Shorter week this week with Easter Monday. Headed to the office on Tuesday after the long weekend and did some writing and planning. In the end (with what it being school holidays) I was in the office every day this week. With many people in Jisc on leave this week, and the same can be said for much of higher education it was a rather quiet week, which gave me time to focus on getting some research, analysis and writing done.
I did write a blog post about lecture capture and how you could do things more creatively.
The idea of capturing a lecture isn’t new. Even before the advent of dedicated lecture capture systems being installed across the campus some lecturers (and some students) would record the lecture onto cassette tape.
I have been thinking of using Jisc’s Digital Elevation Tool for FE in the Intelligent Campus space. So this week I started planning what needs to happen to make that happen. This involved looking at the scaffolding that the tool has and what would need to be in a campus version of the tool.
Is UK higher education really the world’s third most expensive way of getting a degree – and if it is, what might the alternatives look like?
One of the key questions that arises from different operating models, are higher education institutions prepared to change, and are they only going to change because they are forced to.
There’s a history of attempts to drive efficiency by sharing services – and precious little evidence of success.
When I started my work in this space, I came to similar conclusions that were in this article. However I do think just because that was the way things were, doesn’t mean that there isn’t opportunities in the future.
Did some analysis of various reports, articles, and links in relation to Optimising Operations and Data. I did a similar analysis of various reports, articles, and links in relation to Intelligent Campus.
I started the planning various reports in relation to Optimising Operations and Data.
I had a meeting about a proposed Intelligent Campus maturity framework.
I did some more field research on the Intelligent Campus.
A busy start to the week, I was attending HESCA 24 at the University of Loughborough. HESCA is the Higher Education Smart Card Association, primarily a membership organisation for vendors in the smart card and access card space.
There were some interesting talks and presentations. Some were from universities and others were from vendors. As the presentations were about fifteen minutes long, I didn’t make any sketch notes.
I was talking at the final session of the conference talking about the holistic approach to building a smart campus. Got some nice feedback from the session.
This week we also had our Senior Education and Student Experience Group Meeting. As a well as our usual what’s on your agenda discussion, we also looked at what the big challenge is for higher education and discussed two of the future visions I have been writing. Some interesting thoughts and commentary came out from that.
I had an initial discussion meeting with another university about a possible stakeholder workshop. I was also contacted by a colleague in Jisc about a different university for a conversation, who is also interested in this space. There is a lot of interest and demand in this area from universities across the UK.
I continued my work on optimising operations and data, undertaking further analysis of various reports, articles, and links. I did a similar thing with my work on the intelligent campus.
We had a team meeting, though meeting isn’t really the operative word here, much more a structured conversation and chat.
I was in the office on Friday which was quite busy, for a Friday, usually it is quite quiet.
I attended the Digital Elevation Model review meeting with colleagues from the FE side of Jisc.
I have been working on a series of visions about how universities could be working differently in the future. The aim of the visions is not to predict a future, but to provide an insight into a possible view of what that future could look like and think about how these impact on your current position and thinking. We did something similar for Learning and Teaching Reimagined, and though I wasn’t personally credited with the authorship of some of the visions, I did create and write the visions. I tested them out with a few people and got the reaction I wanted as well as stimulating an interesting discussion.
One of those visions was about organisations merging. Coincidently in the news this week was the news that City, University of London and St George’s, University of London have agreed a merger – the new institution will be called City St George’s, University of London and commence operations from 1 August, “though full integration will take longer.” Current City president Anthony Finkelstein will lead the combined institution.
There has been much talk about the four day week, in the Guardian this week was an article on how some firms have made their four day week trials permanent.
Most of the UK companies that took part in the world’s biggest ever four-day working week trial have made the policy permanent, research shows.
Reports from more than half the pilot organisations said that the trial, in which staff worked 100% of their output in 80% of their time, had a positive impact.
For 82% this included positive effects on staff wellbeing, 50% found it reduced staff turnover, while 32% said it improved job recruitment. Nearly half (46%) said working and productivity improved.
How can learning analytics – data systems that help understand student engagement and learning – be used to identify students who may be at risk of withdrawing from their studies, or failing their courses, and what interventions work to re-engage students in their studies?
