Aug 182015

All of this week, whilst I am mainly working on Managing Your Digital Footprint research work, there is a summer school taking place at the University of Edinburgh School of Informatics on Security and Privacy with several talks on social media. This afternoon I’ll be blogging one of these: “Policing and Social Media Surveillance : Should We Have any Privacy in Public?” from the wonderful Professor Lilian Edwards from University of Strathclyde and Deputy Director, CREATe.

I come to you as a lawyer. I often say what I do is translate law to geek, and vice versa. How many here would identify themselves as from a legal discipline (about 10 are), I know most of you are from a computer science or HCI area. What I will talk about is an overlap between law and computer science.

So, a nice way to start is probably David Cameron saying: “In extremis, it has been possible to read someone’s letter, to listen to someone’s call to listen in on mobile communications,” he said. “The question remains: are we going to allow a means of communications where it simply is not possible to do that? My answer to that question is: no, we must not.

I’m going to argue that encryption, privacy, etc. is a good thing and that there should be some aspect of privacy around all of those social media posts we make etc. Now, what if you didn’t have to listen to secret conversations? Well right now the security services kind of don’t… they can use Tumblr, Facebook, Twitter etc..

So, a quick note on the structure of this talk. I will set some context on open source intelligence (OSINT), and Social Media Intelligence (SOCMINT). Then I will talk about legal issues and societal implications.

So, SOCMINT and OSINT. In the last 5-7 years we’ve seen the rise of something called “intelligence led” policing, some talk about this as the Minority Report world – trying to detect crime before they take place. We have general risk aversion, predictive profiles, and we see big data. And we see “Assemblages” of data via private intermediaries. So we see not only the use of policing and intelligence data, but also the wide range of publicly available data.

There has been the growth in open source intelligence, the kind of stuff that easy to get for free, including SOCMINT – the stuff people share on social media. You can often learn a great deal from friends graphs, their social graph – even with good privacy settings that can be exposed (used to always be open) and that is used in friend of friends analysis etc. The appeal of this is obvious – there is a lot of it and it is very cheap to get hold of it (RUSI and Anderson Report 2015), 95% of intelligence gathered is from this sort of “open source” origins, the stuff that is out there (ISC 2015). There have been a number of reports in the last year with increadibly interesting information included. Another report stated that 90% of what you need to know if from this sort of open source, and it’s great because it is cheap.

In terms of uses (Barlett and Miller 2013) are various, but worth noting things like sentiment analysis – e.g. to predict a riot etc, apparently very useful. Acquiring information from the public – have you seen this robber, etc. is very useful. Horison scanning is about predicting disturbance, riots etc. We are also seeing predictive analytics (e.g. IBM Memphis P.D.; PredPol in Kent) and that is very popular in the US, increasingly in the UK too – towards that Minority Report. Now in all of these report there is talk of predition and monitoring, but little mention of monitoring individuals – but clearly that is one of the things this data usage enables.

These practices are rising policy challenges (Omand 2012) of public trust, legitimacy and necessity, transparency. And there is the issue of the European Convention on Human Rights: article 8 gives us the right to a private life, which this sort of practice may breach. Under that article you can only invade privacy for legitimate reasons, only when necessary, and it the level of invasion of privacy can only be proportionate to the need in society.

So, looking at what else is taking place here in contemporary practice: we had the Summer Riots in 2011 where the security services used #tweets, BB texts etc. and post riot reports really capture some of the practice and issues there; Flickr stream of suspect photos leading to 770 arrests ad 167 charges, Facewatch mobile app During the 2012 Olympics the police wanted to use social media data, but basically did not know how. So issues here include police managerial capacity; there is sampling bias (see “Reading the Riots”) as Twitter is a very partial view of what is occuring; And there is human error – e.g. in crowdsourced attempts to identify and locate the Boston Bombings.

So I want to talk about the possibility of using public social media posts and question whether they have any protection as private material.

An individual tweets something, says she didn’t intend for it to be seen by the police, commentators online say “What planet is this individual on? Her tweets are public domain” and that is the attitude one tends to see, including in the law courts. e.g. “a person who walks down the street will inevitably be visible” (PG v UK 2008 ECt HR). In the UK that seems to be the standard perspective, that no reasonable expectation to privacy when expressing yourself in public.

In the US there is even less privacy of social media posts, e.g. see C.f. Bartow (2011) who says “Facebook is a giant surveillance tool, no warrant required, which the government can use… with almost no practical constraints from existing laws”. There is no idea of privacy in the US constitution effectively.

You’d think that the EU would be better but where are our traditional concepts of when “reasonable expectation of privacy arises?” Is it in our body, our home (Rynes ECJ 2013), car, what about our data “relating to you” vs “public sphere” (Cf Koops).

So, what are the legal controls? Well the Data Protection law seems obvious but there are strong UK exemptions around detection and prevention of crime – so there is no need for consent.

How about the European Convention on Human Rights article 8, the right to a “private life”. So, the start of my arguement is Von Hannover ECtHR (2004) about intrusion by press rather than police – Princess Caroline of Monaco was being followed by the press in all of her activities. The Court says, seminally, that this is absolutely an invasion of her private life – even though she is a public figure in a public sphere. So we have a concept of privacy being beyond the bounds of your home, of being able to have a right to privacy when out in public.

Now, that was an important case… But it hasn’t had that much impact. So you have cases where the police take photos of people (Wood v Metropolitan Police 2008) or CCTV (reapplication by JR38 for Jusicial review (2015). In the case of Wood a serial activist was going to a corporate AGM, expected to cause trouble, so police followed him and photographed him. Judge said that he was an activist and well known, and could expect to be followed. The arguement was that the image was a one off thing – that not part of ongoing profile.

The most recent case, which was in Northern Ireland, was caught on CCTV during the NI equivelent of the London Riots. The person in question was 14 year old and images were circulated widely, possibly including to the Derry Journal. Again he uses, but in an interesting way. There are at least three judgements.

Lord Kerr says “The facet that the activity… Is suspected to be criminal… will not alone be sufficient to remove it from… application of article 8”. That’s a big deal – suspicion of criminal activity isn’t enough for your rights to be exempt. However in this case the second test, whether the intrusion is justified, was found to be the case. And they took very little time to decide it was a justified act. Under proportionality of rights of individual, and rights of community to protect itself, they felt this intrusion was justified. They say that he’d benefit too – saying that that 14 year old might be diverted from a life of crime. They lay it on a bit but they are under pressure to justify why they have not stigmatised this youth through sharing his image. So, an interesting case.

So, there is some expectation of privacy in public but even so interference can be justified. Interferance must be justified as necessary, proportionate and according to law. But security usually seems to win in UK? (Wood, JR38). Even if no reasonable expectation of privacy, may still be part of “private life”. But all of this assumes that you know you are being surveilled, of your information being accessed. But you may not know if your data is being used to build up profiles, to build up an airport stop list, etc.

Now, in response to Snowdon, we have something called RIPA – an envisioned “digital” scheme to cover surveillance of personal data. This scheme covers real time interceptions of emails, warrant from secretary of state needed. But social media isn’t part of this. They just seem to be making up how they manage that data.

