2. Why would we want an intelligent campus?

So far we’ve looked mostly at the concept of “intelligent”. Now it’s time to look more at the campus aspect. What is driving the agenda to incorporate some of these technical capabilities into the educational setting, and who benefits?

Drivers

If the campus is more responsive, able to react to changes in the environment and to behaviour of those in it, to adapt and to optimise, what are the implications for universities and colleges?

Potential applications exist in several key areas:

  1. improving the student experience – responding to student needs, providing timely and relevant information, enhancing learning opportunities
  2. creating new opportunities for research including cross-disciplinary areas, societal challenges and the management of the research lifecycle
  3. reducing environmental impact – monitoring energy usage and waste, and adjusting energy to meet needs in real time
  4. enhancing the physical environment – making it more comfortable or conducive to learning
  5. maximising use of valuable resources – including rooms and equipment, understanding availability and usage

A combination of drivers may be behind specific initiatives that aim to achieve some of the above benefits.

  • the economic context encourages better use of resources
  • legal and ethical concerns contribute to environmental objectives
  • the learning and research environment is influenced by institutional reputation, competition and educational principles
  • challenges of increasing amounts of data used in research and how to collect, organise, report or integrate this data in pursuit of research goals
  • last but not least, technological advances make this all possible, and in some cases the technology itself may be a significant influence

Ensuring that the technology is used in support of other strategic aims rather than as an end in itself is important in developing useful initiatives.

The concepts are also frequently explored in collaboration with the local area and services, including transport, not just the campus in isolation. Similar agendas are being pursued in other contexts, in particular the development of “smart cities”. Examples of universities trying to work with city wide developments are already taking place, particularly in areas such as transport, energy, health, urban informatics, collaboration with other sectors and the environment. This is a topic we will return to in a later section.

Specific benefits

Whether you are a student, teacher, researcher, manager or providing services to others, the intelligent campus offers the potential to improve effectiveness and efficiency. Realising that potential is more complex, and we will introduce specific examples in a later section to look at how this is achieved in practice but here are a few possible scenarios:

  • student recruitment and retention – ensuring new students have the best possible experience upon arrival with timely, relevant information being pushed to the student
  • the learner environment, experience and voice – monitoring environmental conditions and the feedback from students
  • smart research – creating, structuring and publishing data for the research community
  • campus management and cost saving – particularly in efficient use of space and facilities – ensuring facilities are as fully available as possible and that students and researchers are aware of available facilities
  • anytime, anywhere learning – using smartphones to provide learning opportunities away from the campus and contextual learning

What the campus does have already is a wealth of connected devices, both user-owned and organisational, reliable and fast networks, established systems,  and experience in collecting and organising data. Intelligent campus projects aim to bring together these existing systems and infrastructure with innovative applications to benefits campus users.

What are the concerns?

There are several main challenges to effective implementation of intelligent campus projects, centred around the following areas which are explored further in a later section:

  1. setting relevant goals – understanding what is useful and appropriate
  2. logistics of collecting and processing data – managing the sheer scale of data that can be generated
  3. interpreting large amounts of data to inform decisions – concerns about bias or misinterpretation in algorithms leading to inappropriate responses
  4. safety, security and privacy – such as the appropriateness of monitoring the location of individuals and sharing data
  5. reliance on technology – user skills, the need for resilience in networks, the danger of removing valuable human input, maintenance of devices and infrastructure
  6. the impact on people – including unexpected consequences of attempts to influence behaviour
  7. the need for joined up thinking and action from different departments and services across campus

Learning analytics

Analysing the data has already been identified as crucial to the intelligent campus, and has been  of interest for some time in the context of learning. Learning analytics is the focus other work (https://www.jisc.ac.uk/rd/projects/effective-learning-analytics) aiming 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, especially in enabling successful completion.

Analytics can be used in other contexts, for example applying the same analysis of data but in the context of teaching processes to support the work of staff rather than the focus of students with learning analytics. This could be in improving administrative efficiency, or supporting and enhancing teaching methods for the design and delivery of education.

Where intelligent campus fits with existing analytics work is to consider the integration of different types of data and more joined up analysis and knowledge. For example learner data and decisions combined with the wider context of the environment, community and services. This includes data on buildings and facilities, learning spaces and location data to deliver a more efficient campus, and potentially taking this further to improved teaching and curriculum design and personalised and adaptive learning.

With more joined up thinking and collaboration between teaching and learning, IT and estates, the benefits to the individual and organisation are potentially much greater, but also perhaps more complex to deliver.

 

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