally important factor of how to intelligently enhance the estate and facilities in ways that bring the most benefit to the activities of core users – academic teaching, student learning, and research (as well as, of course, the professional services staff that support all of this).

The notion of the smart campus is such a huge area, touching on so many aspects of academic life, that it can be difficult to see how it might be narrowed down into something useful and tangible. Given that Jisc sees itself as working best in areas where no-one else is working, it was agreed that connecting smart building systems thinking and knowledge to teaching, learning and research would be a valuable role to play for providing sectoral advice and guidance as this field unfolds further.

The broader notions of horizon scanning, identifying risks, and developing a better understanding of opportunities were also important – from conducting the ‘blue sky thinking’ in order to imagine the potential to developing concrete sets of use cases that would make these ideas more tanglible. This might result in output as ‘how to’ and ‘why’ guides that included issues like the ethics of the smart campus or consderations for senior managers.

Finally, there is the possibility of reviewing and learning from other intelligent infrastructure projects and broader social trends – modern airports, smart cities, the Internet of Things, proliferation of sensors – to identify lessons that could be learned for cross-pollinating with the smart campus.

Ideas, questions and considerations

There were plenty of fascinating and challenging ideas, questions, concerns and considerations that arose during the course of the discussion. For example, might institutional chatbots be developed as new user interfaces for helping students with some of the common questions they have – where is my next lesson? what books do I need for this topic? when is my tutor free for a quick chat? Might these be utilised as push notifications to a user’s mobile device, and if so, how could concerns about location identification be addressed?

Jisc is already developing a data warehouse as part of its Learning Analytics project. Could spacial data, such as room temperature or occupancy rates, be connected with that to facilitate AI solutions for the questions posed above? An example might be where an exam hall adjusts the temperature to provide optimum conditions for sitting an exam (assuming that exams are still considered viable assessment methods on the smart campus). As broader trends in energy capture and storage technologies develop, how about using footfall in large campus spaces to be harnessed by conductive flooring and used as part of the energy mix powering local features like digital displays? If future project-based learning activities are to take place in immersive environments that are nevertheless situated on a physical campus, what is the roadmap from the lecture theatre to the learning holodeck?

As I outlined in a previous post on this topic, given the vast volumes of data that would need to be collected in order for a smart campus to function and one of the most pressing questions about such a development, how can the smart campus avoid becoming a dystopian environment – with endless harvesting of personal identifiable data, energy footprints with a voracious appetite, and hackable buildings with no private space?

Our table essentially concluded that, given the vast range of questions and challenges in this area, easily definable output for Jisc on this subject would be difficult to produce within the next three months, but refining the ideas further into potential use cases could be a useful way forward.

Next generation learning environments

Another nearby group held a discussion on what the next generation of digital learning envionments should do. As with City, many of the people in the room represented institutions that also used Moodle or a similar virtual learning environment (VLE). Some very interesting ideas also emerged from them, and they tended to be more concrete that the smart campus ones. It was agreed for starters that any next gen VLE needed to (obviously) meet pedagogic needs, strongly support the BYOD (bring your own device) approach, and improve on current accessibility factors.

Their discussion started with looking at two ideas that gained traction during the initial consultation – the ‘pop-up VLE’ (lightweight tools that could be deployed at small and potentially time-limited scales) and connecting institutional technologies and user-owned tools, along the lines of the If This Then That (IFTTT) tool used on the social web for connecting different services together. An ‘IFTTT for education’ emerged as the frontrunner idea from their discussion.

IFTTT works by the creation of ‘recipes’ that enable certain channels to be connected with each other. For example, if a new blog post is published on Learning at City, then a tweet is published at @CityUniLEaD with the title and URL of that post. In an educational context, this might work (for example) as if a student publishes a post in a module reflection blog, then a copy of it gets pushed to the student’s e-portfolio. A new tool such as this might start with a class-based teaching and learning focus, then could be connected to an institution’s Educational Strategy, perhaps with ‘recipes’ routing via a Learning Analytics service.

This discussion raised a broader recognition of a space between institutions, educational technologies, technology vendors, and social media. A means of connecting these disparate systems together, most likely via open APIs. It was also hoped that in doing this, a space could be provided that might allow new pedagogies to emerge. The group envisioned that institutions would maintain VLEs as they currently use them, but that open APIs would enable greater access to them for content to flow in and out. It might even lead to greater take up of the VLE within institutions.

Having completed their discussion with a more concrete set of outcomes than our ‘smart campus’ table, they suggested that Jisc would start looking for institutions that would be willing to trial a proof of concept of this vision of the next generation learning environment.

I suspect that this may well come to fruition and wider adaption much faster than the smart campus.

Wrap up

This blog post from Jisc provides a far more succinct summary of the meeting than mine here, and sets the scene for what might come next.

So, over to you. Does the smart/intelligent campus sound like a place you’d love to work or study in, or does the idea leave you cold? If you’re broadly in favour of the idea, what ideas would you like to see in a data-driven campus that makes integrated use of artificial intelligence, Internet of Things technologies, and a profusion of sensors? What would be your main concerns about such an environment?

What about an ‘IFTTT for education’? If there such a feature integrated with City’s Moodle, what tools would you like to see connecting with it? What educational uses would you make of being able to easily connect the ‘walled garden’ of the campus VLE with the wildness and diversity of the social web, or the broader range of digital tools available to people than institutional provision?