Now I want to argue that use of SOCMINT shouldn’t have any special excemption…

Demos in 2013 asseted “open” SOCMINT collection (and processing) needs no authorisation of any kind. Why? They argued that no expectation of privacy so long as user new from T&C that public data might be collected, especially via API. I think that is just egregiously stupid… Even if you believed that it would apply to the platform – not for the police, the rest of the world, etc.

The other argument is the detailed profile argument. And that is that even if we admit that this material is “public” there is still part of ECHR which is that detailed profiles of this sort need to be treated with respect – that comes from practices by the Stasi and concerns around the possibility of a secret police state, Juris Prudence (Rotaru v Romania) covers this.

So, my perspective is that there is a real difference between structured and unstructured data… Even if in public is SOCMINT an autoamatic dossier? With Google most of the internet is a structured dossier. With that in mind ECtHR case law has seen structured dossiers maintained ver time as a key threat – Rotaru v Romainis dictum: “public information can fall within the scope of private life where it is systematically collected and stored in files held by authorities”. So does the Rotaru distinction between structured data in files held by police, and unstructured data hold up in the age of Google and data mining (e.g. Google Spain (ECJ 2014), UK RIPA case (2015).

As we move into the internet as the main site for key publishing of data, and as the internet of things and smart cities come online


Q1) Should we be able to do data mining on large sets of social data?

A1) Big data, data mining and the internet of things can be seen as the three horsemen of the apocalypse in a way. And that’s the other talk I could have given. The police, using this sort of data are using data in a different context, and that isn’t ok under ECHR art 8.

Q2) I remember a paper about a year ago about the distinction between what an individual can do in terms of asking about others etc. They have more right that the police in some contexts.

A2) There is this weird thing where if you are not looking at specific people, you aren’t as restrained. That’s because it used to be the case that you could find out very little without investigating an individual. That has changed considerable but he law hasn’t been updated to reflect that.

Q3) A lot about us is public, so don’t we just have to deal with this. I see the concerns of a police state, but I don’t understand where you are drawing the line on legal controls on policing. If they can only do the same as a member of the public then there shouldn’t be an issue there…

A3) You’ve given that answer yourself – the power dynamic is asymmetrical. They have capacity to join data up to their own databases – which may include your being a witness or victim of crime, not always suspect or perpetrator. There is a lot of black boxing of data here…

Q3) What controls are you proposing?

A3) Honestly, I don’t know if the quick answer. But if we look at the requirements for intercepting letters, email, telephone are strict, searching homes, pretending to be friend etc. are less strict… But that scooping up of mass data is something different in terms of implications and we need some form of safeguarding around that, even if less strict than some other approaches/interceptions.

There is overwhelming evidence that young people don’t realise the potential implications of their sharing of data, and see these spaces as a private space away from other areas of their life in which they find themselves surveilled. So there is a reasonable presumption of privacy there.

Q3) I think there is a need for appropriate controls on police activities, I agree with that. If I share things only with friends on facebook and police look at that, that is an investigation. But if I tweet something it is public

A3) This is the classic liberal argument I don’t agree with. Tweeting is a bit different. Facebook is the new mall, the new social space, they use openness to serve them socially, believing it will only be read by peers. So they have a reasonable expectation of privacy. Part of Bartett and Millar work is about the use of the word “rape” – in gaming culture it is being used to take a game. Imagine that being crunched. That’s the sort of issue that can arise in big data. I’m not saying police needs a warrant for all Twitter data capture, I’m saying we need to think about what is appropriate.

Q4) There is a perspective that taking the UK out of the EU Human Rights Act is a red herring to distract from other legislation.

A4) Even if we left the EU Human Rights Act, the UK Government would find many of its protections are embedded in other part of EU law, so it would still require appropriate respect of individual rights to privacy. But that’s a political conversation really.

Q5) So, in terms of the issues you have raised, how do we understand what is private and what is public data?

A5) I think essentially that we need to safeguard certain points in what has become a continuum in privacy around human rights, something that will set some barriers about the types of interventions that can occur, and what kind of oversight they require.

And with that Lilian’s excellent and information-packed talk is done. Really interesting and there were clearly plenty more questions arising. Particularly interesting for me thinking about the Digital Footprints work, and the legislative context for the research we have been undertaking on student expectations, experiences, practices. 

Apr 272015

This afternoon I am attending a talk on the Privacy of Online Social Networks which has been arranged by the Social Network Analysis in Scotland Group (SNAS) and is taking place at the University of Edinburgh. The speakers are Jordi Herrera-Joancomarti, Cristina Perez-sola, and Jordi Casas-Roma, all from Universitat Autonoma de Barcelona (UAB). I’ll be taking notes throughout, although I think that the talk is also being recorded so may be available later. As ever this is a liveblog so corrections, comments, etc. welcome. (I will also be adding some images from the event later today as some of the processes discussed were quite complex and require illustration!)

We are opening with an introduction to the SNAS group, which meets at the University of Edinburgh on the last Tuesday of every month… They have a mailing list and I’ll add a link here later. Dr Jordi Herrera-Joancomarti is leading the talk, and is an expert on privacy and security.

Dr Jordi H-J: This is collaborative work with my colleagues Cristina and Jordi. My background is not social sciences but mathematics, so it is a good challenge for me to speak to a non technical audience here… Hopefully there are no scary mathematical equations here! I’ll open with an introduction, talk about Online Social Networks and graph theory, talk about the data you can mine, and I will talk about Online Social network Data anonimisation, and how you can release data from networks without compromising privacy, before coming to my conclusions.

So, to start with the definition of Online Social Network I am using is an “online service, platform or site that allos to create a user profle which can be connected with other user profiles of the network… ”  – a very computer science definition.

So this can be about specialisms like Flickr, LastFM, WikiLoc… specialised format (e.g. Twitter); Scope limited (e.g. LinkedIn); General purpose (e.g. Faebook, Google+) etc. The denomination of connectivity can be network dependent (e.g. Facebook: friends; Twitter: followers). An dinteractions between user profiles are also network ependent (e.g. Facebook: “like” action, post a message; Twitter: tweet, Retweet etc).

So, why are OSN interesting or important? Well they have become an important part of people’s everyday communications, with huge volumes of users. But there is also a book, Big Data (Viktor Mayer-Schonberger and Kenneth Cukier) which includes chapter 5 “Datafication” talking about the quantification of the world along the time from differnt aspects. So, when words became data (Google books in 2004); when localization becomes data (GPS); and when relationships become data (OSN). For instance Facebook datafied relationships, and most notably with the introduction of “Social graph”.

To graph theory then. A graph is a mathematical tool used to represent objects (nodes) that can be connected by links (edges). OSN can be modeled using graphs and analysed with graph theory. So… You can represented connections between individuals etc.

There are different OSN propoerties that dertmine the type of the corresponding social graph:

– Undirected graphs are those with no meaning on the incidence of an edge in the node. Facebook social graph is an undirected graph. So, no arrows between individuals, no value to that edge.

