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Near Future Teaching Final Report Launch Event: 27 March 2019

The celebration of Near Future Teaching, and launch of the final report, happened on the evening of 26th March.

The event brought together a really diverse grouping of students, staff and friends from across and beyond the university. The room itself was full of enthusiastic and encouraging discussion, which our colleague James Lamb was kind enough to document through a sound recording.

The overall purpose of the night was to present the process and the outcome from the last two years, so as well as eating, drinking and chatting, we had a series of short talks outlining different parts of our work.

Image by Anne-Marie Scott

Sian Bayne, the project lead described the background to the project and its overarching aim not to predict or respond to versions of the future determined by others, but rather to design our own future as a university, based on our own shared values.

Michael Gallagher, project research associate, spoke briefly on how he reconciled his work in developing nations where education is often a low-resource, low-technology, yet highly intricate affair with the models being advanced in the project. He emphasised the value of diversity in widening participation efforts, and how that value is found throughout the project.

Diva Mukherji, the Vice-President for Education for the Edinburgh University Students’ Association (EUSA) spoke next on the values underpinning the project, synthesised from data gathered and generated over the period of the project.

Diva from EUSA
Image from Chris Speed

Jennifer Williams, the Near Future Teaching core team member, project manager, and renowned poet, recited a work written during one of our project events which creative writing as a way of articulating the futures of the University. “What you will teach is, what you believe…”.

Jennifer Williams from NFT
Photo from Chris Speed

Santini Basra our partner and colleague from Andthen, the design-research and futures-thinking agency that has been working with us spoke next. He described the methods from the project, discussing how contemporary futures thinking can shake institutions into rethinking and exerting agency over their futures.

Image from Chris Speed

Finally, Professor Peter Mathieson, Principal and Vice-Chancellor of the University of Edinburgh then concluded the evening by officially launching the report, encouraging its uptake throughout the University, and emphasising that the values and methods emerging from the project could inform teaching at the University for generations to come. The remaining part of the evening was spent chatting around the exhibition about the project which designed by Andthen.

Peter Mathieson

Data Fluent

Aim: digital education that understands data, data skills and the data society.


  • Taking a research-led approach to education and data.
  • Understanding the possibilities and problems surrounding the datafication of education.
  • Addressing automation with an emphasis on human skills.
  • Engaging creatively and responsibly with learning data.

Short- to medium-term actions

  • Balance development of data skills with other human capacities for wellbeing and employability in a future of automated work, by building cross-university courses to develop student creativity, criticality, problem-solving and collaboration.
  • Establish Edinburgh as a world-leading centre
    for research in interdisciplinary, data-informed education in key areas such as educational data ethics and data-driven policymaking in education.
  • Use our research expertise in data to build an ethical, responsible near future for our teaching and to improve student experience.
  • Create specialist academic development opportunities for staff to fully understand how to analyse and interpret learning and engagement analytics, with an understanding that the datafication of teaching is likely to accelerate and intensify in the coming decades.
  • Embed critical understanding of data ethics and algorithmic accountability within academic development and staff training.
  • Support cross-university programmes of work to provide data skills training for staff and students.
  • Seek mechanisms for embedding students in ‘data work’ via digital apprenticeships, internships and employment experiences.
  • Develop new, engaging ways for students to work creatively with their own learning data to understand issues around its use and ownership.
  • Instigate an academic-led programme to scope ways in which transparent, fair, context-sensitive artificial intelligence applications and services could assist and support human-driven teaching.
  • Establish a cross-institutional, student-led programme of work to develop creative, responsible designs for a ‘smart’ campus.

Post Digital

Aim: education which recognises that technology is fully embedded in daily life.


  • Reworking the concept of ‘contact time’ to reflect contemporary practice.
  • Breaking down the boundaries between on and off campus.
  • Rethinking what it means to be ‘here’ at Edinburgh.
  • Offering more flexible ways to be part of the University community.

Short- to medium-term actions

  • Define and embed a re-worked understanding of ‘contact time’ into workload models and course descriptors, which takes account of student mobility, distance education and flexible patterns of study.
  • Continue to invest in programmes of work which open our teaching and community to new cohorts of students online and globally, including technologies for increased telepresence for students working off-campus.
  • Plan for the introduction of technological capacity to teach online and on-campus students together in joint cohorts.
  • Use our capacity and understanding of distance education to open our teaching in new ways to on-campus students, putting student-focused flexibility at the heart of our offer.
  • Ensure all staff have the baseline skills needed for a good student experience of digital education (for example the ability to upload slides, to record lectures, to design effective visuals, to tackle accessibility issues, to provide electronic reading lists).