The key findings from the report were:
Neither HEP found a measurable difference in post-intervention engagement rating between at-risk students who received an email followed by a support phone call and at-risk students who received only the email.
Neither HEP found any significant impact of the additional support call on the likelihood of a student generating additional at-risk alerts.
Qualitative feedback indicated that students welcomed the intervention. For some, the phone call was appreciated as a means of breaking down barriers between themselves and the institution and stimulating their re-engagement with learning. For others, the email alone was cited as a sufficient motivator to re-engage with learning.
A new study from TASO seeks to judge “what works” in the use of learning analytics for student support, exploring whether students identified by engagement data as being “at risk” were better supported by email and phone contact or email alone. Large cohorts of students at two providers, Sheffield Hallam University and Nottingham Trent University, were divided into two random groups. In both cases, it was found that an additional support call created no measurable difference in at-risk students’ subsequent engagement and no appreciable change in the likelihood of the student generating subsequent alerts.
It will be crucial to robustly test the impact of any wellbeing interventions that analytics systems may trigger.
As many people already well known, the environmental costs of generative AI is soaring, and that also being kept mostly secret. In Nature is an article about the impact AI will have on energy systems.
Last month, OpenAI chief executive Sam Altman finally admitted what researchers have been saying for years — that the artificial intelligence (AI) industry is heading for an energy crisis. It’s an unusual admission. At the World Economic Forum’s annual meeting in Davos, Switzerland, Altman warned that the next wave of generative AI systems will consume vastly more power than expected, and that energy systems will struggle to cope.
Spent some time planning out Senior Education and Student Experience Group meeting for March.
Wrote a briefing update on the work I have been doing on the optimisation of operations and data work.
Had an interesting and informative conversation with a college about their smart campus aspirations.
Spent time planning next steps of my Intelligent Campus work.
Planning a meeting with an university for a follow up workshop on their smart campus planning, after successful workshop in January and their request for a 1-2 day cross university workshop.
Worked on creating and planning blog ideas in the personalisation space. Also worked on creating and planning senior management primer ideas in the personalisation space, and some use case ideas.
Spent time planning out ideas for Spaces events over the next 12 months.
Noted that this worknote represents five years of undertaking worknotes for the blog.
It was half term week in North Somerset, so I was off to the office for most of the week.
I posted a blog post What makes an intelligent campus? which was about the differences between a smart campus and a campus which is intelligent.
A dumb campus is merely a series of spaces and buildings. For example the heating comes on at 8am, off at 5pm, and is only switched on between November and March, regardless of the external temperature.
A smart campus uses data from the spaces and buildings to make decisions. For example, a thermostat controls the heating, as the room warms up, the heating turns off.
An intelligent campus uses data from across the organisation to make decisions and make predictions. For example, a team is out on an away day, so the intelligent campus, switches off the heating and lighting on that floor for that day.
I also updated a blog post I had written about the links between the university smart campus and the smart city (or smart community).
So how does the intelligent campus slot into the smart city? The reality is in many cities the campus and the city are not distinct spaces, and for many people they will move between city and campus across the day. If a university with an intelligent campus does not integrate or work with the smart city, then they won’t have the full picture and in some cases could be at odds with each other. Bringing in the full picture, all the data, a better understanding can be drawn from the experiences of the students and the city population at large.
Following on from the Intelligent Campus workshop I ran in January, the university has been back in touch to discuss planning a two day workshop with a wider range of stakeholders.
I had my Q2 review. As always, these notes come in useful for writing up that review.
I spent time reviewing the personalisation space I have on Dovetail and identifying gaps and further research required. The plan here is not to create the definitive guide to personalisation in higher education, but reflect on a shared understanding, the needs of the sector in this landscape, and where and how Jisc can help and support universities in moving to a more personalised student experience. I worked through a potential workplan and what the next steps are.
I have spent time working on learning spaces, and I undertook a second analysis of learning spaces scoping study we did last year, adding tags and insights to Dovetail space I have on learning spaces.