– Directed graphs (digraph) are those in which the edges have a direction associated with them. Twitter social graph is a directed graph. For instance you can follow someone, they don’t have to follow you… So we have arrows here to indicate connection and direction.

– Weighted graphs assign a weight to every edge in a graph.

So, when you add direction to a graph you can borrow many analysis tools from graph theory. So if we try with a degree of a node in an undirected graph… The degree of a node is the number of edges incident to that node, denoted as deg(vi).

In a directed graph the same concept applies but it is more complex… We have In-degree of a node and that is the number of head endpoints adjacent to that node denoted as deg-(vi). Similarly we can have out-degree for number of tail endpoints, denoted as deg+(vi).

So, in a facebook social graph the degree of a node is the number of friends of that user. In Twitter social graph, the in-degree can be seen as the number of followers of that user. High in-degree may indicate a popular user. And the out degree can be seen as the number of users that person follows.

We can also talk about the clustering coefficient. We see local clustering coefficient of a node – the proportion of edges between the nodes within its neighbourhood divided by the number of edges that could possible exist between them… So it measures how far are the neighbourood of a node to become a clique. So this is how well the friends of a node are connected. These kinds of technical techniques can be used to understand user connections and relationships.

We study OSN privacy from an information-fundamental point of view, analysing OSN privacy from a graph mining perspective. We do not study specific OSN services, configurations or vulnerbailities. In some cases we do make some assumptions about the type of OSN: open vs closed profiles. For instance Facebook is more difficult to extract data from than Twitter, an open social network.

So there are two kinds of users information that can be extracted:

1) Node information – data about a specific user, details contaied in the users profile on a specific OSN

2) Edge information – data about the relationship between members of the network – and that is what we are most interested in.

Edge information can, however, directly disclose node attributes – e.g. an edge representing a sentimental relationships between two individuals of the same sex would be revealing about their sexual orientation. It is more difficult to protect edge information than node information – as it depends on behaviour of connected people whereas node information is controlled by just one user. Relations between users can also detect communities, and more node attributes.

So, I wanted to explain about data retrieval. How do you ontain social network information? Well you can ask OSN providers – but many are not that cooperative or put a great deal of restrictions/agreements to do that. They provide local and/or anonimised data. OR you can take the data from the OSN providers – that is not always possible adn depends on the open degree of the OSN service. And it is very important to take care on the mechanism used to obtain information as that may determine the bias of the data you collect.

You can gather data several ways. You can use a web crawler to gather daya from an open OSN (like Twitter). Web crawlers are computer programs that retrieve web pages starting from a single (or multiple) page and exploring all its linked pages and also the pages linked to those ones and so on. Since most of OSN interact through the web, you can use web crawlers for OSN data retrieval… The process is iterative…

A download is the interface between the OSN and the crawler – it downloads the users profiles and passes it to the parser, which then parses that data. You draw out the friends of that user and add them to the queue, which contains all the users that are awaiting to be explored, found when crawling every user. And the scheduler selects which user, from the ones in the queue will be explore and sends the decision to the downloader. The scheduler impacts on both performance and data quality.

If you are exploring the whole network then it is not so important to consider the crawler details… if I am crawling every member I will find all of the connections at the end… the order you gather data in doesn’t matter in that case. BUT you cannot crawl all of the network available now… So you will have to, at some point, decide to take a partial view of the network. So to do that we have to think about notification and assumptions…

Users can be crawled (one that all his profiles information and all friends are known to the crawler (v E Vcrawl). A discovered user (connected to the user crawled), and an explored user  (discovered by relationship to discoverd user)?

So… for instance a Breath-First Search (BFS) Algorithm would start with one user (h)… you find they have two friends (d and j)… I crawl j and then discover they connect to users l and k and g (and I’ve already crawled d and h)… Then I crawl user d, finding connections to f, e, b, c… others are already found… Then I crawl l, find connections etc…

So, that is your schedule, the order you crawl. And the idea is that you can end up with all the elements of the network… This is quite a linear process. So, this is one approach, and this BFS algorithm produces graphs quite dissimilar to other algorithms you could use.

An alternative approach is the Depth-First Search (DFS) which works as a traditional stack, the first nodes to be crawled are the last ones that have been discovered (LIFO management). So, in this approach… If you start with user h… you discover j and d… But the next node you explore is d… then when you find connections to f, g, e, b, c… and you next explore node c. At the end you will end up with all the nodes as well… But in a different order than you had before… So, again, if you do this with a group of users (example here being 162 flickr nodes) it looks quite different…

Then you can do more intelligent things… You can use “greedy” algorithms:

– Real-degree greedy (hypothetical greedy or higherst-degree-crawler) takes its decisions based on the real degree (which may be unknown to the crawler before the node is crawled) of the nodes in the OSN. So a user has degree 5, degree 7 etc. based on the edges between different nodes… You can gather the whole network, or you may have restrictions and only capture part of the network…

– Explored-degree greedy (greedy) uses the actual known degree of the nodes in the OSN… So if you graph that you see many many connections, you look more conciously to the mode connected nodes.

You can also choose to select more variance in the network, to randomise your sample to an extent. This can be done with a lottery algorithm…

So, if you take information from a social network or a social network graph you have to be really well aware of what you are getting. When you do your sampling from different profiles, etc. that you understand what your sample is of. As far as you can see you can just adjust the scheduler to get what you want… you can do that to focus on particular users, types of users.

Schedulers have implications on privacy… depending on the level you select that has different implications… So your scheduler can have different objectives for the crawler – taking the privacy attackers point of view. So you can then understand which scheduler algorithm fits those objectives most appropriately…

You can also do more tricky things… For instance the classification of users from a graph point of views. So, I want to classify users, identifying the set of categories a new observation belongs to. The decision is made on the basis of a training set of data containing observations whose category membership is already known. When you try to classify users within the network, you can see link information which may help you to classify a user – connections to a community for instance.

The idea is that you can see classification as a privacy attack – user classification allows an attacker to infer private attributes from the user. Attributes may be sensitive by themselbes, attribute disclosuer may have undesirable consequences for the user. So the design of a user (node) classifer that uses the graph structure alone (no semantic infomation needed)… So, for instance… We may classify the user, with a neighborhood analysis to better classify the user… So the classifer analyses the graph structure and maps each node to a 2-dimensional sample using degree and clustering coefficient. The output is an initial assignation of nodes to categories…

And you can make that neighborhood information to classify the node… You can also have a relational classifier, which maps users to n-dimensional samples, using both degree and clustering coefficient and the neighborhood information to classify users…

So coming to the issue of data and data release… When you obtain a collection of data… you may have a more anonymised data view… You may see connections etc. but without user names, for instance. The intention is to preserve the privacy of users. But is this enough? Well no… this nieve anonimisation potentially reveals huge amounts about the user… if you know other data (other than names), you may be able to deduce who is in the network, you might find one user in the network and thus expose others. Removing the identifiers is not enough… So, you have to do something more elaborate…

One approach is to modify the edges – adding or deleting edges to hinder re-identification… But the problem is that you have two opposite objectives: On th eone hand you want to maximise the data utility and you want to minimise noise in that data. But you also want to preserve users privacy…

So, there are different ways to quantify the objective…. There are generic information loss measures (GIL) – measures like average distance, diameter, harmonic mean of shortest distance, etc… You want to preserve that in your data. So… you have the original network, you do one metric… and end up with a different network that is anonimised, and you can apply a similar metric afterwards to use it… In statistical databases you can preserve the mean of all the registers that sold boots (say)… If you know the questions to ask of that data, you know the process to keep that anonimised data close to the original data set…

You can also use specific information loss measures (clustering process)… Similar problem here… You have the original clusters, you use a clustering method to get to an anonimised (perturbed) version.