Phase 3: Testing Vision and Strategy

Phase 3 Blog Post of Near Future Teaching Methods: Testing Vision and Strategy

— From Zoë Prosser and Santini Basra

During the earlier stages of the project, the opinions and values of staff and students had been collaboratively translated into a series of speculative worlds and scenarios. These served as thought experiments, which outlined possible futures for digital education at the University. From these speculative scenarios, an understanding of the kinds of futures that would be ‘preferable’ to students and staff had been identified and translated by the Near Future Teaching (NFT) team into a draft vision and associated strategy for building a preferable digital education future at the University. These were outlined through a series of five aims (vision), each with a set of indicative actions (strategy) to help realise each aim.

Find out more about this process by exploring our earlier blog posts.

Throughout October we supported the NFT team in facilitating a series of sessions with staff and students from across the University to test the response to this draft vision and strategy, and gather feedback and input for a further iteration. Through these sessions, we engaged 15 staff members and 40 students (although over 150 students expressed interest in attending one of the sessions).

The Testing Approach

Since the values and opinions of staff and students directly fed into the creation of the draft vision and strategy, it was important to take these back to them for further feedback. We were also aware that the students and staff members who had taken part in the earlier phases of research were limited in number and also by their distribution across the University. So further testing was an opportunity to widen the project’s scope of engagement, gather a broader range of perspectives, and add detail to our existing insights.

There were three areas that we proposed to focus on during the testing sessions:

  1. Assessing Preferability: Is our notion of what makes a ‘preferable’ future correct?
  2. Adding Detail: Collecting feedback on the aims and indicative actions that is sensitive to the diverse range of learning and teaching experiences from across the University. Understanding how aims and actions might affect people from across the University in different ways.
  3. Identifying New Indicative Actions: Taking suggestions and considering new actions which could be built into the strategy..

The testing sessions were kept brief, to 90 minutes, to allow for four sessions per day and a higher number of participants. At the same time however, it was also important to create an environment for deep and detailed conversation, and so while the sessions were kept short we limited the number of participants to under ten. This meant that the sessions were similar to focus groups, valuing each individual’s responses.

The Methods

As each aim was introduced, so too were a selection of designed speculative artefacts that touched upon the issues which the aim raised. These artefacts, which we called ‘provotypes’ (provocative prototypes), were used during the session to help participants quickly immerse themselves in ideas and discussion topics that are speculative and typically intangible, such as data ethics, new forms of assessment, and building digital skills.

Since the provotypes were intended to help facilitate discussion, and not to propose outcomes or ideas, they were produced in low fidelity. Therefore the artefacts themselves were not the subject of the discussion, but rather a mechanism to enhance and deepen discussions. They invited critique of the aims proposed in the draft vision, and the wider issues that the project is concerned with. Specific focus was placed on the opportunities and specific threats that the aims afforded.

Once a group had discussed an aim and its issues, the indicative actions were then introduced. These actions were discussed, developed and built on by the participants in relation to their own experiences at the University, and views on education. To conclude, students were asked what they thought the University should do to deliver each aim.

Distance students were engaged in a separate online session using Skype. This followed the same format as the previous face-to-face sessions on campus, however the aims that were discussed were those with particular focus on the experiences of distance learners and distance communities. Conversations between the online participants were captured using the chat box as well as audio.

Next Steps

At the very core of the draft strategy is our understanding of what a ‘preferable’ future means to those at the University. Our filter of ‘preferability’ has been qualified by the four values that were identified at the end of the community scoping phase, which concluded in Spring 2018. These values emerged from staff and students who are at the University now, but the NFT team is aware that in the future a new generation of students might hold, or prioritise different values. By continuing our testing with children in secondary and primary school education, the NFT team hopes to understand what new values for digital higher education might emerge in the future.

Following the sessions with school children, the NFT team will synthesise the data captured from conversations, into a final draft of the vision and strategy for digital education at the University, to be published widely.