The smart campus is already here. Universities across the UK are already using technology, sensors and data analysis capability to prompt simple, automated actions such as adjusting heating, for example. The smart campus 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 the system will take into account the actual external temperature 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. Similar occupancy data can be gleaned from campus wide wireless neteworks. We can also ensure that the lighting, heating and CO2 levels are within defined parameters. We often have insights into specific aspects of the smart campus, environmental conditions or room utilisation but these insights can be limited in what they can tell us. Most of the time, it isn’t all joined up and so has limited scope in terms of what we can learn and how we can use the knowledge to enhance and improve the student experience.
It’s a similar story with the smart city. Cities across the world are looking at how they can use technology to make transport and transit systems work for the people in that city. The Wikipedia definition of a smart city is “an urban development vision to integrate information and communication technology (ICT) and internet of things (IoT) technology in a secure fashion to manage a city’s assets”. Data from systems and sensors across a city can tell us some stories, about the use of transport, congestion, parking, pollution, health care, crime and a range of other functions and aspects of the modern city. Like the smart campus these insights and stories can be limited in scope, and often only give us part of the story.
Newcastle University worked with its local authority to develop a Cooperative Intelligent Transport System (CITS) leading to a “smart corridor”. This will mean that buses will be controlled by digital technology. This will allow buses to “talk to” traffic lights, maybe holding green lights for a short time or redirect drivers past congestion, improving journeys and reducing delays. Many of these smart city initiatives work in isolation, where real benefit comes is when the data from these systems is integrated and new possibilities emerge. It’s not always about systems talking to each other – if a system can utilise the data from another then maybe better informed decisions can be made.
There is a vision of universities moving from a smart campus, to a smarter campus, to the intelligent campus. An intelligent campus will take data from a range of sources, not just the physical aspects of the campus and how it is being used, but also the data from digital systems such as cohort information, attendance records, the virtual learning environment, the library, student records, even Electronic Point of Sales 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.
An intelligent campus using predictive analytics means that rather than responding to problems, universities and colleges are proactive and make appropriate interventions earlier to avoid those problems happening in the first place, based on a range of live data sources. It’s a similar story within the smart city, where using a range of data sources and analytics could enable informed decision making removing the need to react to problems by ensuring they don’t happen or are mitigated as much as possible.
So how does the intelligent campus slot into the smart city? The reality is in many cities the campus and the city are not distinct spaces, and for many people they will move between city and campus across the day. If a university with an intelligent campus does not integrate or work with the smart city then they won’t have the full picture and in some cases could be at odds with each other. Bringing in the full picture, all the data, a better understanding can be drawn from the experiences of the students and the city population at large.
The collection and interpretation of data from a wide variety of sources understandably raises some concerns about the appropriateness of data collection and usage. One of the challenges that does need to be seriously considered are the ethical issues of using a range of sensors, tracking technologies, even CCTV that could be used to track not just people’s movements, but could actually be linked to individuals.
Some of the examples of data used in intelligent campus or smart city activities might not be thought of as personal. However, with the combination of different types of data from different sources, it becomes potentially easier to identify individuals, for example precise location and user behaviour. Anonymised data once aggregated can lead to better understanding of user behaviour and the management of facilities, but also potentially reduce privacy.
Even in an age where sharing of data on an app is commonplace, and sometimes scant attention is paid by users to the extent of this sharing, the fears and concerns of individuals should not be underestimated nor dismissed. This is something that we at Jisc have had to grapple with when developing our Learning Analytics service, which we recently launched, along with a code of practice to address ethical questions.
Could this become a reality? Learning analytics services rely on a hub where academic and engagement data is collected, stored and processed. What if we, as a sector, could extend the learning data hub to enable data to be gathered in from physical places? Could we also bring in data from public systems, such as transit information, traffic, pollution levels, health care, entertainment information and provide a full enhanced student experience? Well that’s a dream that may well be possible in the near future.
References
Clay, J. (2018). Guide to the intelligent campus. 1st ed. [ebook] Bristol: Jisc. Available at: http://repository.jisc.ac.uk/6882/ [Accessed 13 Feb 2024].
Education Technology. (2018). What makes an intelligent campus?. [offline] Available at: https://edtechnology.co.uk/Article/what-makes-an-intelligent-campus [Accessed 10 Sep. 2018].
I often, well sometimes, I got asked what is the difference between a smart campus, and an intelligent campus.