So, some measures behave in a similar way independently of the data in which they are gathered.

And then you have the idea of k-anonimity. A model that indicates that an attacker can not distinguish between different k records although he managed to find a group of quasi-identifiers. Therefore the attackers can not re-identify an individual. So, node degree can be the quasi-identifier… We can presume the attacker may know some of the nodes in the network… We can preserve the degree sequence, and the ordered degree sequence. And you can measure the k degree by understanding how many nodes have the same degree. So if two nodes in the network have degree 4, then the k-degree anonymity is 2. You can then make use of this to preserve the graph…

To modify the graph you can use edge modification (adding and/or deleting); node modification (adding and/or deleting). You can use uncertain graphs – adding or removing edges “particially” by assigning a probabiity to each edge. The set of all possible edges is considered and a probability is assigned to each edge.

Edge modification can include edge rotation, random perturbation, relevant edge identification, k-anonymity orientated anonimisation. These can allow you to keep data you want to keep, whilst preserving user privacy.

So, in conclusion, OSN can be modeled with social graph and analysed using graph mining techniques. Web crawlers may retrieve sensitive information from OSNs but the quality of the collected information will depend on the scheduler algorithm specitifities. Relational classifiers may provide relevant user information by just analyzing the graph structure information… Data anonimisation is needed for releasing OSN data without compromising the user’s privacy. This is a research field that is quite new and quite difficult… unlike statistical databases, where you can change one user without impacting on others, any change here does effect the network. And anonymisation algorithms need a trade-off between information loss and user anonymity loss.


Q1) You talked about how much stuff is being datafied… Soon with smart watches we’ll have health data available. Because crawlers take some time… things could change whilst you are crawling.

A1) One of the problems in social networks and graph theory, is that algorithms for this sort of data are complex and time consuming… And that is a problem… Especially at scale. And sometimes you have the information, you make a lot of computation but the information is not static… so not only a lot of work not only on algorithms but also on understanding different and changes in the network – what happens when a node is removed for instance. There are people working on algorithms for dynamic data… But much m

Q2) What kind of research questions have you been using this with?

A2) There are two different issues for me in terms of social sciences… We don’t start with research questions… we start with problem and try to start it… So when AOL released data about lots of servers… you could identify individuals from the data… but you shouldn’t be able to… That happens because they don’t understand or care about anonymising data. So we are trying to provide tools to enable that anonymisation. We also have ideas about the crawling approach… So as a social network provider you might want to avoid this type of crawler… you might use this approach to trap or mislead the crawler… So the crawler end up in a dead end… and cannot crawl the network.

Q3) Some of the techniques you showed there were about anonymisation… do you use removal of nodes for that purpose

A3) There are several approaches for adding or removing nodes… Sometimes those approaches collapse those nodes… So you anonymise all the nodes too… But the general techniques that are more used are those that perturb and move the nodes.

Q4) One of the last things you said was about that trade off of utility of analysis and user privacy. My question is who makes that decision about the trade off? Would the people being studied agree with those decisions for instance, in the real world?

A4) The real world is much more complex of course. The problem is about deciding level of usefulness of the data… At the present time these methods are not used as far as they could be done… For statistical data this is often fixed by government… for instance in Census data you can see the method by which data has been anonimised. But for OSN there is nothing of that type, and nobody is telling… and basically no-one is releasing data… Data is money… So if we can try to give good algorithms to enable that, then maybe the OSN companies can release some of this kind of data. But at this moment, nobody is putting that idea of privacy there… Generally privacy level tends to be low, information level is high…

Q5) I didn’t totally understand how you set the boundaries of the network… Is it the crawling process?

A5) The idea is that there are no boundaries… Crawler goes… Maybe it completes within 1000 nodes, or 3 hours… or similar. You won’t crawl everything and you want some data. So 10 million users might be the boundary for instance… Then you have data to look at… So I have 10 million users out of a pool of 500 million… But which ones do I have? How representative? That needs consideration…

Q6) The crawler gathers a model of relationships and behaviours, and I’m sure that marketers are very interested. Is there potential to predict connections, behaviours, intentions etc.

A6) Yes, there are lots of techniques of graph theory that allow that sort of interpretation and prediction. OSN use these sorts of approaches for recommendations and so on…

Q6) How reliable is that data?

A6) Understanding similarities there can help make it more reliable… similarity rather than distance between nodes can be helpful for understanding behaviour… But I will say that they are quite accurate… And the more information they gather, the more accurate they are…

Q7) I was wondering when you were talking about measuring the effectiveness of different anonymisation methods… Is there a way to take account of additional data that could effect anonimisation

A7) In computer security in general, when you model someone you have to define the adversary model… What the adversary is able to do… So, what is the attacker able to have… The available information… So the more information is available, the harder it is to protect the individual. It is a complex scenario.

Q8) Is there a user friendly web crawler that can be used by non technicians…

A8) No. Sorry about that… No, because there are some frameworks… But you don’t have one solution to fit all… But the idea is that there are some frameworks that are more suited to computer science people… Tomorrow in the workshop we will explain extracting information from Twitter… And those techniques will let us explore how we could develop a crawler on Twitter… So exploring connections and followers, etc.

Q9) What are the ethics of web crawling in social sciences? And what are the positions of the OSN on that?

A9) You can crawl OSN because the information is public. So you can crawl Twitter, as information is public. If you want to crawl Facebook, you have to be authorised by the user to look at the profile… And you need to develop an algorithm to run as an app in Facebook… and authorise that… But that doesn’t mean the user understands that… But for instance in last US Election, Obama campaign did an application on Facebook that did that… graphing their supporters and friends… And use that in the campaign…

Q9) I was wondering about the crawling of discussion forums… where you cannot get authorisation. But you also mentioned that providers not keen… is it legitimate to do that…

A9) I think that it is… If you are crawling public information… There is another thing of the OSN not liking it – then they can make some restrictions. If I do things that avoid OSN restrictions that is fine… You can do that

Q10) I wanted to follow up on that… There are legal and ethical issues associated with crawling websites. You have to consider it extremely carefully. If I use a website that says it does not allow crawlers, I don’t expect it to be crawled and that would not be legal under data protection law. And there was some research about 10 years ago a research project found that bloggers, although posting in public, didn’t expect to be analysed and interpreted… And you do have to think about the ethics here… And you need to think about the user’s expectation when they put the data up.

