Different types of "Blended learning"

The term "blended learning" has become a lot used word in educational sciences, and in general in the filed of e-learning and technology enhanced learning (TEL). It's almost a "passe-partout", a term used to mean a little bit of everything.

I came across a paper that had identified 6 models or categories of blended learning. I'll copy them here and I look forward to reading the whole paper!  

Choose Your Blend*
In 2010, more than 4 million K-12 students participated in some sort of online learning (up from 45,000 in 2000). An Innosight Institute survey of schools that have adopted blended learning was able to identify six basic models.

1. Face-to-Face: Most material is taught in the traditional manner. The teacher uses online learning as a supplement or remediation.
2. Flex: This is online learning but in a school setting. Teachers provide support as needed, generally through tutoring, either one-on-one or in small groups.
3. Self-Blend: Students supplement traditional school by taking online classes from home. This model is used mostly to take AP and foreign language courses.
4. Rotation: In this model, used in Rocketship schools, students spend a scheduled portion of their day learning online. Essentially, they rotate from classroom to online computer lab and back.
5. Online Lab: Courses are conducted entirely online, including interaction with the teacher, but students do coursework in school (rather than at home). 
6. Online Driver: Schooling is online: Students take classes and work with teachers remotely.

*Source: Heather Staker et al., The Rise of K-12 Blended Learning, Innosight Institute, innosightinstitute.org

Challenges and lessons learned from Social tagging in MELT

Social tagging in MELT, how do we want to take the social tagging work forward

Social tagging of educational resources potentially offers new ways for:

Individuals to
1.1) better manage their digital learning resources that reside in different repositories and platforms, and

1.2) discover and access new resources from different contexts (e.g. different language, educational system) through tags and other users.

LOR managers to
2.1) get third party metadata on learning resources (either the ones that already reside on their repository, or the possible new ones to be added to collections,

2.2) create affinities (e.g. link structure) between separate pieces of resources (either on their own repository, or the ones that reside on other repositories on the federation or on the Web) that were not cross-referenced before.

In the MELT project so far, we have only been able to see the peak of these potentials emerging. We list issues that we see important for future work in the field, for the clarity, we only list one of the main issues for each topic:

• 1.1 To fully support users in their knowledge management task on digital learning resources, the bookmarks (including title, url and tags) should be exportable in standard Webfeed formats. This would allow users to access and manage their MELT resources as part of their other resources collections, whereas now users need to be logged on to the MELT portal to do this.
  
  
• 1.2 Pivotal browsing of social bookmarks takes advantage of the affinities between the user, resource and tags. In the MELT context, more metadata could also be added to support pivotal browsing, such as the country of the user, interest topics; resource metadata such as multilingual indexing keywords. This would allow novel ways to access resources that other users have already discovered within the federation, and thus build on users’ social interactions and co-construction of knowledge.
  
  
• 2.1 Tags by end-users on the MELT portal have been shown to be of good quality as additional metadata descriptors of resources. We have enumerated possibilities of metadata ecology that the use of multilingual Thesaurus can offer to a federation such as LRE. Apart from working on ways to automatically generate LOM from tags, we urge on using the hierarchical structure and multilingual features to leverage user-generated tags.
  
  
• 2.2 Why not do Google for learning resources? Using PageRank-like algorithms on a learning resource repository or federation has been impossible for a number of reasons, the most important is the lack of a link-structure that cross-references resources. Tags, creating underlying connections between seemingly random pieces of content in different languages, on repositories in different countries and other platforms on the Web, rely on humans’ subjective idea of its importance for a given information seeking task. Using this new, emerging link-structure with tags as “anchor texts” offers totally new ways to “organise the world's learning resources and make them universally accessible and useful”. A new tag line could be “From teachers to teachers”.

Sneak preview: SIRTEL'09

Workshop on Social Information Retrieval for Technology-Enhanced Learning (SIRTEL'08) in the International Conference on Web-based Learning (ICWL) 2009 in Aachen, Germany, August 21, 2009
http://www.hkws.org/events/icwl2009/workshops.html


IMPORTANT DATES

Contribution Submission: June 14, 2009
Results Notification: July 13, 2009
Camera Ready Submission: July 31, 2009
Workshop date: August 21, 2009

CALL FOR WORKSHOP CONTRIBUTIONS

We are delighted to welcome exciting new contributions for the 3rd SIRTEL workshop

• Research papers
• System Demos
• Hands-On proposals
• Abstracts for "Pecha Kucha"

RATIONALE

Learning and teaching resource are available on the Web - both in terms of digital learning content and people resources (e.g. other learners, experts, tutors). They can be used to facilitate teaching and learning tasks. The remaining challenge is to develop, deploy and evaluate Social information retrieval (SIR) methods, techniques and systems that provide learners and teachers with guidance in potentially overwhelming variety of choices.