A dumb campus is merely a series of spaces and buildings. For example the heating comes on at 8am, off at 5pm, and is only switched on between November and March, regardless of the external temperature.
A smart campus, uses data from the spaces and buildings to make decisions. For example, a thermostat controls the heating, as the room warms up, the heating turns off.
An intelligent campus, uses data from across the organisation to make decisions and make predictions. For example, a team is out on an away day, so the intelligent campus, switches off the heating and lighting on that floor for that day.
Now onto the detail…
The smart campus is already here; the technology, sensors and data analysis capability are all available, but it isn’t all joined up and so has limited scope in terms of what we can learn and how we can use the knowledge.
What we need now is the intelligent campus, where data from the physical, digital, and online environments can be combined and analysed, opening up vast possibilities for more effective use of learning and non-learning spaces.
But before we head down that road, it is useful to reflect on what we mean by a campus.
Universities across the UK are a diverse mix of traditional campus-based institutions, city-based universities where the estate is mixed in between retail, office and housing, and multi-site universities, with geographically spread campuses.
But they all have many features in common. There are formal teaching spaces, including classrooms, lecture theatres and labs. There are informal learning spaces, where learners can learn when they want to, including computer labs and the library.
There are also a whole host of social spaces such as cafeterias and dining halls, sports facilities, concert halls, common rooms, and student accommodation. Then there is the work space you need to run the institution, from the finance office to the server rooms, and there may also be green spaces, parking areas and business parks.
The non-smart or “dumb” campus is one where information on how physical infrastructure and space is being used, and what it is being used for, is rarely noted, and even more rarely acted upon. Any room utilisation surveys will be carried out by people with clipboards noting the number of people in each room, but probably not considering their activities. It would be really hard to work out how many people were in the building, even more challenging when there are multiple entrances and exits. In the non-smart campus heating comes on at 8am, and is only on between November and March, regardless of the external temperature. There are physical switches for the lighting system. Timetabling will dictate which cohort has to be where and when, and what subject they are doing. But often that is planned a year ahead and won’t take account of the kinds of teaching and learning that may be undertaken in any given slot, or whether the cohort changes size.
The non-smart campus can be inefficient, costly, and impact negatively on the student experience.
In many ways the smart campus is already here. Most new buildings built on the university campus will have an element of smartness about them.
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. The data from these sensors can tell us a lot about occupancy, as well as saving electricity costs.
But the smart campus 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 the system will take into account the actual external temperature 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.
Timetabling and curriculum planning, gives us an insight into when students could be on campus (not saying they will miss lectures, but you and I know this happens), adding in attendance data (if used) can enhance that picture. Bring in retail date from the coffee places and the shops. Data on bus tickets and car parking will also be an useful indicator of visitors to the campus.
Throw in library data, PC bookings and book issues.
Then there is network data, how busy is the network, how many devices are connected. Top end wireless networks can also help with occupancy based on connections to different wireless endpoints.
Even energy costs will add some useful insights into the use of the campus.
So what is the difference between a smart campus and an intelligent campus?
There are some key considerations when we come to looking at what makes an intelligent campus – the first is the aggregation and analysis of different kinds of data.
One of the noticeable attributes of a smart campus is that data is often siloed and isolated, and analysis and decision-making is based on a single data set.
An intelligent campus will take data from a range of sources, not just the physical aspects of the campus and how they are 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 campus. Here are some examples:
A student using an app on their smartphone can decide very quickly if they should visit the library that day as the app is indicating that the library is very busy, but it also informs the student that the noise levels in the coffee shop on the other side of campus are low, making it a possible option for study.
A lecturer decides on various group activities in a classroom, the room system having checked the module information and activity parameters, and set the heating and lighting to the optimal level for the activity, while also considering the preferences of the particular cohort of students.
A member of the finance team finds out from an app on their computer, based on data from previous visits, that the cafeteria is running low on the vegetarian special that day, so they can decide to leave now for lunch, so as not to miss their favourite meal.
The next level of the intelligent campus is to move beyond using this live data to add a machine learning or artificial intelligence element to the analysis, providing further insights. Bringing in historical data, feedback, and evaluative data, we can start to add a level of predictive analytics that will allow students and staff to make informed decisions on what is likely to happen.