A – Christina) Everyone uses Google, you can’t expect that when you put something on the internet you have to expect it to be crawled

A – Jordi) From my perspective, as a researcher doing cryptography what you say is quite strange… My work is about protecting information… It assumes people will be trustworthy with your information…

Q10) No, I’m saying an ethical researcher should not be breaking the law.

Comment) There can be an expectation of privacy in a “public” space…

Comment – from me) I would recommend the Association of Internet Researchers Ethics Guide for more on how you can mediate expectations of users in your research. For your cryptography work that may not be as relevant, but for others in this audience that guide is very helpful for understanding ethical research processes, and for thinking about appropriate research methods and approaches for ethical approval.

And with a gracious close from Jordi, we are done! There is a workshop running tomorrow on this type of analysis – I won’t be there but others may be tweeting or blogging from it.

Feb 142012

On Thursday afternoon I was at the University of Edinburgh eLearning Presentations Showcase 2011 event. This is a really lovely idea as it brings together presentations given throughout the year on or around the subject of eLearning into one afternoon. It’s a great way to catch up on colleagues’ work but also interesting from the point of view of seeing lots of varying types and styles of presentation in a packed afternoon.

Tweets about the event can still be found on the #elpp hashtag and further information and the presentations from the showcase can be found on the ELPP wiki:

These notes were taken as a liveblog but due to wifi issues are only being posted live now. So, although I’ve done a little tidying up, please be tolerant of typos etc. I thought it would be better to get these live quickly rather than perfectly but will try to correct any errors as they spot them. 

Wilma Alexander, Chair of the eLearning Professionals and Practitioners Forum, opened with a note that the annual eLearning at Ed conference will  be on Friday 13th April and loads of exciting programme stuff information will be live soon. With that it was right into the presentations…


Jo Kinsley PostGraduate Virtual Open Week at the University of Edinburgh

Jo originally presented this at the Blackboard Collaborate Connections Summit 2011 in Las Vegas.

Jo originally introduced this presentation with the background of the University mission statement and international profile. The University of Edinburgh has 26k students, many from Scotland. Of those international students at Edinburgh the largest group is from the US but 137 countries are represented in total.

This project intended to let potential students around the world the opportunity to engage with staff and attend an online open day as they are unable to attend the on campus open day. The idea came from the School of Social and Political Sciences with the idea that this would be important to students from other countries, particularly North America.

It was always intended as an alternative and additional initiative. It’s the first time this sort of project had been done in the UK on this sort of scale.

The planning… we saw this as an opportunity for a central event, here information services would be the central point for coordination. A one day turned into a full week in the end. Some schools wanted to represent the whole school, just one single programme of study. Number of staff (and in some case alumni) varied. Lots of varying technical requirements. We limited registration for academic sessions to 15 people to make it manageable and we decided to record this to see the outcomes, the attendance level etc.

Project requirements – a website, online registration, promotional planning, choosing software and training. We did most of the website central, also used an online tool on the website for registration. Comms and Marketing assisted with promotion. The software selected was Wimba and the training would be by IS.

Wimba was chosen as it is easy to use, there is no client software to install and we already had a pilot running across the university. Wimba also, via the SDK kit, made it easy to replicate classrooms quickly as there were 100s of sessions.

There were 38 staff technically trained to support sessions – Wimba did 2 hour training sessions for these staff. But we also ha 135 staff who would be hosted and/or moderating a session. The training was close to the event – took place in the training suite in the library with headsets etc. We showed them how it worked as a student and how it worked as a moderator. We gave them a role playing session to get used to the role of host, and of students, and some slides and examples to let them get a sense of using the classroom and the etiquette of the space.

We also gave them scripts – hosts with scripts, moderators with scripts etc. We gave everyone a script. People were hesitant but it worked well. We also made the staff try the experience of a participant – questions they would ask, what they would want to know – to help them get an idea of slides or notes to have to hand.

Although people were initially embarrassed etc. But after a few rotations around people really enjoyed and got into the role play. The feedback was that people weren’t sure about the time commitment or role play BUT they felt it gave them a good experience, what they could do on the day etc.

So the Virtual Open Week was 21st to 25th feb 2011. Involving 22 schools, 6 support sessions. There were about 170 unique drop in session visitors. For the academic sessions we had about 740 registered participants. We had 369 unique visitors – registered vs attendance. Roughly 50% of those who registered showed up on the day. Actually not that far off the in-person open day experience.

There was some disappointment over numbers but some great in depth discussions did take place. One chap from the dental school prepared a fantastic presentation but no-one showed up BUT he recorded the presentation and is using it as marketing on the course website.

Feedback on non attendees tended to be that they had forgotten, timings didn’t suit as well as expected, etc.

But those that attended gave great feedback. Most responded that they were slightly or significantly more likely to attend as a result. They felt it was worth while. Some said it was better than travelling to Scotland – the travesty!

Issues and lessons learned – some sessions had no preprepared information, emphasize the need for having some powerpoints to break the ice and engage attendees.

Working around admission deadlines of schools presented a timing issue.. One large event plus various school events would work.

From non attendees:

  • Reminders
  • Better account of timezone
  • And more programmes they were interested in to be included

Feedback from schools and staff has been positive. Since we did this Wimba has been in wider use across the university – PhD interviews, careers events etc. Been good for getting people used to the technology.


Q1) would you do it again?

A1 – Jo) I would but as it happens I won’t be. But I was on the technical end, not managing the whole thing…

A1 – Fiona) It will run again on 23rd Feb as a central University thing. It will be once a month with drop in session on fees, other topics of interest etc.

Q2) It’s very important to note that on-campus that open days only attract 50% – really encouraging that online has same. Also an hour for one student is a great use of time.  And the training sessions were rather lively!

A2 – Fiona) central services found it effective – could work away then attend to students as they came in.

Q3) I used Wimba with students in Japan last year. They had some technical issues with the software. Last summer I tried it and had a problem as well. Stephen Vickers helped with that. But maybe in other countries the bandwidth can/could be an issue with using this. Especially places like China

A3 – Jo) We did put up some training/guidance and a wizard to try out Wimba before the sessions to try and help.


Jen Ross Partnerships and Collaborations: Future Networks of Exchange for Museums

This was originally presented with Angelina Russo (at RMIT) at ICTOP 2011 in Toronto. Jen is associate lecturer at the School of Education and works on various projects including cultural heritage.

This presentation was part of work that began as the National Museums Online Project and that led to the Digital Futures for Cultural Heritage Organisations project which ran recently. Angelina is a world expert in social media and museums – she’s not here but she says hello! Angelina is also the founder of Museum3 which is a great way to find out about digital innovation around the world.

So this talk was about how museums and cultureal heritage organisations approach social media and digital technology. As they get to grips with this they also have all sorts of organisational challenges around what expertise and authority means now. And how to be relevant in the world. The idea of exchange, the relationship between the audience and the museum as an exchange rather than top down, is something that Angelina has been working on.

So, exchange is a challenging thing for Cultural Heritage organisations (CHos) to think about. Often museums etc. have a real sense of purpose, that they are guarding “everyone’s stuff” so how  you start conversations about opening up that stuff. An exchange is a two or maybe even a three way exchange – there are exchanges between patrons/visitors as well as with the organisation.