NFT methods: community scoping and crafting worlds

Unpacking the community scoping phase

— From Zoë Prosser and Santini Basra

The first phase of the NFT project, ‘Community Scoping’, has generated a large amount of content: the vox pop interviews are summarised in a series of thematic videos, while earlier blog posts capture outcomes from several workshops, think tanks and focus groups with staff and student around the campus.

Working closely with the core Near Future Teaching Team (Sian, Jennifer, and Michael), we extracted information from these vox pops and workshops, with a focus on understanding the viewpoints and values of those who were engaged. This would serve as useful source material in the later stages of the project, and help us develop possible futures for digital education at the University of Edinburgh.

Fig. 1. Affinity mapping some of the key quotes.

Combing through these videos and blog posts, we pulled out key quotes and statements and affinity mapped them into clusters of quotes with similar sentiment. To formalise these, we converted each cluster into an opinion card (fig.2.); each card captured the essence of an opinion that was commonly held by those who engaged in the earlier phase of the project.

Near Future Teaching Workshop #1: Divergent Thinking

On April 30th at the Edinburgh Centre for Carbon Innovation (ECCI),  the first of two workshops was conducted for the Near Future Teaching project.

This first workshop was largely driven by the data and the subsequent outputs from the first phase of the project: vox pop interviews with a large range of faculty, staff, and students; events and focus groups; and the thematic videos emerging as a result. The workshop was attended by the Task Group of the project as well as students from across the university. Our task was to discuss, appraise, and collaboratively build speculative future worlds that higher education will inhabit over the coming decades.

The workshop was designed and executed by Santini and Zoe of Andthen, a consultancy which marries Design Research and Futures Thinking to help companies with early-stage innovation. They will be drafting a post soon on the design methodology behind this series of workshops and we will provide subsequent posts once we have had a chance to review the data generated as a result.

Briefly though, this first workshop was largely about exploring divergent thinking. We started with discussions around values which emerged from the Near Future Teaching vox pops, events, and materials generated by the student occupations.

We then each assigned (four groups in all) future worlds we had crafted based largely in the research, four future worlds that moved on one axis between open and closed systems, and human-led and technology-led on another. These four future worlds were outputs distilling a large amount of HE futures research, implicitly a challenge to the misconception that “there is an inevitable future to which we must simply adapt or resist” (Facer & Sandford, 2010).

Each group explored one world and the themes emerging from the video that might serve to underpin it: creative learning approaches, data, lectures, AI and automation, community, humans, and more. We worked through the future worlds and these themes, identified when they aligned and when they diverged.

The second part of the activity was about developing stories that might occupy the homepage of the University of Edinburgh, complete with images, quotes, and headlines. These were at times funny, poignant, largely astute, and ultimately revealing of the values this group would want embedded in such a future world (values that will take some effort to extract!). We presented these news stories to the room and closed for the day. The next workshop scheduled for late May will revolve around how these divergent ideas converge into a possible future for the University of Edinburgh.

The student occupation: near future teaching at the real Edinburgh Futures Institute

Students and staff constitute and give meaning to universities—and it is students and staff who should directly and co-operatively control their learning, their teaching, their research, and their contributions to the common good.

At the time of writing, students and staff at the University of Edinburgh are 14 days into an occupation of one of the lecture theatres in the university’s Central area.

Reclaiming the name of the university’s high profile project to refurbish the old Edinburgh Royal Infirmary, the occupation has re-named the Gordon Aikman Lecture Theatre in George Square ‘The Real Edinburgh Futures Institute’. Catalysed by the recent industrial action, the work of the occupation is impressive in lots of ways, but particularly in the thinking it is doing around the future of the university and its teaching.

Those students and staff involved in the occupation have written a declaration which the Near Future Teaching project would like to draw on as it moves forward – in particular the way in which the students have claimed a space to build a vision of education which is ‘free, democratic, and open to all’. Particular directly teaching-related parts of the declaration that can shape the work of the project are these:

  • We resist uncritical education that puts certificates over learning and exploration.
  • We resist assessment systems that force us to compete instead of co-operate.
  • We resist assessment systems that tell us how to teach, learn, and research, and ignore extracurricular learning.
  • We resist hierarchies that defer to credentials before and above the learned experience of teachers, students, and non-academics on the ground.
  • We resist being treated as consumers, and seeing our education treated as a commodity.

Other parts of the declaration cover the structural, governance and finance issues which drive the university, and it ends with this call:

Let us reimagine our curricula together. Let us unite to create the accessible, creative, and democratic universities that we can only achieve together.

