Tag Archives: intelligent timetable

The Intelligent Learning Space

So what do we mean by a learning space and how is an intelligent learning space different? What is a smart learning space?

lecture theatre
Image by Michal Jarmoluk from Pixabay

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.

solitary
Photo by Philippe Bout on Unsplash

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.

Image by Peter H from Pixabay

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…

Working together
Image by StartupStockPhotos from Pixabay

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.

The bells, the bells… – Weeknote #34 – 25th October 2019

Wedding Car by James Clay

I spent the weekend at a family wedding down in Sussex and I got my first taste of campanology, when I was asked to ring the bell in the church at the end of the wedding service, why I was asked I have no idea, but my family now have an amusing video of me being pulled up and down by the bell rope! The wedding was lovely and we had a great time.

Nine years ago on the 19th October 2010 I took this photograph of one of the offices in the college I was working in.

Office space

We had been having a lot of discussions about desks and offices. One particular group of staff were adamant they needed their own desks to work on and that they didn’t want their space changed.

What you should notice from the photograph above was that though everyone had their own desk, what they were actually using them was for, was storage. No one was really using their desks for working at. The result was a room which was not conducive to working, so no one worked in there. No one could find anything… well some could.

I remember having discussions about replacing the space with fewer desks, more storage and some nicer seating and comfortable areas. The reaction was (as expected) no, I need my own desk.

The staff in this office spent the majority of their working week teaching in classrooms, when they were not teaching, they wanted space to mark and prepare, research as well as somewhere to relax, drink coffee and discuss stuff with colleagues. They also needed space to store materials and resources, as well as student work. Their needs were being overshadowed by the need for their own space, a space they could call their own.

For me the key lesson here was that people didn’t think about the space in the context of what they needed to do in that space, but more about having a space to call their own. In terms of space planning you do need to balance those things out. Continue reading The bells, the bells… – Weeknote #34 – 25th October 2019

The tyranny of the timetable

Image by Free-Photos from Pixabay
Image by Free-Photos from Pixabay

What is a timetable?

An academic timetable is a way co-ordinating four elements:

  • Students
  • Academics or teachers
  • Rooms
  • Time

Currently the timetable is something that is often done to teachers, academics and students, over which they have minimal input or control.

In the world of Education 4.0 where we want to transform teaching, provide a personalised adapter learning experience and re-imagine assessment, all within a fluid digital and physical campus, the timetable as it stands now is something that constrains and blocks this potential vision.

As a student at school, college and university I had no control or influence over my timetable. When I first started teaching, I was given my timetable, I wasn’t asked to input into the process. It told me what I was going to teach, who I was going to teach, where I was going to teach and when I was going to teach..

As a programme manager in another job I had a bit more input into the whole process. We didn’t have a system or mechanism for creating the timetable, just large sheets of graph paper. It felt like some kind of three dimensional chess combing the four elements outlined above. What I do remember about the process, the first static aspect was the rooms, then the part time cohorts, after that everything else was just fitted into what was left.

Back then following student feedback, it was apparent that some of our timetables for our full time students weren’t exactly student friendly. They were expected to be in every day, and there were large gaps in the day between lessons. The end result was a fair bit of absence and a fall in retention.. So one year we decided to build the timetable around the student, we condensed their week into three (longish) days. Then we fitted in the rooms and teachers into the process. The end result was an improvement in attendance and retention.

Photo by Priscilla Du Preez on Unsplash
Photo by Priscilla Du Preez on Unsplash

These days we have timetable systems, some are based around Excel, others databases and some proprietary timetabling systems. There main focus is to avoid clashes, and enable people to discover when to if rooms are free. However in my experience they are still quite static systems that are still done to students and academics.

You have a cohort of students, you have a number of weeks to deliver your subject and you are assigned a room or space for that year. If you want to do something different than you normally do, you sometimes have to make do, and undertake it in the same space, or you have to struggle to find a space, do things out of hours or just give up. You want to deliver online, then you still find you have to retain using the space, because otherwise you might lose it!

We need to build an intelligent timetable, one that adapts and changes to the changing requirements of different subjects, teachers, spaces, cohorts and individual students. This is easier said than done.

Image by Jan Vašek from Pixabay
Image by Jan Vašek from Pixabay

So what is the current landscape like? Most timetable systems operate in a silo, a fixed point in time. It is hard to make dynamic changes to the timetable, as it is rather inflexible. Once it is set up, because the fact it inflexible, only very small changes can be made, but making a large number of changes wouldn’t be possible.

So could we build a smart timetable? A smart timetable would be able to flex and change as the demands placed on it allow rapid shifts and changes. I need a larger room, the timetable would be able to accommodate it, whether it be for one week or the rest of the year. A smart timetable would inform decisions about space.

An intelligent timetable would be able to make changes in advance, based on information gathered from across the college. It could predict what spaces would be available and what changes would be needed, based on data and make changes as required. So as a cohort increases, it would automatically assign a bigger room. As a curriculum changes, they change the cohort to the most appropriate space.

There are some challenges on this, especially if the campus is diverse and large. Students may not know where specific spaces are, going to a different space each week. A smart timetable would need to know how long it can take to move between different rooms to accommodate room changes. Students would need some kind of way finding process to find the rooms. So in order to build a smart or intelligent timetable you need to have already created a digital map of your campus. You need to have already identified route mapping, timings and accessible routes.Similarly students may need to receive notifications about which rooms they will be in, how will these be sent?

If you are changing the curriculum, how would the intelligent timetable system know what the space needs are for different kinds of activities? So you then need to be able to define the curriculum in a way so that the timetable can interpret that and make appropriate decisions about spaces.

What spaces are appropriate for what activities? How do we know this? Does the space have a huge impact on learning? How do we describe this from a digital perspective?

Image by Free-Photos from Pixabay
Image by Free-Photos from Pixabay

When you start down the road, moving from a static timetable to a smart timetable, and then onto an intelligent timetable, you start to realise that the timetable is actually a small part of the work involved. There is a whole lot of data needed to enable the timetable to make smart or intelligent decisions.

Of course with a whole lot of data, you can then start to think about timetabling analytics. Can we start to use our spaces better? Can we improve the timetable for students? Can we improve the timetable for staff? Can we utilise resources for efficiently? What interventions do we need to make to enable this?

We need more detailed advice and guidance on why we need an intelligent timetable and how it could support the future that is Education 4.0.

We need to design the data infrastructure required to feed into any future intelligent timetable product.

Could we even build a prototype of a smart timetable, or even an intelligent timetable.

How do we overcome the tyranny of the timetable?