Exchange requires people to invest in your project, in your idea. So trialling and piloting ideas can work well but if you neglect that you can lose some of the good will built up in the project.

The idea of communities of practice might be too constraining or problematic in thinking about what the relationship between museums and their audiences. It implies a shared language or a sustained engagement. It is not a realistic paradigm in the online networked world.

Instead we have been thinking about networks and flows. Organisations can trigger these but ultimately cannot control, flows of information and communication in digital space. Digital networks thrive on border crossings. What about “knotworking” (Engestrom Engestrom and Vaaho)? <another ref here too to grab>.

The digital futures of cultural heritage education project

The project had two main aims. To begin to establish a research agenda

Heritage was the biggest group, but there were a number of commercial, academic and government sectors – this is brilliant, you want to create a network of people with a shared interest but diverse needs.

I did want to iklustrate something about how twitter was used in the project. We normally think of tweets as knowledge exchange mechanism – here are five of my favourite tweets (AddressingHistory gets a mention!). But  the power of tweets also moves outside the room – presence, reach, flow…

Someone in the room asked for questions, someone else asked “how you identify your brand/institution fanatics and let them be fanatical about you?” and another person in the room summarised and replied. Artifacts move in and out of physical and virtual spaces in this sort of way. And here we see three very different people retweeting the same information to three very different audiences here.

We think that networks are a very useful and powerful way of thinking abouyt exchange in a cultureal heritage situation and a social media situation. And we nee dto think about how trust is reconfigured and strengtherned by a willingness to echange. Onus is on the institution to earn that trust through their participation with broader audienes.

You have to tie projects up when they finish – fragments on the web can reflect poorly on your institution,


Q1) This might be premature. I can see the power of Twitter and other social spaces but they only reach a particular type/group of people but that canj provide some powerful insights into ow that moves into other digital and real spaces.

A1) That’s interesting. The DFCHE project had museums and RCAHMS etc. all part of this event. RCAHMS has had some dramatic things happen oin their education department happen as a result of these events. People working with digital things are often part of these big educational teams so are able to share that experience and develop it. In the msuems sector can be easier. But buy in from curational staff can be more tricky. Education and curation can be quite separate. Intra organisational issues can be just as profound as extra organisational issues.

Q2) Was the project combined with the resurgence of the National museums that has been going om – it feels really opened up now.

A2) We did have museums staff on the project but their refurb work was well underway. New Museology looks at the power relations within museums.

Q3) Was one project aim to raise awareness of flows and knotworking etc. in a systematic way.

A3) Yes and no. We wanted to establish a research agenda in Scotland. But we were all pleased and slightly surprised by the interest from the commercial sector so it was fantastic to see those people in those groups. Knotworking and flows it was more about what we have seen and looked back on.


Julie Moote & Erin Jackson Student learning in online discussions

Erin is teaching manager at the school of law. This presentation is related to the Principals teaching award. Julie originally presented this at a law education conference

Julie is a PhD candidate from the School of Education and has been working with up on the PETAS(check) project.

Julie – we are just near the end of this project, we really want to disseminate what we found. So this is a content analysis of discussion transcripts comparing synchronious and ascynchornous environments.

First step was to look at the literature of online learning. (e.g. Hara et al 2000, Heckman & Annabi,. 2005, Bliuc et al 2007,). There are real gaps in online learning environments and particularly in law learning and reasoning.

We had here main areas to look at – what is the nature of the learning taking place in online discussions – the level of cognitive engagement, the community of learners. How does the tutors online presence influence learning, the frequency of posts and the interaction betweein the students, and the final aspect – how to support a highly diverse cohort of students online? Suggestions for pedagogy, impact of legal background, language skills.

Over to Erin to introduce the elearning programmes in law. The LLM programme Innovation, technology and law, was launched in 2005/6:

There are three nominate eLLM degrees in IP Law, IT Law and Medical Law which began in 2008/9 and more are planned. There is a really diverse group of students and backgrounds here. And we do assess discussion as part of the programme – 20% usually – and discussions are led by academix tutors often with contributions with guest tutors and visiting scholars. Students value the opportunity to learn form the experiences  and insights of fellow students.


The most time consuming aspect of this project was thinking about how to analysis this content. We found an ascynchonous protocol that seemed to fit the programme. We found one and coded transcripts accordingly. Of the 30 students that consented, 9 students transcipts from the discussions were chosen fro detailed content analysis. One of the potential gaps or issues of this research was we eliminated postings from any student who had not consented so you do not get both sides of conversations often.

We found high levels of cognitive processing in discussion transcripts. They went beyond detailing factial information – connecting ideas, supporing opinions, application of judgements to different contexts. Personal interest side notes and examples etc. also were brought in.

We looked at students over 2 modules. There weren’t any obvious imporvements in discussion performance between modules 1 and 2. There didn’t seem to be a sense of tutor differences in assessment. Explicit student and outline of assumptions. We also did an in depth analysis of referenceing literature and how it was refefrenced.

We found that class size was not related to overall performance in the discussions. English languiage speakers may have a slidght advantage over non English speakers. But Lawyers fo not appear to have an advantage over non lawyers.

Limitations – we need a far larger number of students to get a sense of progression in terms of discussion. And although we used a strandard protocol it’s not well used and tested.

Conclusion s- some suggestions for pedagogy. Support for quality abd depth of student learning taking place in discussions. There are high levels of cognitive processing taking place.


Q1) Do students have marks released between module 1 and 2

A1) Erin: Yes, they are per semester. They get grades and qualitative feedback. They should have had feedback between modules 1 and 2.

Q2) Did students get feedback on the study

A2) Julie: That’s the next step.

A2) Erin: We are looking at how we give feedback to students. Looking at how to use findings from this study to feed into that.


Robert Chmielewski – INTEGRATE – INTerlinking and Embedding Graduate Attributes at Edinburgh

Robert works in IS and particularly on the excellent work that has been taking place with PebblePad in the university. And this was given at the ePIC2011 (elearning Portfolios International Conference).

This was about a project that took place last year. A Scottish initiative run by AQA and HEA and this project involved Jessie Paterson (project leader), Tina Harrison, Nora Mogey, and Robert Chmielewski.

We wanted to look at graduate attributes at the university of Edinburgh. It’s a useful thing for universities to recognise the development of students etc. Lots of projects and work looking at developing this sort of reflective practice.

We identified 3 projects, one for UG, one for PGT and one for PGR students. We wanted to make a story of these that could be shared on the employability website. So three strands were recorded. Graduate attributes are crucial and link to the student experience at the university. It’s a tough choice to pick a programme of study. Many choose the wrong thing, but you learn loads of things even if you don’t want to stick with the subject you studied for your degree… so being able to pick out graduate attributes and skills is really important.

So, jumping into the first branch, for undergraduate students. This was for Divinity students – this is from Jessie. You can become a minister or a researcher at the end of your studies but most become something else. Jessie is running an Academic Skills course for 1st year undergraduates where they identify their existing skills and those they want to develop.

From the very beginning of that course students are given a framework of desirable skills and they monitor their own development against that framework. That’s a compulsory course but not assessed in a traditional meaning of that word.