The aim of the SIRTEL’09 workshop is to look onward beyond recent achievements to discuss specific topics, emerging research issues, new trends and endeavors in SIR for TEL. The workshop will bring together researchers and practitioners to present, and more importantly, to discuss the current status of research in SIR and TEL and its implications for science and teaching.

The proceedings from the last years:
- SIRTEL'07 http://ceur-ws.org/Vol-307
- SIRTEL'08 http://ceur-ws.org/Vol-382


TOPICS OF INTEREST (but not limited to):

• Recommender systems and collaborative filtering in educational settings
• Defining the scope, purpose and objects of social information retrieval in TEL
• Novel ways of generating input for recommenders (explicit and implicit methods)
• Ranking of search results to support individualised learning needs
• Integrating SIR services in existing educational platforms
• Folksonomies, tagging and other collaboration-based information retrieval systems
• Social navigation processes and metaphors for searching information related to teaching and learning
• Social networks and interactions in learning communities to facilitate information sharing and retrieval
• Approaches to TEL metadata reflecting social ties and collaborative experiences in the field of education
• Pedagogic decisions, recommender systems and how to contextualise recommender system to support learning processes.
• Interoperability of SIR systems for TEL
• Visualisation techniques in learning and teaching
• Semantic annotation and tagging for social information retrieval purposes
• Evaluating the performance of SIR systems in educational applications
• Measuring the effectiveness of SIR systems in supporting learning and teaching
• Evaluation the user satisfaction with SIR systems in supporting learning and teaching

WORKSHOP SUBMISSIONS

The workshop invites several types of contributions which allow a wide level of participation:

• Research papers (upto 8 pages)
• System Demos (upto 2 pages)
• Hands-On proposals (1-pager)
• Abstract for Pecha Kucha (1-pager)

The workshop proceedings will be published as CEUR Workshop Proceedings online at http://ftp.informatik.rwth-aachen.de/Publications/CEUR-WS/. Copy rights will be reserved.

Please use the same template as the one for the main conference with details at http://www.hkws.org/events/icwl2009/submission.html. Workshop paper length is not limited.

All questions and submissions should be sent to: sirtelworkshop@gmail.com
The website with the call will be up shortly too.

PROGRAM COMMITTEE:
• Alexander Felfernig, University of Klagenfurt, Germany
• Brandon Muramatsu, MIT, USA
• Frans van Assche, European Schoolnet (EUN), Belgium
• John Dron, Athabasca University, Canada
• Lloyd Rutledge, Open University of the Netherlands, NL
• Markus Strohmaier, Technical University of Graz, Austria
• Markus Weimer, Technische Universität Darmstadt, Germany
• Martin Wolpers, Fraonhofer-Institut, Germany
• Miguel-Angel Sicilia, University of Alcala, Spain
• Olga Santos, UNED, Spain
• Rick D. Hangartner, MyStrands, USA
• Rosta Farzan, University of Pittsburgh, USA
• Wolfgang Reinhardt, Universität Paderborn, Germany
• Xavier Ochoa, Escuela Superior Politécnica del Litoral, Ecuador
• Yiwei Cao, RWTH Aachen University, Germany
• Zinayida Petrushyna, RWTH Aachen University, Germany

OER Creating connections: content, users, tags

I'm in the Hewlett grantees meeting now and marveling all the work that has been done in the area of Open Educational Resources. I had a chance to present some of the work here that we are doing with OER. I focused on creating connections, which I think is one of the most important things for the content. Knowing how it all is connected together is important in order to make sense of all the small pieces of separate content. Here are the slides, I give a few explanations.

Learning Resource Exchange -OER Hewlett Mongerey

View more presentations from Riina Vuorikari. (tags: lre eun)

The LRE is an access point to 16 content providers who make resources available to teachers in Europe and elsewhere. It's pretty much like any conventional content portal, but we have added a social tagging and bookmarking tool on top of it.

A good part of the slides show how we can make connections between pieces of content from different repositories, and how those content pieces can bring users togeher across country and language borders. In the visualisations, the little dots (nodes) are resources that are connected to other resources or users through tags and bookmarks.

Moreover, I give a few pointers to research that we have done on creating better navigation to the content, evaluating whether it is efficient or not, and also looking into the quality of tags.

"Thesaurus-tags"

One of the particularities of the MELT portal is that apart from being a "traditional" resource portal, we also have social tagging-features implemented. This creates a situation where resources have both indexing terms that come from our multilingual Thesaurus, as well as teacher generated tags, that, btw, are also multilingual.

