The promising vaccine news is making bosses think about the return to work. But when it does happen, the office won’t ever be the same again.
I had a good discussion on Tuesday about the future university campus. I have worked on an intelligent campus project in the past, back then we had a vision. However the current landscape has changed and will continue to change. This has implications for campus planning and usage.
Wednesday saw the publication by the Government of guidance for universities on students returning in the spring.
Apologies I am on leave today, I will be unable to respond to any questions or requests on Twitter. I will not be posting pictures of my breakfast either. I will send replies and retweet interesting stuff tomorrow when I am back on the Twitter.
Friday was a full day of meetings and events. I actually have very few days where I spend most of the day in Zoom and Teams meetings, but today I had nearly six hours of online meetings. The key for me was to move away from the computer when I can.
A lot of news over the weekend on grade inflation. I was at an event last November where this was discussed and there was some despair about the issue, on one hand everyone is expecting the quality of teaching to be better, but at the same time they don’t want students to get better grades.
I spent a fair amount of time writing some proposals this week.
We’ve also been working on where Jisc goes next with Learning and teaching reimagined following the publication of the most recent report.
This report is the result of a five-month higher education initiative to understand the response to COVID-19 and explore the future of digital learning and teaching.
As the directorate I am now in is responsible for moving things forward, the key issue is how we move from a series of challenges and recommendations to a plan for change and transformation. We have a vision, we know where we are, it’s less about where we want to be, much more about how do we get there, what do we need to do to make it happen.
@jamesclay is taking us through the ethical issues of using student data & analytics. Privacy & consent is so important. Consent of the processing of data and what we do with it. Can we understand how data tells us story? how does this lead to action if any? #UHLTC2020pic.twitter.com/FSqbmj8SOF
So what do we mean by a learning space and how is an intelligent learning space different? What is a smart learning space?
As we design learning spaces, we can add sensors and mechanisms to collect data on the use of those learning spaces. It then how we analyse and use that data that allows those spaces to be initially smart and then intelligent.
Generally most learning spaces are static spaces designed to allow for particular kinds of learning. Some have an element of flexibility allowing for different kinds of learning activity within the same space.
We have seen lecture theatres where the seats can swivel to allow for discussion and group work. There are other lecture spaces where the students are seated in groups around a table, allowing them to see the front of the room and work together. New active learning spaces allow students to work independently or in groups, but the use of large screens on the table allows for whole group teaching or lecturing.
Often the pedagogy is shoe-horned into the space that is available and even if more appropriate spaces are available on campus, often they are unavailable for that particular slot or cohort.
In the past room utilisation was often a combination of what was in the timetable and what could be seen during a survey (often with a clipboard).
There is some technology already in place which can start us on the road to making better-informed decisions about how best to use space – sensors, for example. We all know when lighting is linked to a movement sensor because everything goes dark when we sit still for too long, promoting much frantic arm-waving to turn the lights back on.
But a smart learning space goes further than such simple actions and allows us to gather data about the spaces and, importantly, act on that data. We can turn down heating in rooms which aren’t being used, and some systems will take into account the external temperature, humidity and pollution levels, and not just the time of year.
We can use electronic entry systems, such as swipe cards, to ensure the security of the rooms, but also to measure room occupancy. We can also ensure that the lighting, heating and CO2 levels are within defined parameters.
If you then throw in data from the timetabling system, the curriculum, lesson planning, teacher commentary and feedback, student feedback. You then start to get a wealth of data that could be analysed and used to design and enhance the learning activities which will take place in that learning space.
A smart learning space would taken into account historical usage of the room and how people felt that the space either contributed or hindered the learning taking place there. You can imagine how users of the room could add to a dataset about the activities taking place in the room and how they felt it went.
Of course there is a challenge with historical data in terms of bias, errors and legacy processes. You can imagine that if a space, regardless of what it had been designed to be, was only used for lectures, then the historical data would imply that the space was only ideal for lectures. Bringing in more datasets would help alleviate that issue and ensure any assumptions about the space had some element of validity.
