An animation illustrating the principles of personalisation for accessibility. Produced by the EU4ALL project in 2011.
The other presentation I attended on day 1 of the festival was that given by Prof. David de Roure of the University of Oxford. He spoke on “Big Data for the Social Sciences“, which I hoped would be relevant to my own work on Learning Analytics. This blog post is my notes from his talk.
How does technology get used in research?
-> What is this new “big data” and what does it tell us?
- Big data does not respect disciplinary boundaries
- Data has been around a long time
- There is a lot of “hype” around big data that has led to inflated expectations of it
- Can consider 2013 as the year we sort to define big data and 2014 the year we begun to use it effectively
- It is big data because of both the velocity and volume of the data being generated
- “Data deluge” is now a phenomenon across the disciplines
- In the past analysis moved from the universities to business, now it is from the business world to the universities.
- There is huge unsatisfied demand for “data scientists”
- Mores Law vs The Big Social
- We use digital tools because it is the ecosystem – Research 2.0
- What is the relevance of Social Science to Big Data?
- We need to think through the implications
- RCUK’s definition of “big data” is: big enough that we can’t deal with it as we did before
- Why do we want it?
- To do things in new ways
- To do new things
- e.g. Twitter data – we can look at the evolution of social processes in real-time
- We need the expertise of those from classical Social Science
- e.g. food vs consumption
- can obtain new data from new sources (e.g. supermarket loyalty cards)
- We can use different data sets to correlate
- Real-time uses of big data, e.g. Twitter
- spread of infectious diseases
- Visualisation can lead to better analysis
- Underpinned by available infrastructure
- Wikipedia is an example of a social medium
- behaviorally it is socially constructed
- different in different countries/languages
— end —
A little humour as light relief. Open the image and enlarge to view the jokes or visit the source: http://www.tickld.com/x/20-jokes-that-only-intellectuals-will-understand
I am currently working on an internal project proposal: Learning Analytics for Disabled Students in STEM subjects (LA4DS-STEM). Hopefully it will run from April – December 2014.
The LA4DS-STEM project will review the potential of Learning Analytics in higher education, specifically in STEM, and with an emphasis on supporting disabled students and facilitating accessibility enhancements.
Learning Analytics is defined as the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. The LA4DS-STEM project will specifically explore the following STEM application areas for Learning Analytics. A key output of the project will be an external funding bid for a larger-scale collaborative project. The work of LA4DS-STEM will inform pilots in this project. Provide envisaged benefits are confirmed, this should lead to enterprise level implementation within the OU and across HE.
The findings of the LA4DS-STEM project will be disseminated, firstly throughout the Science and MCT faculties, then to the wider university. External dissemination will highlight the OU’s lead in this field.
I have spent most of the morning interacting with reps of the various exhibitors here. Now to rest my legs I have settled down in Hall 1 for the keynote by Sugata Mitra, Prof. Of Educational Technology at Newcastle University.
Notes from Keynote
Sugata was the originator of the ‘Hole in the Wall Experiment‘. He plans to review the last 15 years of work and review trends.
The hole in the wall experiment
ATM like computer in a hole in the wall. They (the slum kids in New Dehli) did not know English and the interfaces were in English. Street children were browsing within 6 to 8 hours and teaching each other. Conclusion groups of children left with a computer would reach the level of the average office secretary in the West in about 9 months. [Video shown of this work].
The children’s achievement of their proficiency happened because not despite of the absence of an adult teacher/supervisor. After 4 to 5 months the teachers reported that their English was much improved. Discovered they were using a search engine to find quality content and copying it down on to paper. Question – why we’re they copying down the right things? They seemed to know what they were writing. Then gave them educational objects. Working in groups they seemed to be able to locate the right information and select it. Groups of children could reach educational objectives of their own if they wished to. People supposed that when got to in depth learning or skills acquisition they would need human intervention. However, could not find the limits of this learning.
In England turned the hole in the wall upside down. Created the chaotic environment of the hole in the wall inside the clasroom with just a few computers. Made up some rules: free discussion and free movement allowed. In period 2008-2010 this led to the descriptor of self- organising learning events. E.g. For 7 year-olds “why is a polar bears coat white”. Given the the choice between a hard and easy question the children opted for the harder questions. They were able to do GCSE questions about 6 to 7 years ahead of time. Called these Self Organising Learning Environments (SOLE).
In other countries around the world similar results. C.F emergent phenomena or self ordering or spontaneous order in the Natural Sciences. Tested limit of this method in Southern India. Research Question: can 11 year-olds learn the process of DNA replication? Experiment was a failure but the students self studied why DNA replication sometime went wrong causing disease. Pre and post testing showed those working 10 years ahead of their time. Used a non scientist and the method of the grandmother. Using an older adult to stand behind and encourage.
[Slides: Schools in the cloud]
Constructing 7 pilots trying to level the playing field in primary education comparing India with UK.
Experience with older students? – Used to think method applied to ages 6 to 14 but beginning to show that it is not restricted to this. Experiences reported with 16-18 year olds, in FE and he is using SOLE approaches in his university courses.