I was looking at the tags today with a specific question in mind: "How many of the user-generated tags are actually terms that exist in the Thesaurus?" If there is a tag that is added by a teacher, and if it exists in the Thesaurus, I will call it a "Thesaurus-tag".

Here are the figures:

• Distinct tags: 4428
• Tags applied: 5009
• Distinct "Thesaurus-tags": 505
• "Thesaurus-tags" applied: 714

I was actually really impressed: 11.4% of distinct tags are "Thesaurus-tags"! And if we look at tag application, "Thesaurus-tags" amount to 14.25% of all tags.

Moreover, 22.37% of distinct "Thesaurus-tags" are applied more than once. This amounts to 45.1% of all "Thesaurus-tag" applications! The top "Thesaurus-tag" were:
Europe (10), music (8), test (8), Vocabulary (8), Internet (7), art (6), biology (6), history (6), Australia (5), chemistry (5).

This is really quite interesting. On the one hand, we always ask ourselves how to make the Learning resource indexing better, and here we can totally "crowd source" part of the indexing, that is usually done by the experts", to end-users. If we think an end-user thought that a Thesaurus-tag was good enough to add for a resource, I can be pretty sure that it is also good enough for being an indexing term. The story can be VERY different for all tags, we do not think that ALL tags could become indexing terms, although we know they are good for other stuff.

On the other hand, being in the multi-lingual context, we have always a bit hard time with tags in different languages. At least with "Thesaurus-tags" we could easily show a translation of the tag, as we are certain it to be a good one.

There are lots of interesting things to see, for example, whether these resources previously had the same indexing term as the "Thesaurus-tag" was, i.e. was the tag redundant or does it really add some value to our system. It will also be interesting to see whether there was a trend; the resources that had poor/little indexing terms received more "Thesaurus-tags" from the end-users. Well, lots more, I guess, but that will be for another time.

Emerging search patterns on learning resources

I am hugely inspired by the stuff from J.Feinberg and D.Millen, especially by the studies that they've done on doger, the IBM internal social bookmarking service. I must admit, though, that I had missed on it a bit, I cannot believe! Anyway..

This paper is really interesting, Social bookmarking and exploratory search (2007), not least for the reason that it offers a very interesting, almost similar study design that I am planning on my log files and search pattern analysis on the MELT portal. (Great minds think a like ;p yeah, right..)

The study design is a field study of a social bookmakring service in a large corporate (IBM) with quantitative data (click level analyses of log files and boomarking data) and qualitative data like interviews.

And, this is the data that I collect for my study (Table 1). Quite simlar!

They use a categorisation of search that I will adapt to my usage:

• Community browsing (Examining bookmarks created by the community. In my case these could be lists of most boomarked items, travel well; tags; other people Favourites)
  
• Personal search (Looking for bookmarks from one's own personal collecction of bookmarks)
  
• Explicit search (Explicit search using traditional search box)

A few days ago I looked at the first logs from Melt. Here is the run-down. I have not used the same types of searches, but I will explore them for the later usage. But basically what you can see:

There were 512 search events:

• 41% Explicit searches (adv. search)
• 34% Community browsing (tagcloud)
• 25% browsing categories

What was called "click-through" in this paper is when the particular navigation path resulted in a page view. This is what I call view resources. We can see that there were 538 page views, which implies that most likely users have clicked on more than one resource as a result of a search.

• 74% of resources were viewed in search result list (srl), this means that they were results from advanced search and browsing categories
  
  
• 20% of resources were viewed as a result of community browsing (e.g. tagcloud, lists)
  
  
• 5% of of resources were viewed as a result of personal search (e.g. in Favourites)
  
  

How many searches resulted in viewing resources? I have to verify this

• 85% of explicit searches and browsing categories
• 65% of Community browsing (tag cloud and lists)

Millen et al. 2007 speculate that in their study, the a higher click-through rate indicates a more purposeful searching, whereas the community browsing was used more as an exploratrory search activity. I will need to keep my attention on this and whether I can make similar conclusions.

Most likely, anyway, I do not use click-through as an indication of intenet of using a learning resources, what I find most interesting in my study will be how many of the search activities result in a bookmark and/or rating. That is much cooler in my mind than viewing the page. Actually, I've noticed that in our system users view resources a lot, but they do not necessarily show any further interest on them.

That is why I use both implicit and explicit Interest Indicators. By Interest Indicators I mean Explicit Interest Indicators like ratings as a subjective relevance judgment on a given learning content, Marking Interest Indicators like bookmarks and tags on educational content, and Navigational Interest Indicators such as time spent on evaluating the metadata of educational resources, as well as Repetition Interest Indicators as categorised by Claypool, et al., 2001.