You would think that data from the timetable could allow for this automatically, but timetabling data tells us about the cohort, the course they are on and the academic leading the session, most timetabling software doesn’t have the granular activity data in it. What will be happening in that session, not only what was planned, but also what actually did happen.
The course module information may have the plans of the activity data within it, but may not have the room data from the timetable, nor may it have cohort details. You could easily imagine that some cohorts may be quite happy with undertaking group activities in a lecture theatre space, but there may be other cohorts of students who would work more effectively if the space was better at facilitating the proposed learning activity.
Likewise when it comes to adding feedback about the session, where does that live? What dataset contains that data?
Then there are environmental conditions such as heat, temperature, humidity, CO2 levels, which can also impact on the learning process.
So an actual smart learning space would be able to access data about the session from multiple sources and build a picture of what kinds of learning spaces work best for different kinds of learning activities, taking into account factors such as cohort, environmental conditions, the academic leading the session and so on…
These datasets could also be used to inform future space planning and new builds, but smart learning spaces are only the beginning. Taking a smart space and making it intelligent is an obvious next step.
An intelligent learning space would take this data, and then start to make suggestions based on the data. It would identify possible issues with the learning plan and make recommendations to either change the learning activities planned, or recommend a more appropriate space. An intelligent learning space would adjust the environmental conditions to suit the activities planned for that spaces, rather than users of the space having to manually adjust the conditions when it becomes too cold, too hot, too bright, stuffy, etc….
An intelligent learning space could take data from a range of sources, not just the physical aspects of the space and how it is being used, but also the data from digital systems such as attendance records, the virtual learning environment, the library, student records, electronic point-of-sale and online services.
This joined-up approach can provide insights into the student experience that we would otherwise miss. These insights can inform and support decision-making by individuals across the campus, including students, academic and professional service staff. By using live and dynamic data, decisions can be made that are based on the current state of the different learning spaces across the campus.
Making the timetabling software intelligent, well at least dynamic, could mean that learning spaces are not allocated to cohorts of students for a set amount of time, but learning spaces are allocated based on pedagogical need and student need and done as and when needed.
One of the key issues with all this is to collect and store the data somewhere, a centralised hub or data lake would be critical.
I have decided to take next week as leave, not that we’re going anywhere, but apart from the odd long weekend (bank holidays) I’ve not had any time off working since the lockdown started, actually I don’t think I’ve had leave since Christmas! I had planned to take some time off at Easter and go to London for a few days, as we had tickets for the Only Fools and Horses musical at the Royal Haymarket. I had bought tickets for my wife as a Christmas present and it was something we were all looking forward to. Then all this lockdown happened and the theatre cancelled all the performances as required by the Government.
I did consider keeping my leave, but with leading a taskforce, it was apparent that I might not have the time to take some (and where would I go).
So this week I was winding down slightly as I wanted to ensure I had done everything that people needed before I was off.
I published a blog post over the weekend about making the transition to online and to not make the assumption that though there are similarities in delivering learning in classrooms and online, they are not the same.
If we are to make the move a combination of online, hybrid and blended than we need to ensure that the staff involved in the delivery of learning have the right capabilities and skills to deliver effectively online.
For a few years at Jisc I was working on the Intelligent Campus project and then got a new role as Head of HE and Student Experience. I still have an interest in the space and when I read this recent post from WonkHE, Can we plan for a socially distanced campus? interesting and useful for the planning for September.
We know how to operate a traditional on-campus model, and we are very quickly developing a better understanding of how to facilitate off-campus working and learning, but how can we best support social distancing on a functioning campus?
Is this what social distancing looks like in a lecture theatre? via WonkHE Seminar.
I was reflecting how if the concept of the intelligent campus was further advanced than it is, how potentially helpful it could be to support universities planning for a socially distanced campus.
I published a use case a year ago, on people flows and congestion,and it gave me an idea of updating it to reflect the current challenges that universities and colleges will face in September.