Predicting when the library will be most busy and noisy, for example, will allow students to choose whether to come to campus before or after peak times, and will reduce the probability that the library will be too full for comfort at any one time.
An intelligent timetabling system could start to reflect on the sort of activity likely during a particular study module, not just on the number of students taking part, so the group activity could be shifted to an optimal room, rather than sticking rigidly to the same space.
By analysing when and how rooms are used, organisations will be able to make smarter, more effective use of learning spaces and other facilities across campus and to improve curriculum design and delivery.
But could this dream become a reality? Learning analytics services rely on a hub where academic and engagement data is collected, stored and processed. What if we, as a sector, could extend the learning data hub to enable data to be gathered in from physical places? How would we collect that data and what smart campus technologies would we need to have?
Making timely interventions to ensure that the best available spaces are being used for each session will enable students to learn more effectively and ensure that the organisation is running efficiently. Insights into utilisation of space, services, and resources, will enable universities to enhance the student experience.
Though much is being done in this space, the work has been focused on the relationship between the physical estate and the IT infrastructure coming together. The reality is that a university campus is awash with data from many different systems. A truly smart campus needs to bring that altogether, and an intelligent campus will enable deeper and more useful insights. Longer-term the possibilities for the intelligent campus are practically limitless.
After a week in the Bristol office, this week I was only there on Friday. Monday I was working from home, the train strikes disrupting rail travel for my Bristol commute. I spent a couple of days in Birmingham as well. I was off to Birmingham for a Smart Campus Roundtable being facilitated by PTS, an external consultancy company. I had attended a similar eventin London in June.
The focus of the event was about progress universities were making in the smart campus landscape, with presentations from Birmingham and Bristol. We had various discussions about university aspirations, challenges, business cases, cross-institutional teams. There was very little discussion on the actual smart campus technologies that are available. As was recognised across the room, the real challenges are vision, strategy, planning, policy, process, and culture.
I also found about the Smart Building Overlay to the RIBA (Royal Institute of British Architects) Plan of Work.
RIBA have developed a Smart Building Overlay to provide guidance on smart building technology through each RIBA Plan of Work stage; aligning decision-making with project outcomes and helping designers integrate the technology to support them.
This is an interesting document but does remind you of how much work has been done in this space by those involved in the architectural and construction industries, not just in education, but across all other sectors as well. Are educational spaces that different, something to think about.
Though much is being done in this space, the work has been focused on the relationship between the physical estate and the IT infrastructure coming together. The reality is that a university campus is awash with data from many different systems. A truly smart campus needs to bring that altogether, and an intelligent campus will enable deeper and more useful insights.
In a couple of weeks I have my Q2 review. As always, these notes come in useful for writing up that review. I also write my review in a Word document before then pasting into the HR system. I am glad that I did as I found out on Monday that there had been a glitch in the HR system which meant all my input was missing. Of course I could replace the text in my form from the Word document.
This was a habit I got into many years ago, as too often when writing into a web form, there would be a connectivity issue, or a glitch and I would lose everything I had written. So I now write in a word processor and then copy and paste. I do that for all my blog posts as well. So I am writing this blog post in Word, and then I will copy and paste into my WordPress instance later.
There is another advantage with using a word processor, is that I can write some of the blog post one day and finish it off another day. Using it for week notes means I can write up each day individually if I need to.
Saw an online presentation from David Kellerman on the digital transformation in his work at UNSW in Australia. He was an enthusiastic presenter and very passionate about his work.
I have been invited to speak at Higher Education Smart Campus Association (HESCA) event Smart Technology for a Smarter Campus’.
HESCA’s aim is to provide Higher Education establishments with a platform for debate on smart card technology issues relevant to their business objectives.
As you might imagine, the focus is very much on smart card technology, but though smart cards can provide lots of data, they can also be used to enhance the student experience in a lot of areas, if other sources of data are joined up. Very much an aspect of the intelligent campus.
I spent time researching, planning, and writing my presentation for HESCA 24 How smart technology is vital for tomorrow’s campus.
Reviewing and analysing my learning spaces space on Dovetail, looking at what I have done, what I could do, and what I need to do.