The occupation’s web site is here, with some great blog posts, and contact details for those who want to follow up, drop by, or support their work.

Finally, the occupation has also started an open googledoc to which anyone can contribute. The section on Education and Assessment is excellent, and at the time of writing contains the following points:

  • Students involved in designing and updating courses and degree programmes
  • Student participation on defining, diversifying and decolonising syllabi – working with Liberation groups and projects such as Project Myopia
  • Empowering tutors and groups of students to make decisions about accommodations within their courses (eg extensions, alternative assessment)
  • Personalisation of the setting + submission of coursework to fit individual needs
  • Possibility to submit drafts etc
  • Relaxing anonymity rules to do so
  • Attendance and contribution in tutorials removed as a part of course assessment
  • Joint degrees
  • They should focus on overlaps/true joint aspects rather than being two separate single degrees with little communication between them
  • Staff contacts particularly for joint degree courses
  • Community-building (e.g. classes, socials?) for specific joint degree programmes
  • More flexibility within degree structure and information about changing degrees
  • Fewer (no?) requirements for taking courses within certain “subject areas” – too-specific DPRS requirements
  • Creation of an open/flexible degree
  • Smaller tutorial sizes
  • Pedagogical training for lecturers and tutors
  • Minimum hours/rigor TBD – not just a one-day workshop!
  • Diversify education >> not relying solely on massive lecture halls
  • Recording and publishing all lectures
  • Postgraduates should not be required to teach completely outside of their discipline
  • Valuing excellent teaching staff who are not researchers
  • Sanctuary Campus – the university must not be complicit in Home Office regulations (eg re: visas and contact hours) or policies such as Prevent
  • Openly reject such policies
  • Publishing “Contact Points,” or engaging in discussion with students on Tier 4 visas rather than having immigration officers being completely separate from all academic staff and not knowing any of the students
  • Recording and publishing all lectures (asap)
  • Timetables
  • Exam timetables released further in advance
  • Course timetables released further in advance (minimum 1 year?)
  • Exams to be sat in the space (and time?) you take the class
  • Increased transparency on moderation and feedback
  • Focus on quality rather than speed of feedback

Near Future Teaching Think Tank: Vets

On 18 January 2018, we were delighted to welcome 17 students at various stages in their training to the Institute for Academic Development.

The students were primarily from the University of Edinburgh Veterinary Programme at The Royal (Dick) School of Veterinary Studies. They came along to attend a Near Future Teaching Thank Tank event.

The format for the event was three short talks or ‘provocations’ detailing possible developments in the future university, which would be followed by a group challenge being set. The group would then be split into teams which would respond to the challenge.

The first talk was by Dr Catriona Bell, and was called ‘No More Lectures – more time to think’. Catriona noted that lectures are traditionally ‘didactic and linear’ and that it could be difficult for students to remain engaged throughout. By the time the typical 50 minute lecture is combined with making notes and revising, the total time cost is usually 3-3.5 hours, and she asked whether this was the most efficient use of student time.

Her provocation was that in future we eliminate lectures completely, increasing flexibility and using other approaches such as the flipped classroom to enhance and develop a more personalised learning experience.

Next up was ‘Competition, analytics and student league tables’, by Dr Jeremy Knox. Jeremy spoke about the ‘datafication’ of society and asked – if we have all this big educational data, what can be done with it, or more importantly, what SHOULD we do with it. He promted us to consider ‘openness’, ‘prediction’ and ‘attention’ and described some of the benefits of data sharing in these areas, however he also pointed out that there may be a tendency for data to be used to control and reduce. His provocative questions touched on the following:

  • Openness: Is your data really you? Who owns student data? Who should see it?
  • Prediction: Is a future without failure a good future? What is the educational value of mistakes?
  • Attention: Should students in classes be scanned for attentiveness? What if students were punished for not paying attention?

Finally we had Erin Williams on: ‘Getting rid of the bodies – cadaver-free anatomy teaching’. Erin asked if we can use technologies such as 3-D printing and virtual reality to replace the need to cut up cadavers in the lab when learning veterinary skills. She talked about how these technologies have been used in the commercial world, such as in gaming, with great success and asked if this could be a way forward to a more animal-friendly, economical, healthy and flexible way of teaching in future.