In this small study we can see that 19% of viewed resources ended up in users' Favourites. Again, ratings were much less, only about 6% of viewed resources ended up being rated. In the study from IBM system, they had 34-39% as high click-through. Will be keeping my eye on that.

My advisor asked me whether I could find search patterns in my logs. I think I could. In this paper (Millen et al. 2007) they do that :) and here is how: "Looking for Patterns using Cluster Analysis"

To better see the patterns of use, we performed a cluster analysis (K-means) for the different types of search activities. We first normalized the use data for each end-user by computing the percentage of each search type (i.e., community, person, topic, personal, and explicit search). The K- means cluster analysis is then performed, which finds related groups of users with
similar distributions of the five search activities. The resulting cluster solution, shown in Table 4, shows the average percentage of item type for each of four easily interpretable clusters.

Should not be too hard :)

Millen, D., Yang, M., Whittaker, S., Feinberg, J., Social bookmarking and exploratory search (2007). In L. Bannon, I. Wagner, C. Gutwin, R. Harper, and K. Schmidt (eds.).
ECSCW’07: Proceedings of the Tenth European Conference on Computer Supported Cooperative. Work, 24-28 September 2007, Limerick, Ireland

How do tags connect to the Thesaurus terms?

Our social tagging system in MELT is special in two ways:

• one, we support multi-linguality
• two, we have not only tags, but all resources that users tag also have Thesaurus terms

In that context it becomes very interesting to know how do tags relate to the Thesaurus terms that have been used to index the resources that users tag.

I took a sample of tagged resources (n=185) that have 1013 tags associated with them. Out of those tags, there are 595 distinct tags. There are 44 users.



I made a network diagram visualisation that displays the Thesaurus terms as nodes that are connected by edges to tags. You'll find it here to play around with it. Unfortunately, I found out that 24 resources did not have Thesaurus terms related to them(that's about 13%, hmmm), thus a big plumb node in the middle without a Thesaurus term.

There is another visualisation here, it's more explorative about the data.


It's rather interesting that 595 distinct tags from users can be comprised to 34 thesaurus terms. That is 17,5 tags per Thesaurus term on average. Of course it does not go like that, it's more like rich-get-richer-type of a story. In the visualisation above you can see that most tags are related to language learning, for example.

If you look at the distribution of tags you'll find that many of the top tags are also about languages. Interestingly, many of them repeat the topic of the resource, but some of them (clearly less) state something about the nature of the resource (e.g. interactive) or the type (e.g. exercise).

The problem with creating this kind of visualisation of tags on the system level will be that the resources seem to have too many Thesaurus term. If there are 5 or so indexing terms, everything becomes related to everything else. It might be interesting to either to ask limit the Thesaurus terms to three (as should be the case anyway) or ask the indexer to give one term priority over others.

The same also goes for content-based recommendations, btw. If there are too many terms, you recommend everything for everyone.

Call: WORKSHOP ON SOCIAL INFORMATION RETRIEVAL FOR TECHNOLOGY ENHANCED LEARNING (SIRTEL'08)

Good news, we are ready to roll out the call for contributions for our 2nd workshop! This time we are planning more time for discussions and brainstroming type of exercises that participants can lead! This was the feedback from last year, so you see that we are taking it seriously :)

Check out the format for contributions; Research papers and System Demos are the more conventional stuff that we welcome, whereas Hands-On proposals are there to let us all loose and to think how could we use ideas from some exiting, existing systems to enhance and support learning and teaching. Oh then, there are of course the Pecha Kucha talks. That makes me really curious: someone said that they would not really work with computer science. I hope we are able to prove that wrong ;)


WORKSHOP ON SOCIAL INFORMATION RETRIEVAL FOR TECHNOLOGY ENHANCED LEARNING (link)

in the 3rd European Conference on Technology Enhanced Learning (EC-TEL08), Maastricht, The Netherlands

IMPORTANT DATES

• Contribution Submission: June 29, 2008
• Results Notification: August 3, 2008
• Camera Ready Submission: August 31, 2008
• Workshop date: September 17, 2008
• Main conference dates: September 18-19, 2008

CALL FOR WORKSHOP CONTRIBUTIONS

After the successful first SIRTEL workshop last year, we are delighted to welcome
exciting new contributions for the 2nd Social Information Retrieval for Technology Enhanced Learning (SIRTEL) workshop:

• Research papers
• System Demos
• Hands-On proposals
• "Pecha Kucha" talks*
  

RATIONALE

Learning and teaching resources are available on the Web - both in terms of digital learning
content and people resources (e.g. other learners, experts, tutors). They can be used to
facilitate teaching and learning tasks. Developing, deploying and
evaluating Social information retrieval (SIR) methods, techniques and systems that provide
learners and teachers with guidance in potentially overwhelming variety of choices remains to be tackled.