Here are a few random quotes I noted down while at the JISC Digital Festival 2014 in Birmingham this week. Apologies for when I didn’t note who said them.
Academics need to stay on top of the analytics movement and not get pushed around by it!
A related to the above:
How does technology get used in research -> What is this new “big data” and what can (can’t) it tell us?
[Prof. David Rowe, Oxford University]
From a different perspective:
Research and Teaching have now diverged at the Universities
From the presentation by the originator of the “Hole in the Wall Experiment!:
Children will learn to do what they want to learn to do!
[Sugata Mitra, Prof. Of Educational Technology at Newcastle University]
I will add to these as I review the archived talks that I did not attend which you can do by going to: http://www.jisc.ac.uk/events/jisc-digital-festival-2014-11-mar-2014/expert-speakers
I attended the JISC Digital Festival in Birmingham, UK. This blog post is a set of notes from Day 1 (11-March-2014).
Keynote – Diana Oblinger (CEO Educause)
“Why are we still talking about this digital stuff?”
It is about 25 years since we moved from the analogue world to the world of society, education and work being based on digital computing technologies. But we still use the term “digital” because either we see it as something special or we get concerned about “man vs machine”. It is not just about digital – it is about demographics. In US only 17% of learners are traditional college students. Many are now studying as adults who may not have previously had a positive educational experience. This changes what we need from education and “how” we deliver that education.
When you are engaged you learn better – leading to the hypothesis that face-to-face is always the best solution. But face-to-face often just presents text on a screen (a board or projector screen). However, digital technologies allow greater interaction between students and between them and data about what they are investigating. We want to promote deep learning and develop skills through practice. In these online practice environments not only is there student activity but there is data coming back from the students’ interaction. When have massive amounts of data can begin to realise the long-held goal of personalised learning. This can lead to adaptive learning systems.
There are different types of students. Two example profiles:
- ROI Skeptics – not sure education will be worth the effort; external barriers; lack of vision; juggling work and family etc.
- Highly motivated students who always expected a college (university) education
Students need help with their complicated lives to be able them to give education the right priority. Case management – dealing with the student holistically; early alert programmes (for e.g.) have significant and lasting impact. Some students are blissfully unaware that they might be at risk of failing the course. Here lies a potential for learning analytics. However, beyond that teachers need support on how to deliver those messages to the student, e.g. mobile phone text message? (BTW 43 words seems to be about the right length of message.)
Too much choice can be the enemy of student success if they choose courses they are not prepared for or at too high a level for where they are in their studies. (C.F. consumer choice problems). Software tools are emerging to address. Example shown of a tool for students and their advisers as they seek to support them and their choices.
IT in education can spawn over complexity and disorientation. Interconnected elements:
Part of this is coming from outside our institution – e..g. MOOCs; large-scale commercial educational providers. Many customers (students) feel they are over-served by the traditional university system. Now a big puss on competency based education – prove you have particular skills irrespective of where you acquired them. However, current IT systems just focus internally to the educational establishment.
Time is an opportunity cost. Example “Direct to Degree” from University of Kentucky, enabling students to rapidly acquire a degree and reach their employment goals. If students never go to campus where do you provide their support? Another example from College for America that provides the support in the workplace. Can be low-cost models – e.g. 1 student completed degree in 3 month at cost of $1,350.
There is lots yet to do in the digital environment. Need to design from the digital and with man & machine not man vs machine in mind. A great frontier for all of us.
- What does it take to exceed expectations in this digital world?
- What capabilities (personnel, budget, skill) are required to deliver the value from IT?
- How do we optimise for a digital future??? – Answer yet to be told!
Response and Reflections on keynote
Prof. Paul Curren VC at City University
Was in a situation of ailing IT and with many mismatch between demand and supply issues. (Here the focus is on education not research or admin. but had to address all three). How to develop a personalised experience for the students and enable academic staff to give the support they want to provide? Further, how do we enhance the educational experience? How can we do this in the context engendering a community experience. City has multiple campuses now.
Trying to achieve a clear vision (2016) of where wanted the university to be. Investing in academic staff, IT and estate. Focused on having sector leading IT areas in education. In 2010/11 large IT service, 142 IT staff, £ 14.6 million budget. But, very devolved, often software developed in-house and not fully documented and big problems occurred when staff move on.
Formulated a strategic plan with projects each under a PVC.
- Engaging IT services around the student (e.g. brought in Moodle, Office 365) and organised around the concept of “The One City”.