If I now skip to the second strand. So these are the Postgraduate Tought students, in this case nursing studies. They use PebblePad to make sure that students are able to track their skills throughout their studies. They track their progression, they share things with tutors, and they can build up a more informed picture of their skils. We also decided to describe their journey of how eportfolios began in that department. And how these were embedded within the programme – this work will be published soon so do have a look. Quite an interesting example. All assignments are done through PebblePad and they can also do web essays instead of traditional dissertations etc. Quite exciting stuff.

The third branch is the Principals Career Development Scholarship Scheme – a series of these have been released across schools and this is exclusively for PhD research students and includes training to help them put their skills across and make more informed choices for their career paths. And look at how to engage with the rest of the world – public engagement, entrepeunership, teaching, etc.

So the picture of graduate attributes developed by the employability part of the careers service – see diagram.

So this can be shown in PebblePad and students can grade their skills in each area etc.

And an example of a webfolio from nursing studies – in this case nursing inforatics – this is something students can submit in place of a dissertation.

There is so much mojre I could tell you that is going on now – lots has progressed since this was originally presented.


Q1) What’s happened since that project?

A1) The highlights: An aweful lot of new functionality in PebblePad that are now being used. And the user experience is hugely improved. And it looks like it may move into the School of Law for skills (not core teaching) etc. Also EUSA is working with ePortfolios now, as part of the Edinburgh Award which is recognition for non academic achievements – volunteering etc.

Q2) Is it linked with the new PEER project?

A2) Not yet. Lots of potential there and we will be expanding. It’s beginning to gain proper momentum at the moment.

A2) Nora: that group are well aware of PebblePad so those conversations are happening

Q3) What is the student feedback on PebblePad? How many students use it reflectively?

A3) Really only thoe using it as part of a structured programme in these sorts of way. Few students using it otherwise. It makes more sense with a purpose. At the moment we have about 5000 active users, but maybe less than 4000 who are properly active.  Our users are becoming users after they’ve logged in and begun using it.


The teaching and learning experience – a look back at the last ten years and the way ahead for the school of divinity, university of Edinburgh – Dr Jessie Paterson

This was given at HEA Subject Centre for Religious Education (check) at an event which was the last before the subject centre closed.

eLearning, as I mean it hear, is about teaching using technology usually via the web (not for us to do with teaching spaces). So very much about blended learning with very traditional lectures etc. Our approach has a strong pedagogic basis, teaching first, tool (technology) second.

Our mode of teaching is very traditional. So our Level 8 students (1st and 2nd year UG) are lecture and tutorial based. Our Level 10 and 11 students (3rd and 4th year UG and PGT are small seminar based).

We started out with our Integrated Virtual Learning Environment (IVLE) from National University of Singapore (U21 partner) as an easy entry point. At the time we looked at WebCT as a VLE and it was too complicated by comparison. But now on WebCT and about to move to Learn9 in 2012.

Initially only a few innovators used the VLE, they wanted to break traditional models a bit. Now all courses have WebCT presence. The usage very much depends on the teaching style of lecturer. The only requirement is that all essays are submitted via WebCT. Adoption based on seeing success from colleagues and also student pressure. The students pushed academics to adopt the VLE in some cases.

Resources are materials that are providing content – in differet ways, in contexts that are unusual.

So for instance we have here Katherine Rutven Seminar – historically very interesting as connected to John Knox, Mary Queen of Scots etc. So we built up this webste where her story could be explored and engaged with and combine various resources.

We also produced a Study Skills Treasure Hunt (HEA funded) – there are hugely good digital resources but students don’t know where they are. We gave students questions and missions to explore to find these resources. We still use a version of this. Students keep going back to this as a hub for finding materials.

An we also did a Special Collections resource digitisation project. There are great resources but accessing them can be tricky. So we took students physically to the library to see the real thing but then they could explore the digitised texts in full detail.

We used the Principals elearning Fund to create flash maps – this is quite a complex course that looks at the history of migration. They work well and help students understand the relationships.

This is a new resource – Jewish Non-Jewish Relations teaching resource – this is actually a new website which is a joint project between us and Canterbury University, it’s still a starting point that we’re just getting started with.

Overall comments

Think maintainability – especially with things like the flash map

Think costs compared with gains – digitisation is expensive for few texts so you need to tink this through

Tutorial and seminar preparation – it’s not about the tutorial/seminar itself, it’s a challenge to engage students to read as needed etd. So we trialled an idea of a Gobbet or Image of the Week (the Gobbet is a small bit of primary evidance).

For the Gobbet work: The students had to post this stuff to the discussion board. They could discuss it but at least they came to seminars really enthused to discuss it on the day.

For Image of the week we asked students to choose for an image that highlights the topic of the week. This again brought them engaged to class but they didn’t discuss the image ahead of time.


Used at all levels

Used in different ways but all have ideas around ownership – blogger versus commenter.  1st and 2nd year students use this in tutorials. A student is assigned to be the blogger and has to write fairly thoroughly on a topic, the others must comment ahead of the tutorial. For honours years blogs are used in seminars, in place of essay? These have really transformed the seminars – students are actually prepared and engaged and make the best of the face to face time.


We use this were we want to encourage group working more formally. We’ve done two honours level trials. We put students in groups of 3 and each had to write 1000 words but the whole thing needs to have a cohersive story – some used comments on wikis and you could see development. Some work more like “blog” but have more scope in what do.

We also have a tutor support wiki – a peer support tool for tutors and they pool and add materials all the time. Loads of great sharing and tips here.

Going Forward

We’ve extended our blogging idea but combine with the ability for students to annotate and critic written texts. So can relate blog comments more readibly with the context.

Blogs have transformed tutorials and seminars and it’s been an easy and effective intervention with few technical issues.

The Wiki needs more management, students can find the medium difficult – the technology can be a real barrier. I’m excited to see how the Learn9 wiki works.

Assessment and Feedback

Predominantly essay based but course work do include blog, wiki, tutorial sheet assessment. Now have guidance on non traditional modes, A lot of our work is on paper, marking is usually on paper, but we do use Turnitin and I think staff will quickly adapt to marking/giving feedback online

Exams on computers

We offer some courses students choice typing or hand writing final exam, only alteration from traditional exams. Doing research on this as we go and have only been using 2 years so far. Exam4 by Externity. Student uptake has been quite low so far. But uptake increasing. And a growth there. A lot to do with confidence.

Autumated textual analusis – we’re looking at help that would be automatic to give idea of needing more referencing, grammar etc. It’s not about marking of text but improvement of pre-submission work. Working with Informatics on this.

We’re also doing more work on why uptake of typing by students is low.

Overall comments

Marking criteria non-traditional modeas need to be clear – implications for common marking scheme and our working group here has made quite a difference.

Exams on computers – think they’ll be an increase of uptake. Some infrastructure issues here – need power at every desk, more space etc.

And we’ve like to be able to give formative feedback on student essays as well.

Academic Skills Course

This is totally online for timetabling reasons. The idea is to ensure all students have basic skill set that they need. They work in their own time. It’s a mixture online resources and it’s non assessed.