The aim of the SIRTEL’08 workshop is to look onward beyond recent achievements to discuss
specific topics, emerging research issues, new trends and endeavors in SIR for Technology Enhanced Learning (TEL). The
workshop will bring together researchers and practitioners to present, and more importantly,
to discuss the current status of research in SIR and TEL and its implications for science
and teaching.


TOPICS OF INTEREST (but not limited to):

Technology Enhanced Learning (TEL) and Social Information Retrieval (SIR) techniques such as:

• Recommender systems
• Social collaborative searching, browsing and sharing of queries
• Social network analysis
• Game-theoretic approaches to select learning materials and learning partners in the long tail
• Social bookmarking and tagging, folksonomies
• Annotations, ratings and evaluations

Concepts for Social Information Retrieval (SIR)

• Defining the scope, purpose and objects of social information retrieval in TEL
• Defining user requirements for the deployment of SIR systems in a learning setting
• Current and new trends in SIR methods for TEL
• Approaches to TEL metadata that reflect social ties and collaborative experiences in the field of education
• Analytical modelling of strategic intentions in TEL communities
• Interoperability of SIR systems for TEL
  

Implementation of SIR in TEL

• Methods and models of SIR in the area of learning and teaching
• Social processes and metaphors in learning communities and social networks for searching, acquiring and sharing information
• Pedagogical aspects of SIR in TEL; how to scaffold students, activity patterns, etc.
  
• Integrating SIR services in existing learning platforms
• Visualisation techniques to support SIR in TEL
• Successful scaffolding techniques for SIR implementation

Evaluation of SIR in TEL

• Ideas on how can we get more empirical on evaluation
• Best practices
• Evaluation of the success and acceptance of SIR systems in the context of teaching,learning and/or TEL community building
• Challenges and enablers
• Evaluating the performance and measuring the effectiveness of SIR systems in learning applications;
• Evaluation the user satisfaction with SIR system in supporting learning and teaching, etc.

WORKSHOP SUBMISSIONS

This year we base our call for contributions on last year’s comments, where the participants wanted more time for discussions, for picking each other’s brains and to forecast how SIR could be used in TEL. Apart from more conventional contributions, we also have new formats for you to consider!

• Research papers (4-8 pages)
  to present exciting new work that is not mature enough for a long conference/journal paper. We especially value papers with focus on evaluating early results and making them available for further discussion among practitioners.
  
  
• Work in progress and System demos (upto 4 pages)
  allow participants to share the basics of their SIR for TEL applications. Papers can be short (upto 4 pages), but also different ways using screencasting or YouTube-type recordings of the demo are welcome. Include also information also needed on how others can access your system and test it.
  
  
• Hands-On proposals (1-pager)
  Got a good idea for a SIRTEL implementation? Toying with ideas for SIRTEL prototypes, either totally new ones or based on some existing application (e.g. Amazon, Flickr, Digg, ..)? Interested in “pimping-up” your current LMS or platform to support social networks?
  Create a little scenario and write it down so that others can follow your thinking. Put in a few screen shots to illustrate your point better. During the session, which you will lead, the participants will have their hands and brains-on your idea. The outcome will help you with requirements of implementations in a TEL setting. Early ideas welcome!
  
  
• Abstract for Pecha Kucha (5 min talk)
  Want to share your discussion ideas on SIRTEL concepts with others? We are listening! To leverage on the face-to-face of the workshop, we invite you to submit an abstract for CP type of presentation-discussion moment which you will lead during the workshop. Your talk can be max. 4 minutes long, the participants will decide how much discussion will follow.
  

Papers are to be submitted to: https://togather.eu/handle/123456789/274
Accepted papers will be published online as EC-TEL workshop proceedings
as part of the CEUR Workshop proceedings series.

