I had a pleasure to listen to Ustream of LAK11 conference. It was cold weather there but I sat in my warm room at home. I recognized that I have always (online teacher ten years) been interested in the analytical possibilities of the learning platforms which I used in facilitating learning. I used to offer group reflections and feedback to my students all the time. And now was first conference about these topics. Doug Clow blogged almost all, never seen so perfect conference blog, thanks to him.
David Wiley grasped key questions, I appreciate it. Are we “Letting the data tail wag the theory dog” ?
- Interpretation != science?
- Confusion of science with positivism: Social scientists have “physics envy”, quantity > quality
- Educational measurement: what does he/she know? Research that is mediated by observation – can’t crack open the learner’s head … People engage in behaviours, and we take those behaviours.
- Observable behaviour online is expressed in restricted vocabulary to key presses and mouse clicks.
- Westerman’s argument: Quantitative inquiry is interpretive.
- Can we call it success, if we can predict, but we don’t understand why?
- If not positivism… then what? Hermeneutics – meaning and interpretation
- Problems with metaphor – information processing model – only works when the brain is operating like a computer. Breaks down when creativity is involved
- Reductionism – “nothing more to be said when neurophysiology has had it’s say”
Behaviour in context, social practice: How do we observe behaviour in online environments? We need
- Structural equation modeling
- Multilevel data structures
- Continuous, longitudinal measures
- Tasks nested within practice
Using Learning analytics is an ethical activity .
David said what I wanted to hear. After his presentation we heard many reports which tried to proceed in describing network (mathematical) models and many quantitative measurements. I could not follow all because I don’t know enough .. know only psychological and educational sciences. Modeling behavior is collaborative work, very challenging. Some examples here:
Xavier Ochoa is a Principal Professor at the Faculty of Electrical and Computer Engineering in Guayaquil Ecuador. Learnometrics was the theme and he pondered how to proceed from empirical rugularities to mathematical models. How to understand influence, produce useful metrics? Learning repositories are not working because growth is linear, not exponential like youtube, why so?. Slides here. Data mining <analytics < research, what are the chains from one to other? Similarities and differences between LA and educational measurement, image.
Dan Suthers - Unified Framework for Multi-Level Analysis of Distributed Learning. Slides here. Interesting concepts and questions: Networked individualism? Ties, sequential analysis of interactions? How people live through processes to insight?
Second day of LAK11 conference was more practical. It was women’s day, first was men’s 
. But of course there was a man as a key lecturer: Erik Duval, Attention please! Attention metadata and interaction. Program says:
Attention metadata capture how people interact with resources and with one another. We can make use of the patterns in attention metadata to help learners and teachers cope with the abundance of learning resources through recommendation techniques. By visualizing the patterns, we can make teachers and learners more aware of what they do. An important concern is openness, so that we can detect patterns across the boundaries of technical and organizational systems and ensure data portability that prevents system lock-in.
Erik Duval is a professor of computer science at the Katholieke Universiteit Leuven, Belgium. His research focuses on management of and access to data and content. Typical applications come from the fields of technology- enhanced learning, music information retrieval, and “Science2.0.” It possible to follow so much about our living that it is dangerous. How to work for benefit of people, not to spy or control. It is an ethical question really. Awareness about one’s learning is the key. Slides here.
Caroline Haythornthwaite from University of British Columbia, Vancouver. Her theme was Learning networks, crowds and communities. A copy of the program:
Who we learn from, where and when is dramatically affected by the reach of the Internet. From learning for formal education to learning for pleasure, we now look to the web early and often for our data and knowledge needs, but also for places and spaces where we can collaborate, contribute to, and create learning and knowledge communities. This talk explores the emerging landscape of online learning with attention to the structure and dynamics of online learning networks, crowds and communities. With reference to social network informed studies of learning, the talk explores the different ways learning emerges from social interaction, how structures and motivators differ across ‘lightweight’ (crowd-based) and ‘heavyweight’ (community-based) peer productions, and where an analytics perspective can be used to follow, support or enhance learning outcomes.
Many research projects were presented about learning in social contexts. I am too tired now to continue, have already surpassed myself and need a break. It was fine to hear from many research projects which are going on in Europe and other continents. If you are interested in learner analytics, please read the program. No sense in copying more here 
I will write about the presentation of Rita Kop and Helene Fournier in another post. It is the only one I know as a student in Plenk2010 course.
[...] Posted on March 4, 2011 by suifaijohnmak| Leave a comment Great to learn about Heli’s views on Learning Analytics. I share many of those views with her, in particular the “ethical [...]
Thanks Heli and David Wiley – I love the expression “physics envy”, although I think its rather sad, as a social phenomenon, and rather limited it its view of physics (see the last sentence of this comment).
To the point. I would love to know how learning analytics works (i.e. without the physics envy). I am in principle enthusiastic about Social Network Analysis, but haven’t been able to take the time to get into it, yet. From what I have seen so far, there is much to be gained, but there is still something at the centre of it all that keeps worrying me, like a pebble in my shoe, namely:
The network analyses I have seen all look so 2 dimensional (and three dimensional versions dont necessarily help). I dont think it is the ‘flatness’ that worries me really, but rather the reduction to neat, ‘one-dimensional’ nodes (rather like ‘points’ which have position by ‘no’ dimensionalilty!)
In my own earlier work on media and political analyis, I quickly realised that I had to adopt a ‘post-modernist’ theoretical framework, to accommodate ‘dispersed subjects’, etc, etc. In more recent work, on Affordances for Learning, I took a much simpler approach, and just asked people to tell me stories about how they had learnt something that was important to them.
The result was very ‘rich descriptions’ of what was actually happening, in which learning and identity were so intermingled as to be almost ‘one’ thing. (Etienne Wenger says it so much better, of course). Further, none of these stories were dealing with one identity, but rather many identities, and lots of crises, negotiations, re-alignments, etc between the identities that they were exploring and adopting, and the consequences of buying in to discourses, communities, professions, organisational politics, families, social groups, etc, that the particular ‘identiies’ implied.
So … I long for a method of describing and analysing networks of learning in which each node is a mini-ecology of ‘identities’ and ‘learnings’. Single, static, sutured nodes look so, well, Newtonian?
Hi Roy and great thanks for commenting!
I cannot assess all that was said in LAK11 conference because I had to sleep when they had afternoon. Wiley interested me because he used the concept hermeneutics and dealt with ethical and methodological principles. On the second day many were asking the purpose of LA. Data can be used for becoming awareness about what is happening and it can be used to support critical thinking. There are possibilities but most of LA will be numerical mathematical (physics ideal) modeling. A lot of doctor dissertation coming in near future.
I am waiting for the recordings of the conference in order to check more. Some conference about SELF in Brussels soon… http://quantifiedself.com/conference/ what is this?
Erik Duval (Antwerpen) is worth listening again. He told how we soon can ask Google who I am. It is good for old people
Duval wanted to use all data for benefit of people but how it can be done?
Are you in Diigo? I have sent links there, if we become friends you can see my links but I am not sure they will help. Good to know what others are doing ..
I have to read your wiki, it helps me more than LA