We have now embedded Graduate Attributes into that course. We try to get them to write in semi-formal styles, and that is an attribute, speaking in tutorials etc. We are trying to help them to think about that skill and demonstrating that they have these skills.  And starting to use PebblePad.

Pre-arrival skills

We piloted in 2011-2012 we’ve shared this material ahead of arrival. When is a student really a student – A-Level results don’t come out until August, hard to define when they start. So we have a light touch graduate attrivute – two defined areas – academic writing and tutorials. Lots of skills bound up here. So those umbrellas let us bundle all those skills. These resources need to help and be encouraging – don’t want to put people off.

Some issues of the Academic Skills course though. The fact that it’s a discreet course. And studet engagement and sustainable engagement – making it compulsory has radically helped.

Other areas

First year learners experience project. We worked with STEER tracing of VLE usage – with Physics. WebCT doesn’t track everything you’d like really. And we are looking at student technology ownership and issues/opportunities around that.

In the future we are thinking now about distance education. Employability is becoming a growing issue – particularly as course fees  rise. Very few people come to be church ministers and they go on to a whole range of careers – and it’s the skills that enable that. Mobile U@Ed – we will be keeping an eye on. And Flexible learning.


Q1) First of all I was thinking about how fantastic the work you are doing at Divinity is, it’s inspiring! I was wondering about whether you care about sharing study skills with those pre-admission students of any type – other students that don’t come here may value them

Q2) It all depends on the definition of the student – that really matters from a library/publishers point of view. That’s for us to deal with here. Preparation for university is so much about using the library

A2) we really want our students using both the physical and electronic resources of the library.

A2) Christine: Students know they are welcome to come to the library, using a visitor card. Some of our licenced resouerces do allow access for non registered students so perhaps we can give students a taster to work with that. And the library catalogue is completely free of course.

Comment) you could probably stage it so some parts are fine for all, other levels are only for registered students.

Comment) Students do arrive looking or flats and other stuff early, they show up at the library and need that card, that proof of ID for those rental and council tax type things as well. They don’t know when they are a student.

A2) It’s a huge issue.

A2) Wilma: I’ve just become a matriculated student and we are not clear about what we want them to do, what instructions to follow.


“That ever ephemeral sense of being somewhere” – Reflections on a dissertation Festival in Second Life – Clara O Shea and Mashall Dozier

This is to be presented at Experiential Learning in Virtual Worlds in Prague in 2012. More on the Dissertation Festival can be found here: and images can be viewed at:

Clara teaches on the MSc in eLearning course with various colleagues,  including Marshall. So first off… the programme has about 150 students. About half UK, quarter EU and a quarter other parts of the World. We use Second Life and Twitter and Wiki and Adobe Connect and blogs and a social networking sites, a whole range of stuff. It’s awesome!

But then… students come to the dissertation… after all that aswesome collaboration they are alone and by themselves. They are doing a research projects on their own. They have a bit of a culture shock. And few people will do a similar topic. It can be quite a lonely and isolating experience.

So we thought that would be sort of a need to solve that problem and were thinking about what might work, drawing on our experiences. So we wanted to give people a cjance to get together. But students are very busy professionals. So we need those meetings to be synchronous and asynchronous. We wanted multiple ways to articulate an argument. We wanted sharing and exchange, to feel part of the environment, and to use some of these environments.

So – ta da!  – we wanted to do a Dissertation Festival – inspired by Japanese cherry blossom and Koi fish type festival ideas. So… over to Marshall…

Fiona Littletone raised part of our MSc in eLearning Second Life present out of the sea and made a space where students could share a poster of what the students were trying to address, and then visitors could leave comments, suggestions etc. for each presenter. And also we have them write a haiku summarising their dissertation. These were ways to succinctly describe their dissertation or research.

Clara again. We had  students as guinea pigs for this. The display was up for several weeks and we also had synchronous sessions where the presenters could explain their work.

The feedback boards and comments were useful – students found the summative nature of the displays very helpful, the feedback was great but also made some students feel exposed or a sense of risk.

So for the synchronous sessions we used voice to speak to the audience, the audience mainly used text. A bit like Twitter at conferences. Some of the Second Life “casual” poses tell you very little – so the audience can type “nodding” or “agreement” – some cues but not really disruptive. That seemed to work quite well.

Speakers could also respond in real time – very dynamic. It felt like a real experience of presenting to the student, it had meaning.

On the first day we also had a synchronous session in text for students to discuss the dissertation process – asking questions both straightforward and more complex. Also students not at that stage yet as well. And a champagne poster viewing session (that;s virtual champagne btw).

Students liked the chance to share. Students commented on the invisible blending of tutors and students. We had quite in depth discussion with people who attended. One commented about how nice it was to have tutors there. Another commented that they would have liked to have students there – there was a difference as the usernames aren’t obvious and that really flattens the hierarchy and gives a real sense of community.

Over to Marshall again…

We tried to make this feel like a party – we had sushi and champagne etc. (all virtual). The students said it felt like a group of friends – like discussion boards on steroids according to one syudent. One student said they think of the Uni on SL as a safe space. The wine and sushi gave a sense of presence to on estudent. And another commented that having that space was far nicer than emailing posters around.

The students who attended were current and past student s, some staff and ab outsider. And that was a nice number – like an in person seminar number. It felt very special. It was done in August when things are a bit quiet for students. Just before the restart of courses it sort of warmed people up. Partly we think its partly about how we use SL in the programme – coming together for fun tutorials but also graduations and Christmas parties etc. And that stuff – the sushi and wine and stuff all adds to that great environment. It’s all playful and special. The behaviours we model is very chatty and informal, that makes a difference. The flatterned hierarchy makes a difference. And that synchronous but not exclusionary interaction. And there’s a sense of “hard fun”.


Q1) At what stage were these students?

A1) Different stages – one was writing up and using it to get thoughts in line. One student thought she was further along then she was. She was able to have a reflective moment and get a better sense of her own journey. Another was heading to get stuck. And another had completed and we were just finding out what he’d been up to. We’ve decided to run it once every year. Maybe slightly earlier in August than they were before. But not just people about to hand in. Good kick up the pants.

Comment) All our students hand in at the same time.

A1) Thinking about the idea of exemplars of student work – you show both good and bad work and the range of ideas. I’d like to encourage more students in, those that are a year off say.

A1 – Marshall) Some students were taking a year off and this got them excited about coming back

A1 – Clara) We have a lot of students who get excited about handing in and want things to do over the summer

Q2) IS it still up?

A2 – Marshall) It is down so we can use the space for Innovative Learning Week

A2 – Clara) We left it up for a couple monhs but you can find the Flickr pictures as well.

Comment – Jen Ross) It’s radically asynchronous. A student this semester asked something and it reminded me of one of the boards up on SL and those students have now been discussing their research. Also Clara said “we” but this was her vision.

Comment – Fiona Littleton) We are looking at doing something similar with the Vet school and extending  a physical poster session they do there to SL.

A2 – Marshall) And it would be great to have an archive as well!

And with that we were done for the day…