The two best papers of the workshop will be published in a special issue of
the International Journal of Technology-Enhanced Learning (IJTEL)
http://www.inderscience.com/browse/index.php?journalCODE=ijtel

More information at the submission site. All questions and submissions should be sent to: sirtel @ cs.kuleuven.be


PROGRAM COMMITTEE

• Alexander Felfernig, University of Klagenfurt, Germany
• Barry Smyth, University College Dublin, Ireland
• Brandon Muramatsu, Utah State University, USA
• Clemens Cap, University of Rostock, TBC
• Frans van Assche, European Schoolnet, Belgium
• Fridolin Wild, Vienna University of Economics and Business Administration, Austria
• Hendrik Drachsler, Open University of the Netherlands, The Netherlands
• Jon Dron, Athabasca University, Canada
• Lisa Petrides, ISKME, USA
• Marc Spaniol, Max-Planck-Institute for Informatics, Germany
• Markus Strohmaier, Technical University of Graz, TBC
• Martin Memmel, DFKI, Germany
• Wolpers, Fraunhofer, Germany
• Miguel-Angel Sicilia, University of Alcala, Spain
• Nikos Manouselis. Greek Research & Technology Network, Greece
• Oliver Bohl, Accenture GmbH, Germany
• Rick D. Hangartner, MyStrands, USA
• Selmin Nurcan, University of Paris 1, France
• Yiwei Cao, RWTH Aachen University, Germany
  

ORGANISERS

• Riina Vuorikari, Katholieke Universiteit Leuven (K.U.Leuven) & European Schoolnet (EUN), Belgium
• Barbara Kieslinger, Centre for Social Innovation (ZSI), Austria
• Ralf Klamma, RWTH Aachen University, Germany
• Prof. Erik Duval, Katholieke Universiteit Leuven (K.U.Leuven), Belgium & ARIADNE Foundation

sirtel08

Open social and education

I wonder who is going to come up with the first OpenSocial app or widget for educational use? We certainly are talking about it, for example for our eTwinning platform. It could be cool to be able to use information about teachers collaborative networks to allow, say, better retrieval of learning resources relevant for the project, purpose or task that teachers are undertaking; link with some other sources that teachers are working on through cool widgets, etc.

I never thought that Facebook, which has lately become really popular among my friends (not early adapters), would be the seul app that would "take it all". I was glad to read this:

"The market has already decided that there's going to be a long tail of social networks, and that people are going to belong to more than one. As soon as you belong to more than one, this kind of interoperability is critical," Dash says. "Open standards win every time." wired

Hurray for open standards!

New acquitance: Semiotic Dynamics

Pretty exiting, I came across this new area of Semiotic Dynamics, which is described as "a new field that studies how semiotic relations can originate, spread, and evolve over time in populations, by combining recent advances in linguistics and cognitive science with methodological and theoretical tools from complex systems and computer science." One topic of this study field is folksonomies, which draw my attention. The stuff can look like this.

Everyone nowadays repeat the same mantra of web 2.0, but somehow this project managed to say things sets it apart:

..users are no longer limited to consuming or creating online content, they also provide the semantic scaffolding holding together such content, thus taking on an active role in shaping the architecture of online information. The collaborative character underlying many Web 2.0 applications puts them in the spotlight of complex systems science,..

"Semantic scaffolding holding together .. content", that's a pretty awesome way to put it!

The paper "Vocabulary growth in collaborative tagging systems" investigates the temporal evolution of a tagging vocabulary size (of delicious) both on a

• global level (the number of distinct tags in the entire system) and
  
• local level (the growth of the number of distinct tags used in the context of a given resource or user).

It asks questions like how does the number of tags grow?; what is the rate of invention of new tags? is the asymptotic number of tags finite (uugh, a nice way to say it)? etc...

The paper finds out that the growth behaviours are remarkably regular throughout the entire history of the system with power-law behaviours with exponent smaller than one (non of that "fat head and long thing tail"!) and across very different resources being bookmarked.

Moreover, they find that there are some intrinsic characteristics of the system which do not depend strongly on the size of the dataset, like that the average number of tags is about 3.4 (local level). If I get it all right, they conclude on this that on the local scale (resource or user) "all curves tend to lie along a "universal" growth curve with an exponent close to 2/3".

The authors of this paper also highlight that the tools and concepts from complex system science may prove valuable for understanding the structure and dynamics of folksonomies.

Some interesting papers towards this direction: http://www.furl.net/members/vuorikari/semiotic_dynamics

SIRTEL'07: la raison d'etre

"We use people to find content. We use content to find people."*

On Sept 18 our SIRTEL workshop takes place. It's gonna be "Serious Fun"! Let me just outline why:

SIRTEL'07: Raison d'etre

Recommender systems, as well as social navigation, have been around since the popularisation of WWW, that's some 15-20 years now. The idea is to help people choose the right stuff from a potentially overwhelming set of choices. To facilitate that users could be helped with information from other users, the choices made before (by themselves or similar users), the ratings or reviews other people had done, etc. (Rescnik et al., 1997)

The field of learning technologies has seen recommenders of some sort being discussed and prototyped since the late nineteens. In the review of the field in Manouselis et al (2008) we identified about 10 recommenders, and even more conceptual papers of them, but very little has matierialised so far.