Professor Susan Rhind then set our challenge for the workshop which was: ‘What is your fantasy veterinary curriculum and how will assessment work in your fantasy future vet school?’ The students split into 3 groups and had 30 minutes to debate and consider. They came up with rich and sometimes surprising ideas and responses to the provocations.

Group 1

In response to the first provocation to end lectures, Group 1 suggested a move towards structured small group teaching sessions but did say there was some value in live tutor contact via lectures. One student said she had skipped a number of lectures and still passed her exams, so in her mind that meant that lectures were not of particular value. They argued that the time spent overall on lectures was inefficient, but also made the point that they will be entering busy 9-5 jobs and that the preparation and rigour involved in attending lectures could be good training for full time employment.

They had a strong response to the second provocation regarding data and analytics and argued that they had been tested and pitted against their peers all their lives to get into the University of Edinburgh and that they felt they had ‘been through enough competition already!’ They felt there had been negative emotional consequences for many from the intense competition in schooling and said that now they are here, they should be taught without having to prove their worth all the time. They felt that assessment technology should be used by lecturers to find out what THEY are doing well or not well, rather than targeted at struggling students. They argued that academic knowledge is not the be all and end all of being a good vet and that academic performance does not necessarily reflect the ability to be a good clinician. The ‘at risk’ model of identifying struggling students could be useful to help these students, but should be kept private and used to provide support rather than being public and exposing which they felt would be degrading.

Finally, on the topic of cadavers, the students said that the technology on offer at the moment was not good enough to replace operating on cadavers, and the 3-D/VR technology on offer now is not good enough to support learning properly. They felt the public would not trust a vet who had not operated on a cadaver and that they already did not have enough contact with live animals during their study, let alone dead animals. One devil’s advocate in the room did mention that pilots are often trained in simulators and then fly with real people! They said that while some technologies could help with resources, they would not be a total replacement. 3-D printed skulls would mean that more students could spend more time examining the skull, but it might be more difficult to reflect the natural and important variation of nature. They asked how we would stimulate that spontaneous natural variation.

On the subject of lectures, the students argued that they would like to spend more time learning in hospitals and that effort and tenacity should get more weight than numerical assessment. In their ideal future university, people would graduate with ungraded degrees, teaching hours would be cut and there would be more time spent in teaching hospitals and supervisors would assess technique.

Group 2

Group 2 said that there was a difference between learning the fundamentals of anatomy versus surgical anatomy and that it is very different operating on live animals. They felt that there could be less or no use of cadavers when learning the fundamentals in pre-clinical work – skeletons and muscles could be learned on plastic cadavers and 3-D models, however they still would require cadavers  for the clinical training. This group felt strongly that they did not want data tracking and agreed with Group 1 that they had already faced their fair share of comparison and competition. They stressed that praise is important and does not need to be data/numbers-based (for instance, it could be a response to good client communication). They said that the Vet School does not say ‘Well Done!’ enough and that this type of praise can mean so much more than a distinction.

They argued for more smaller, ‘bite-size’ exams and felt that data could be used to flag up failing students and get help for them, but not to punish them. This group had already experienced flipped classrooms and stated that they are a huge improvement over lectures. Overall though they did acknowledge that it is impossible to cater for everyone and that the Vet School does a great job at balancing priorities.

Group 3

This group had some mixed opinions. As regards data, some felt this could be used usefully to improve the performance of lecturers, and that in the business world data will inevitably be used to track performance and help meet targets, thus it is important to get accustomed to working with it and in response to it. Others argued that we are already self-critical and compare too much and that data can be dangerous, that it is a way of a seeing a reduced version of a person on paper rather than conveying other vital skills such as good interpersonal skills. It could be a way to weed out people who might deserve a job but do not look like that on paper. One student mentioned that in some countries interview scores are released to the public by companies and that this can improve overall performance rates, but asked if we are prioritising outcome behaviour or welfare. She said that if you look at China, they are able to make technological advances because they can control performance via data, however if we make data public and get rid of anonymity, are we in danger of changing the way we look at failure and destroying our ability to make mistakes and learn from them?

On the subject of lectures, there were some mixed views as well. Some felt that lectures should be replaced with group sessions whereas some thought lectures should never be completely eliminated because some things can only be learned in a lecture format. That student said that contact with a lecturer is good and that you can ask questions of them in person. She had also learned a lot from working through cases at home and presenting them in small groups. They agreed with Group 2 that more little assessments along the way would be of use and make one value what one is learning more, and that after each lecturer’s series of lectures, the students should be able to give immediate anonymous feedback.

