Smart homes are impressive, there’s no denying it. More and more devices can be hooked up to your wifi in order to do various ‘smart’ things – from smart lights to smart thermostats and of course Google Home and Amazon Echo, all set to become run-of-the-mill (are listening hairbrushes and emotional cars also on the horizon?).
This is all very well, but why aren’t we harnessing this technology to improve the campus or classroom? Answer? We already are, and we’re planning on taking it to the next level too – by using data.
By taking the data retrieved from sensors, tracking and the internet and combining it with data from other sources (library management systems, virtual learning environments, even restaurants and catering), we can interpret patterns and learn how to improve the student experience.
What are the possibilities for universities and colleges?
The potential improvements really are endless:
- Socialising with others, whether for academic collaboration, social activities or mutual support
- Identifying and sharing events and activities
- Providing real time contextual information that improves decision making
- Raising issues and problems as they arise and linking to support
- Moving around the physical environment and accessing facilities easily
- Making the physical environment more comfortable and healthy
In short, anything that can make life easier for students, improve their academic progress, enhance their emotional wellbeing or make the environment more comfortable.
Smart buildings on campus are old news (automatic temperature gauging for example), but have always been very expensive, which is why many institutions just don’t have them. What we haven’t done though, is link the smart buildings with smart learning: using the data collected through learning analytics (explored later in the blog), to inform decisions about teaching and the space in which it takes place.
Intelligent timetabling is another possibility. Sitting in the same lecture room or theatre for every class could become a thing of the past. If the timetable ‘knew’ what a lecturer planned to teach, it could select a more suitable room for that particular class, for example – even providing directions to the room to each students’ devices.
Wayfinding your way around
Wayfinding (information systems that guide you through a physical environment, enhancing your understanding and experience of the space) is another component that could enhance campus life.
For example, imagine heading to a lecture if you were in a wheelchair. A wayfinding system on a mobile app could direct you to an alternative route that avoids tricky steps or difficult terrain.
I know how you’re feeling
Can the performance of students and tutors be improved by a combination of emotion recognition and artificial intelligence?
A number of universities are already looking at to the possibilities of using video monitoring and webcams along with emotion recognition software. In lecture theatres and learning spaces, disengaged or struggling students, could be identified and feedback provided to their tutor or lecturer.
The Sichuan University in China has been using facial recognition technology for attendance monitoring for some time and is now investigating emotion recognition1. The aim is to determine the student’s interest level, identify sadness, happiness and boredom. This data can then influence teaching techniques and content to ensure that students are stimulated and paying attention.
Learning analytics aims to use data about students to make informed decisions particularly in the areas of student satisfaction, retention and attainment. It is seen as having the potential to improve understanding in student performance and interaction with university resources, as well as helping to spot students at risk of dropping out/those who might be struggling.
Addressing the ethics
Of course, students can be cautious when it comes to their data being tracked. At Jisc we take the ethical aspects of analytics seriously – and have created a code of practice that sets out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively.
The intelligent campus guide from Jisc is on its way, and will provide advice, ethics information and guidance on implementing intelligent campus ideas, as well as looking at what other industries are doing in terms of intelligent data collection.
We’re still deciding the role that we’ll have to play when it comes to the intelligent campus, and there’s a lot of research to be done. Regardless, we’re excited to be investigating the space, and enthusiastic for what’s to come.
Listen to our podcast series on solving the ethical and legal issues around learning analytics and take time to read our code of practice for learning analytics.
We’re also looking for feedback on our draft intelligent campus guide, so please do get involved.
- 1 Read more in this article from September 2016: http://www.telegraph.co.uk/news/2016/09/12/facial-recognition-technology...