Spent time doing the purchase orders, booking, and logistics for various conferences. I am planning to attend UUK’s Survive or thrive? Grasping the financial sustainability challenge Conference. Also WonkHE’s Secret Life of Students, and the UCISA Leadership Conference in Edinburgh.
After some setbacks I did the recording and editing for my Leadership Masterclass – Operationalising your Strategic Vision video.
Most of the week I was over in East Anglia, and as a result I spent quite a bit of time travelling. It was also a shorter week as I was on leave at the beginning of the week.
My main event was delivering an Intelligent Campus workshop at the University of East Anglia in Norwich.
We had an excellent interactive discussion about what is the smart campus, how do we make it intelligent. We looked at possible opportunities in making your campus smart, but also many of the challenges and barriers that will stop this from happening.
I also brought in some external perspectives from EDINA in Edinburgh and some of our own Jisc staff.
One thing that I was reminded of, was how that campuses don’t just appear, they evolve and grow over time. A typical university campus will have a range of buildings and spaces and with each building there are challenges in making them smart.
Another perspective was the importance of having a strategic vision for your campus. This can be challenging when a typical university campus can be for three years, whereas the typical life of a university building is usually in excess of twenty years.
I enjoyed the workshop and having an explore of the UEA campus. It has a real mix of buildings, old and new. There was lots of green spaces and trees as well. It was established in 1963, but their first building was Earlham Hall which was built in 1642. This building now where the Law School lives.
As I was in Norwich, I also took the time to visit the Norwich University of the Arts. They also have a mix of old and new buildings.
I grew up in East Anglia, and I am not 100% sure if I ever visited Norwich. I thought I had, but none of it seemed familiar. I had visited other places in Norfolk before, Kings Lynn, Dersingham, Hunstanton, and Thetford. However I have no recollection of visiting Norwich.
As I was over in East Anglia I also visited the University of Suffolk campus in Ipswich. This was founded originally in 2007 as a unique collaboration between the University of East Anglia and the University of Essex. It gained independence in 2016.
There are a range of buildings, the Waterfront Building which opened in 2008, followed by the James Hehir Building three years later.
There is a substantial amount of student accommodation on the waterfront as well.The most recent addition to the growing campus is The Hold, which houses the majority of the Suffolk Record Office’s collection and provides various facilities to the university including a lecture hall.
It’s quite a hike to East Anglia, so a good part of the week was travelling much as anything, but it was worth it for the workshop and visiting different campus sites.
I had various meetings this week and spent time in our Bristol office, as well as working from home.
I wondered if silo working is another word for non-strategic working? People often complain about silo working and the resulting challenges that can arise. I think part of the reason why there are problems with duplication, conflict, and lack of communication, across silo working, is teams are working to their own objectives and aren’t necessarily working towards common objectives.
The NSA in the US talks of silo working as cylinders of excellence. You can have outstanding or excellent teams, but not necessarily have an excellent organisation. See this blog post I wrote about that. I think I might expand on this on a future blog post.
I attended the Adobe and Wonkhe Education Espresso event on supporting pedagogical development and innovation.
I had a meeting on licensing development and links to intelligent campus and student experience.
I had a meeting with organisers of on possible speaking opportunity and possible session ideas for EDUtech Europe 2024.
I had an Intelligent Campus meeting with the Honeywell PoC team at Jisc.
I also had a meeting for planning a workshop on building a smart or an intelligent campus.
Had an informal discussion with colleagues in Jisc on learning spaces. I have been looking at how Jisc can support universities in the learning spaces space. What help and support do universities need, and what help and support do we want from Jisc. We also discussed the compromise that is a flexible learning space. Often, we see universities building flexibility into their learning spaces, as that is often seen as easier than building flexibility into curriculum design and timetabling.
Continued my work on a concept for supporting institutions in the smart campus space. This included reviewing the Higher Education Reference Model with an intelligent campus lens.
I recorded some content for an internal podcast. I used my Snowball microphone using Quicktime. I did a test recording, which sounded fine, and then did the actual recording. After sending it off I got some feedback that the audio recording was noisy. I checked my recording and there was a lot of interference. I had written a script for the recording, so it was quite easy to re-record the piece. This time though I used Garageband to record the podcast clip, and then checked that it sounded okay before sending it off.