They agreed that cadavers were still needed but said that post-mortems could be used more within early years teaching to incorporate histology. One student said that she always remembers what ISN’T normal – those instances have more impact. Also with post-mortems, specimens are fresher and not full of chemicals. They did feel that a virtual system would be very useful before surgery in order to revise.

So overall it was a dynamic, fascinating and extremely provocative session. The teachers came away from the event inspired to rethink how they are teaching NOW, and the students could not stop chatting as they walked out into the night… into the future!

Jennifer Williams
Projects & Engagement Coordinator
Institute for Academic Development

Learning Analytics: What has data ever done for me?

Friday saw a Future Teacher event at the Moray House School of Education on the subject of learning analytics and its role in the future of the university. Much promise, much potential, and lots of messy, but promising developments.

The event was organised by Anne-Marie Scott of Learning, Teaching and Web Services, and the speakers were Dragan GasevicYi-Shan Tsai, and Jeremy Knox. There were approximately 20 attendees, a mix of mostly staff and some students, representing a range of fields on the campus: education, psychology, geosciences, law, biology, and more.

Dragan and Yi-Shan first provided context, polling the attendees as to their level of familiarity with learning analytics and their understanding of its definition. Answers varied considerably, suggesting a field that is still emerging in its scope and application. Most of us were, by any definition, novices in the field of learning analytics.

Dragan discussed the history of learning analytics and how it finds itself shifting from its original position as a deficit model (retention) towards something more proactive and formative (strengthening feedback loops, primarily). Some of the earliest work was discussed, particularly Signals at Purdue University and how it was an important, if ultimately critiqued, project.

Many of these earlier projects used dashboard models and a relatively small set of indicators to achieve some sort of impact: for Signals, 5000 students were identified as a sample and grouped according to three categories of high, medium, and low risk for failing a particular course. These three groups were translated into traffic lights, providing an easy way for teachers to recognise those in danger and presumably offer more or a different form of feedback. There was some success with this approach, but the feedback itself needed bolstering: the stoplight didn’t give enough feedback to change teaching practices.

There is a new emphasis in more recent projects on 21st century data skills, some sort of data literacy, data and privacy protection, and more. The principles are shifting as well: data is never complete, analytics can perpetuate bias, the necessity for humans always being in the loop, how and if projects should be scaled up, and more. Learning purposes vary dramatically as well in terms of quality, equity, personalized feedback, student experience, skills, and efficiency. A very complex tailoring of data to purpose and principle. This was where most of the discussion in the groups sat, this idea of tailoring and having a very specific feedback and guidance system in place, the need for bespoking this all to disciplinary or domain specific needs, a good understanding on how feedback can bolster or undermine student engagement and resiliency. Much to work through here.

Dragan and Yi-Shan transitioned to three applications, more or less in their infancy, and asked us to give them a try.
Loop, On Task, and LARC.

Loop is a learning analytics application that provides access to pageviews, access to course content, forums, and assignments, presumably plugging in via API to an LMS like Moodle or Learn. It tracks to some degree a student’s engagement record, scores for assessments, and more. Dragan referred to Moore’s transactional distance as we were toying with the application, and how some research suggests that depending on the context, increased faculty interaction may or may not lead to positive outcomes. Clusters, bar charts, and more, Loop felt both complex with Dragan emphasising that data can be interpreted in many ways, if done poorly can have a negative impact on effort and outcomes. Dragan pointed to research (Khan & Pardo, 2016) suggesting that student dashboards were mostly ineffective. Ultimately, these applications need to provide capacity for task specific language and appropriate levels of guidance: it can’t be merely summative feedback.

On Task took a different approach, dividing large cohorts of students into quartiles (or whatever cut was deemed appropriate), and drafting text feedback snippets for categories of feedback (particular answers, passages, outcomes, etc.). Categories are translated to set texts for feedback. Feedback is then given based on the quartile. Some degree of granularity while still being general enough to reach some level of scale. The feedback itself is devoid of numbers; it is just guidance. On Task seemed to have some merit for large course (MOOCs or other scaled course structures).