With the impact of the coronavirus and the need for social distancing and tracing contacts, if there was ever a use case for the concept of the intelligent campus then this is it.
What’s the issue?
The flow of people through campus and beyond is complex and not well understood outside of known peak times such as class changes or lunchtime. The density of people at any one place and time, and the speed of their movement, can have a big impact on how easily people can get in and around campus buildings and facilities. This can have an impact on the need for effective social distancing. Universities need to avoid situations arising which result in large numbers of people congregating in areas which could result in failure to maintain social distancing.
What could be done?
Pedestrian flow could affect the time for journeys between classes, waiting times at cafes or sudden changes in how busy the library is. Location trackers such as used by mobile phones can provide data on flow, and also people counters, such as using video systems, can be placed around campus to collect data on the numbers of people in that location at any time. Such data can have a number of applications, including combining with other contexts to improve services, as well as ensure social distancing.
Monitoring the increasing numbers of people towards a known destination could anticipate potential problems with congestion and queueing. For example, students heading towards the cafeteria could indicate an unusually high demand for food and trigger staffing or stocking changes to cope with higher numbers. You could also use the information to alert students that the space will be busier than normal and due to social distancing there would be longer queues and waiting times.
Timetabling data indicates when classes are scheduled to end, but real time data on movement could indicate that some classes finish earlier or later, leading to changing patterns in availability of services. This could be critical if you are using timetables to stagger the movement of people to ensure social distancing and avoid congesting and crowding.
Usage data could show that the library is already busy when one class ends, and students could be directed towards other study areas or computer rooms that have more availability and more space.
Where campuses interact with local towns and cities, for example crossing roads or using transport services, or where students are using their cars. The changing flow of people could be used to increase the capacity or timing of pedestrian crossings, to avoid congestion. Likewise thefrequency of transport services could ensure that sufficient public transport is in place for both local people and students. Real time traffic information could allow students to make decisions about when to arrive for university on time or when would be the best time to leave.
Over time the data may suggest interesting patterns of behaviour that could be used to further predict, anticipate and respond to congestion. One example might be the impact of weather – on sunny days students may spend more time outside, whereas when it’s rainy they may congregate in specific spaces. This behaviour will impact on those trying to ensure social distancing in spaces such as corridors and learning spaces such as the library.
Using room utilisation data, spare rooms could be opened up to accommodate social interaction and refreshment breaks, or pop up library or IT services could be opened. Ensuring that social distancing guidelines are kept to.
What examples are there?
Many of the existing examples are from “Smart cities”, involving vehicular and pedestrian traffic, to aid safety, improve health and environmental concerns, and also inform retail and business. However, such applications can be easily applied to campus routes and facilities.
Google maps is one of the best known examples of tracking the location of mobile devices (typically in cars) to show congestion on traffic routes. The mapping service then can suggest the best/quickest route for the traffic conditions at the time and provide alternatives if congestion is estimated to lead to a slower journey time. Waze (owned by Google) does something similar, but allows individuals to add information about congestion. This type of system could be really useful in a campus context.
Other methods of “people counting” include video cameras, which can also combine with CCTV, recognising an image of a person and transmitting the numbers (usually not the images). Such systems could be used to flag spaces which are getting congested or filling up.
In Las Vegas, not only do they track vehicles through a junction but also count the number of pedestrians crossing the streets and also “jaywalking”, and then re-routing vehicular traffic when the numbers of pedestrians is high. Could a similar system ensure that students are re-routed when their chosen route is getting crowded.
People counters are often used in business and retail areas for example in Manchester to better understand queuing time and which areas of a store are popular. The data also contributes to strategies to improve walkability and transport, understand the impact of events and marketing campaigns, and assist businesses and community services in adopting appropriate staffing and security arrangements. These systems could be adapted to ensure safe spaces for students on university campuses.
What about ethical and other issues?