Since the last few years recommenders have made a second arrival into the discussion topics of technology, or network, enhanced learning. Undoubtedly, this has been influenced by the arrival "Web 2.0" with all its ideas:

- Collaborative tagging, for example, has changed lots of ideas of how metadata should be produced and how static a metadata record should be: it's not anymore one metadata record produced by a librarian, but lots of annotational and attentional metadata by lots of users.

- Other annotations by users that express their subjective judgements have seen a huge growth too, we don't only talk about ratings or reviews in their traditional sense, but also tumbs-up or down, giving pokes to people or objects, etc.

- Social bookmarking, which allows users to create easy references to their own collections of digital resources (photos, books, links, music,..), has given a new dimension to the concept of social navigations. The link between resource-user(-tag) allows users to navigate other people's collections and thus find novel resources. Also, the same resource-user-tag link gives researchers an itch to use this information to group similar users for recommendation purposes, as well as to study the emerging networks.

- Expressing social ties between people has also brought new possibilities along. We are not only seeing networks of friends, but there are new possibilities where people can express different networks, ones for professional use, others for personal, recreational, etc purposes. Also, portability of these networks has become an issue discussed for better designs (social-network-portability group, PeopleWeb ,..).

- Something else is also happening behind the scenes. Clicksteam and user behaviour on the Web is not anymore a property of the commercial portal on which users are, but users are starting to take seriously how their "attention" is being used, who owns it, etc. Attentional metadata is a huge source of information that educationalists are also starting to take more seriously and thinking how it could be used for better serving learners and teachers (Contextual Attention Matadata, Attention Profiling Mark-up Language, Attention Trust,..). Attentional metadata can also become crucial when it comes to better understanding the intentions of a user, why are they, for example, looking for some information and for what task at hand!

- Finally, content for educational use, or rather its production, is also seeing a change. Users generate more and more of the content on the Web in general, a trend which is also seen in the e-learning. Of course, traditionally teachers have always produced lots of their own material, but now its re-use also has been facilitated (e.g. repositories/referatories). Also, the collaboration aspect is facilitated by the Web, it has become easier for people to work together on things (e.g. wikis, collaborative platforms,..). Additionally, learners produce plenty of material which also should be seen and used as educational content.

To sum-up: two main topics evolve around social context and social content. Social context is how we express the who, where and with whom, and social content are the objects or digital artefacts that are in the center of the communication, exchange and networks.

All the above has hopefully also changed how we will see the future of social information retrieval for technology enhanced learning. This workshop will all be about that! Serious Fun!

-------

N. Manouselis, R. Vuorikari, F. Van Assche, “Collaborative Filtering of Learning Objects for Online Communities: An Experimental Investigation”, accepted for publication in Computers in Human Behavior, Special Issue on ‘Advances of Knowledge Management and Semantic Web for Social Networks’, 2008.

P.Morville, 2004

Resnick P. & Varian H.R., “Recommender Systems”, Communications of the ACM, 40(3),1997

More thoughts on multilinguality and tags

Lately I've been thinking more about tags and how the fact that users use them in different languages effect on the tagging system. In the case where I work (EU+education) we want to use tags in different languages as something that unifies people rather than divides them in different sections. That is why in our system we are NOT thinking of keeping multilingual tags and other annotations separated.

This type of separation along language and/or national lines can be seen in quite a few places on the Web. For example in Amazon, the reviews and ratings are not shared between the .com and .fr version. I understand that reviews and ratings, especially from experts and authoritative reviewers, are something really culturally biased, but I would think that it is interesting for readers in the US to know how a book has been received in France.

Lately in our team we've also talked about translating tags. Like if my tags, which I have added in English would be translated by someone, or a machine, into Finnish, French, etc. I don't like that idea. If I translate my tags, for example I add a tag in English and in Finnish, it's fine. But if it is done for me, I don't think it Ok. Let me explain:

I prefer to display to users only USER generated tags, not translations (neither people done nor automated ones). The key thing with tags, and the big difference compared to normal vocabularies, is that they not only describe the resource, but are associated to a user. This relation of users, tags and resources is fundamental!

In the scenario where tags are translated the following questions arises: to which user do you link a translated tag? In my opinion (say, if pushed to an edge), if a tag is translated, it ceases to be a tag and becomes just a mere keyword.

The above does not mean that tags could not have translations or equivalent terms in other languages or in its own language. Most likely in our system we will see lots of both. But the difference is that those tags all are created by other users and can be associated to users and resources. Translated keywords can be only associated to resources. This connection of users, tags and resources becomes our main asset for connecting people across the national and linguistic borders. Let's keep it that way!