The OnTask Project aims to provide personalised, timely support actions to large student cohorts. The two-year project started in 2016 and is funded through a Strategic Priority Commissioned Grant by the Office of Learning and Teaching (OLT) of the Australian Government.


Jeremy Knox then spoke of the Learning Analytics Report Card (LARC), a project that asks: ‘How can University teaching teams develop critical and participatory approaches to educational data analysis?’ It seeks to develop ways of involving students as research partners and active participants in their own data collection and analysis, as well as foster critical understanding of the use of computational analysis in education. It captures data from an individual student’s course-related activity, and presents a summary of their academic progress in textual and visual form.

However, there is some customisation available here: to choose what is included or excluded, when the report is generated, and how it might be presented. It attempts to both empower the individual student and surface some of the hidden power structures that increasingly underpin and govern educational decision-making (like algorithms).

The first draft of the Learning Analytics Report Card interface is complete, and is ready for testing with Moodle data and the phase 1 analytics. The interface is behind the EASE login, which will restrict access to the identified pilot …


Virtual Reality event at the uCreate Studio: the role of VR in reducing risk and building empathy

A recent event organised by our colleagues at the Institute for Academic Development for the Future Teacher initiative explored the use of virtual reality currently and its potential use for teaching and learning in the future.

It was held at the uCreate Studio, the University of Edinburgh’s Community Makerspace. The event was kicked off by Matt Ramirez of Jisc. Matt is the Futures senior innovation developer at Jisc working on a host of projects including AR-Sci, a 3 year EU funded project aiming to enhance science secondary education and ultimately inspiring students to work with STEM in their future careers.

Participants were from across the university and represented potential for a host of disciplinary and interdisciplinary uses of VR: Social and Political Science; Philosophy, Psychology, and Language Sciences; Design; Health; Engineering; Geosciences; Veterinary Medicine; Law; Social Work; Maths; Informatics; Innovation Studies & Biological Sciences; Digital Skills and Training; Population Health Sciences; and Education. The range alone suggests a technology that is perceived to have significant potential for teaching and research across the university.

Matt walked us through the use of VR and how it has evolved over the years from early 1990s sci-fi to now, highlighting its movement through the Gartner Hype Cycle over the years culminating in its emergence in 2017 out of the trough of disillusionment into the slope of enlightenment. VR didn’t take off initially largely due to a lack of appetite, a lack of portability, and a general lack of content. There were physiological issues: in earlier iterations, everything was in focus leading to difficulty focusing on any one thing in particular; there were cases of nausea and discomfort. Matt pointed out that he rarely goes longer than 20 minutes in a VR session at any one time.

Matt was careful to place VR amidst a larger Mixed Reality (MR) continuum from the physical environment to augmented reality (AR) to augmented virtuality (AV) to virtual reality (VR).

While this event focused on VR, for teaching and learning we can see a range of potential across the larger continuum. 2017 sees VR in a progressive space: use cases are beginning to emerge in museums, in medicine, and beyond; accessible content (Sketchfab, in particular); the use of haptic feedback in simulations, explorations of Tutkanhamen’s tomb with Oculus, and the rise of very low-priced headsets like Google Cardboard, along with some openly and quite visible content like the Guardian’s VR content.

We discussed potential use cases for the university itself. VR as planning tools for the development of learning spaces. Virtual field trips to support disciplinary activity. Virtual apprenticeships where students can use VR to explore potentially hazardous experiences: surgery, disaster response, nuclear hazards, and more.

A study was mentioned that pointed to a study on racial bias with VRand how the results show that adopting a certain virtual race, regardless of the real one, has an effect on certain unconscious behaviours towards virtual people with the same color. Stanford is pursuing a line of research on this racial dimension as I write.

We then cascaded into the UN short VR film Clouds Over Sidra, which follows a twelve-year-old girl named Sidra in the Za’atari camp in Jordan — currently home to 84,000 refugees from the Syrian civil war.

Themes emerged here that could inform both our values driving forward with this technology and potential use cases, and arguably the most tangible were perception and empathy. How does what we see feed into what we believe to know, how that confirms existing bias. How could VR develop empathy, to allow us to critically explore the role of empathy on untangling some of these seemingly intractable issues? Experiencing life as a refugee waiting for asylum, experiencing virtual immersions in autism, perceiving the world as an infant might, all available now in VR. All potentially shaping our shared vision of the future of digital education here at the university. Elaine summed it up nicely.