In principle, data on people movement tends to be aggregated to use the total numbers and changes to those numbers rather than knowledge about a specific individual. This is similar to the way google uses your location to provide mapping data, and is widely accepted. However, images of individuals may be being captured along with their movements and this information could be used inappropriately without strict controls and clear consent rules. Similarly, as data becomes combined, it begins to create a picture of a person’s behaviour that could be considered more of an invasion of privacy – for example which cafe are they going to, who else is there and what do they drink?
It’s important that the ethical aspects of this are taken seriously, and the excuse “it’s a crisis” shouldn’t be used to increase surveillance of individuals and impact negatively on privacy. Transparency of what the university is doing and why is key.
With the impact of the coronavirus and the need for social distancing and tracing contacts, if there was ever a use case for the concept of the intelligent campus then this is it.
For me Monday was very much thinking about how HE will need to plan for the unknown for the Autumn.
The BBC reported on how students would still need to pay full tuition fees.
University students in England will still have to pay full tuition fees even if their courses are taught online in the autumn, the government has said.
We know many universities are planning for either full online degree programmes or hybrid programmes, but also that many are planning for potential coronavirus second (or even third) wave of infections and subsequent lockdowns.
It got me thinking about how this looks from a prospective student perspective, and the impact on those universities which are reliant on local (and commuting) students and those for whom it’s a place where students travel to study there.
We already have an understanding of the impact of the massive fall in the international student market on some universities, but the domestic situation is still highly volatile and unknown. Some surveys say 5% of prospective students have already decided not to go to university this autumn, and another 20% who are changing their plans. If we see a loosening of lockdown measures between now and September, then maybe fewer will change their plans, but we could see lockdown come back and enforced more stringently; this will of course impact on those prospective student plans.
It doesn’t always work, and it doesn’t always work the way you expected. Here are some of the strategies I have used in creating, building, developing and maintaining a community.
Recently I have been talking with others about community and building communities, something I have done in the past with some success (and sometimes not so much success). I don’t believe there is any one way to build a community, but in a similar way I don’t think doing one thing such as a mailing list, or an event, or a Twitter hashtag will result in a community. I have found you need to do a range of things, as some stuff works for some people and other stuff works for others.
In this blog post I will discuss some of the ways in which I have had to build communities as part of my professional practice. Though the communities were different, there were some key things that I did to build those communities. Also there are some aspects that were features of all these communities
What is a community? Why do you want to build a community? Who will be part of your community and why would they want to be part of your community?
Its also worthwhile thinking about the life of the community, is this an ad hoc pop-up community, or are you trying to establish a more permanent community.
In this context it is worthwhile to write down the vision for the community, what is it you are trying to achieve through the community. It is also useful to establish some objectives as well. Over time you can re-visit these, but having them written down does help in the process of building a community and determining if you are being successful or not.
Back in 2008 or so, when I was a MoLeNET Mentor working with people such as Lilian Soon, Dave Sugden and Ron Mitchell (and others) I was helping to build a community of FE people interested in mobile learning. We wanted to start a community as part of the MoLeNET programme, but did not expect that we would continue to support the community beyond the life of the MoLeNET programme. This doesn’t mean that the community wouldn’t or couldn’t continue, but as part of the planning, this wasn’t a key objective. The funding was planned for three years, so we expected the community to be around for that length of time.
Whereas when I was building the Jisc Intelligent Campus community, I wanted this to last as long as Jisc was working in this space, so it was important to think about both the short term objectives, but also the longer term objectives as well.
When starting to build the community, it’s useful to lay the foundations for that community. What tools are you going to use, what services will you be using and how do you expect others to use those tools.
The sort of things I did for the MoLeNET community included using tools such as Jaiku (and then the Twitter) to use micro-blogging to connect and communicate. We also did online webinars, which were interesting and fun to do. We did a lot of podcasting as well. Another thing we did was blogging. Those were in the main broadcast mechanisms, we also used e-mail to tell people in the community what was happening and what they could do.