- Sourced commodity from external suppliers
- Now spending less on IT, less staff but more junior staff at the coal-face and less IT managers
- Standard high quality equipment in the student spaces
- Listened to what students, staff and professional services members wanted
- Moved core services to a central base in London
Where are we now?:
- The student registration system now stabilised
- Monitor student access to Moodle to check on student engagement (reduced drop out rates)
- Early initiation to ensure things were scalable and multi-platform (including mobile to enable work while travel)
- Provided easy access to student records
- Using the big providers (e.g. SAP) linked to increasing in-house skills
- IT staff now viewed differently – previously seen around their skill base (e.g. UNIX) – now seen around their relationship management and knowledge of integrating systems
Challenges for staff:
- Academic staff need to move seamlessly between a “digital” and “real” world – provided a lot of training
- IT staff – understanding their new role around the user/systems integration – again investment in training
- Outsourcing and agreeing the boundaries
- On a journey
- Downtime reduced
- Student Satisfaction Scores with IT increased
The key points that stood out for me from these two linked presentations were:
- We need to accept digital as being here and now and move to a “Man & Machine” mindset and not a “Man vs Machine” one
- Systems integration is key and outsourced systems are often the cost-effective way to go
- IT support staff need to see their role as focussed on the users (students, academics, admin staff, management) not on a particular area of technology that forms the core of their skill set
- It’s a ‘win-win’ situation of better services at lower cost that is achievable this way
A personal reflection from me:
The IT systems should be the servants of the educational, support and management processes not the other way round!
A beautiful poem from my sister-in-law about her autistic son. I read it with a smile because I know and love him!
Well, it’s nearly ten months since I last posted. There is a reason for that.
In June 2013 the husband of a very good friend of mine passed away. My friend and her husband have been a huge support to me over the years and I truly value their friendship and interest in my adventures.
This gentleman was a journalist and, at times, had tried to encourage me into journalism but I resisted believing that this was not the right path for my life. Therefore, as a tribute I decided to fulfil a secretly held desire to write creatively and last October I began a Creative Writing course with the Open Univserity.
The course hasn’t been easy and, at times, it’s been totally discouraging but I am now halfway through and considering signing up for Advanced Creative Writing in October (eek!). I’m hesitant to make my writing public but my…
View original post 164 more words
Today I have been writing a contribution for a paper requested by the Open University’s Ethics Committee about ethics in Learning Analytics. This blog post is adapted from that.
There are two broad use case scenarios where learning analytics approaches may benefit disabled students:
- Targeting support to disabled students or their tutors (Support)
- Identifying online activities that seem to be problematic for some disabled students (Accessibility)
As far as we are aware these approaches are yet to be deployed anywhere world-wide but we are actively researching them here at the Open University where we have approximately 20,000 disabled students. We envisage that if the early promise of this research holds up, deployment on about a 3 year horizon. These approaches, especially the accessibility one, are reported in more detail in Section 5. of Cooper et. al. 2012.
Firstly, a few definitions:
IMS Global Learning Consortium offered education-specific definitions of both disability and accessibility when introducing its work on the development of technical standards for accessibility in e-learning:
[…] the term disability has been re-defined as a mismatch between the needs of the learner and the education offered. It is therefore not a personal trait but an artifact of the relationship between the learner and the learning environment or education delivery. Accessibility, given this re-definition, is the ability of the learning environment to adjust to the needs of all learners. Accessibility is determined by the flexibility of the education environment (with respect to presentation, control methods, access modality, and learner supports) and the availability of adequate alternative-but-equivalent content and activities. The needs and preferences of a user may arise from the context or environment the user is in, the tools available (e.g., mobile devices, assistive technologies such as Braille devices, voice recognition systems, or alternative keyboards, etc.), their background, or a disability in the traditional sense. Accessible systems adjust the user interface of the learning environment, locate needed resources and adjust the properties of the resources to match the needs and preferences of the user. (IMS Global 2004)
Thus disability is not an attribute of a person, but an attribute of the relationship between that person and the tools they are using to meet their goals; in this case online learning. And, accessibility is a property of the learning resources that makes is usable by all, including those traditionally labelled as disabled.
The principle ethical dilemma when approaching learning analytics and learners who might experience a disability in the context of online learning is:
- For what purpose has the individual students declared their disability to the university or other educational establishment, and is this consistent with how that information is to be used in the learning analytics approaches?
No other literature has been found explicitly addressing this issue. So this blog post might represent the first public statement of the problem.
At the Open University students who declare a disability so that they can be provided with support in their studies. This is consistent with the first use case scenario (Support). It is a moot point if it is consistent with the second use case scenario (Accessibility). More critically at this stage of development of these approaches it is not obvious that it is consistent with research into these approaches. Is it ethical to use historic or current data relating to students with disabilities to undertake research into future approaches of applying learning analytics?
Cooper, M,Sloan, D., Kelly, B., and Laithwaite, S. (2012) A Challenge to Web Accessibility Metrics and Guidelines: Putting People and Processes First, Proc. W4A2012, April 16-17, 2012, Lyon, France. Co-Located with the 21st International World Wide Web Conference.
IMS Global Learning Consortium (2004), IMS AccessForAll Meta-data Overview. Available online at: http://www.imsglobal.org/accessibility/accmdv1p0/imsaccmd_oviewv1p0.html (accessed 17/02/14)
Subject to funding and acceptance by the programme committee I am hoping to attend LASI2014 and present on Learning Analytics to Support Disabled Students.
See on www.solaresearch.org