For engagement we ran workshops and events. It wasn’t just one kind of event either, there were workshops, as well as conferences and meetings. The key I think was about connecting, communicating and sharing. What was challenging at the time (well it was 2008) was building online engagement and discussion. Today that might be easier.
I did a similar thing when I started to build the Intelligent Campus community. I started off using Twitter in the main, using a hashtag #IntelligentCampus to connect what I was saying. I posted relevant and interesting links (well I thought they were interesting) to Twitter as well. I also blogged a lot, sometimes it was about what the project was doing, but I also blogged about stuff other people were doing. These posts were shared on Twitter, but also through an embryonic mailing list, well people still like e-mail. I made a point too of posting a monthly digest to the mailing list. I also ran community events where as well as me presenting, I also got members of the community to present as well.
Another thing is to attend other events and present, something I did for both MoLeNET and the Intelligent Campus. This enables you to introduce the community to others and hopefully get them to join and engage with the community.
There are various tools and services in any community toolbox that can be used to build, develop and maintain a community. Thinking about the different stages of building a community is also critical to successfully building a community.
When you start, you have no community, you need to bring together people who have an interest in this space. Building a community is hard, so now I use a range of tools, such as social media (well in the main Twitter), also mailing lists and for me blogging. Interesting and useful blog posts can engage people and get them to participate in the community. It also acts as a way of helping people to understand what the community is about and what they will get from the community.
Communities don’t just grow, they need to be cared for and nurtured. This means you need to plan to bring people onboard to the community. This doesn’t need to be done alone, as you start to build a community you will meet others, and using their expertise and knowledge can help. Get others to write blog posts for you, as well as using the Twitter hashtag for example.
Maintaining a community is an important task. As I mentioned sending regular digests of news and links was one thing I did for the Intelligent Campus community, but also posting questions to the mailing lists to stimulate discussion (when things were quiet on the list). When I was running the Digital Capability project at Jisc, I would write regular blog posts about digital capability, but would also present on the subject at external events.
For me the success of the communities was when I became less important and was less of a focus for the community and others started to put themselves forward. They were posting stuff on the Twitter, publishing their own blog posts and even running their own events.
Determining the success of your community enables you to decide if you should continue or let the community die. Do you want to put metrics on your activities for example? For some of my communities measuring activity was important, so I did look at data and analytics of visits to the website and the blog, but also recording who was using the community hashtag.
Starting and building a community is not an easy task, but one thing to recognise, rarely does it just happen…
Monday was a lovely day, as it was the first day that the new Jisc offices on Portwall Lane in Bristol were open. The new office was lovely, not quite finished, but the main working areas were open for business and it was a fantastic working environment. Lots of choice of different places to work, open plan, quite spaces, not a library quiet working space, small meeting rooms (ideal for silent working), social working spaces, light, bright and airy. Loved it.
I spent time putting together a presentation I was delivering later in the week. Though it was mainly images I did put together some explanatory graphics.
The talk was only ten minutes, so I hoped the graphics would explain the concepts more easily and faster. I also wrote a blog post about the presentation, which helped me formulate what I wanted to say in the talk. I wrote this in advance and scheduled it for publication later on the same day as the presentation.
As I had an early start in London on Wednesday I travelled up on the Tuesday so I wouldn’t be late for the event. In the end due to some travel issues I missed the start of the event, but was on time to present my piece and listen to some others from the first half.
I enjoyed delivering the presentation and a due to a last minute illness I was asked to chair the second half of the event.
My overall takeaway was that developing an intelligent campus (even a smart campus) involves a range of stakeholders and users, and that all departments across an university need to be involved.
Thursday I was on leave, so Friday was more about catching up on missed e-mail from the week and doing some preparation for the Data Matters 2020 conference, ready for meetings next week.
Over the last few years I have been working on a project at Jisc, called The Intelligent Campus. Though I left the project in March, in my new role and as part of Jisc’s work on Education 4.0, I still have an interest in that space and what is possible and what benefits it could bring universities and colleges.