If tags are translated, they could be used for other purposes than for displaying (I mean tag clouds, social navigation, etc). Translated tags could, for example, be helpful as keywords to make the search better. If a tag is translated, it should also be indicated in the metadata of the tags.

Multilinguality of tags and etiquetas

I'm currently looking into the multilingual use of tags in different applications that allow users to taguér les favoris (=signet sociaux), music, photos, etc. and that display these etiquetas in a Nube de etiquetas = Tag-Wolke = nuage de tags. E.g. I took at quick tour on 10 collaborative tagging services to see how European multi-linguality is reflected on these services.

Lots of collaborative tagging efforts on the Web take place in English. English being the lingua-franca of the Internet, it is probably not that surprising. However, we here in Europe live in a multi-cultural and lingual environment, so traces of that should be found from here and there.

Fair enough, I was able to find French and German services (blogmarks.net, MisterWong.de, Oneview.de,..) that harbor communities of users who tag in their native language - as well as in English, too. Some people do not seem to have any difficulties in adding tags in a few different languages, e.g. talking about blogging, they add tags like "blogue", "blog" for for e-commerce "shopping" and "achat".

I also looked at some "global" services such as Yahoo!, del.icio.us, Amazon and LibraryThing.com to see how do they deal, if at all, with the issue of tags being in different languages, and in the case of Amazon and Yahoo!, who offer localised sites, how are tags managed and provided in different languages. Below I give a few examples.

Yahoo!'s MyWeb

Yahoo!'s MyWeb, which is their social bookmarking and tagging service. The service does not exist in all their localised sub-sites, but with a quick look I found it at least in Yahoo.fr, Yahoo.es, Yahoo.uk, Yahoo.de. On these respective MyWeb sites one can find popular bookmarks and tag clouds in the language of the sub-site.

In all the above mentioned sub-sites, regardless in which language I was looking at, 1116436 tags were registered. This first lead me to think that they actually have that many tags in German, Spanish and in French. Then I realised that it was a total of the tags in any languages, and they had much less tags in other languages than in English.

• 1079 in German
• 1052 in Spanish
  
• 873 in French

What is remarkable in Yahoo!, though, is that they seem to have a way to recognise the language of the tag somehow, as they are able to display German tags in their .de service and French tags in their .fr service. This is transparent to the user, so I have only little idea (although a few guesses) how they do that. This focus on languages is rather unique on Yahoo!'s service, it is not the case with any of the other services that I looked. I'll be interested in knowing what they will come up with this!

LibraryThing.com

LibraryThing.com users, as well as developers, love tags! Users actually use them, after all, most of them are book freaks who probably hang out a lot in libraries, so tagging comes easy to these folks. But also, the developers have done a few really clever things with tags and objects to tag, like the concept of "work" (a work brings together all different copies of a book, regardless of edition, title variation, or language) and combining tags (see "concepts"). The difference here to delicious "bundled" tags is that it is done once for all users.

By combining tags, some multilinguality is also taken advantage of.

Like in this example, 19th century also includes 19. Jahrhundert and 19eme siecle.

del.icio.us

Take Delicious as an example of a different approach. It is one of the most used social bookmaking services, but there is little indication to be found of hundreds of languages that exist in the world. Well, I dug a bit harder and found two different types of indications of multilinguality existing.

Either people added tags in a few languages (achat, shopping), or they added a tag like "lang:fi" to indicate the that source site was in Finnish. Also lang:fr, lang:es, lang:pt, .. were there with various amounts of bookmarks. If you know if this was a user initiated activity or whether delicious encourages it, let me know. I could not find anything on it.

Amazon

I also looked at Amazon.com and Amazon.fr, funnily enough, the Frencheis do not even get to tag! (not that tags have been taken up in Amazon in the first place...) Moreover, they only get the reviews that are done by the users of the fr-site, not by the users of the .com-site. That sounds a bit silly, but maybe preserves a way to keep the cultural taste intact.

Different strokes for different folks

It seems to me that not many sites have paid much attention to the issue of multilinguality, however, it might also well be that it is not an important issue to them. Take for example these two German bookmarking sites, Mister Wong and Oneview.de, and compare the Top-50 tag lists.

MrWong.de (image on the left) has mostly English terms in their Top-50 and they are very Web2.0 and developer oriented.

Oneview.de has many German terms (image on the right) and they seem to cover larger area than only Web2.0, there are terms about holidays, music, etc.

So, each user group seem to share the terms that are important for them. Most likely this is also the case in Delicious, by using English tags I, as a Finn, can easily share interesting bookmarks on, say, folksonomies with everyone else in the world who is interested in it.

This to say, I also think that multilinguality has a place in tagging and we in EUN are very interested in the issue. Currently, we are running a pilot where teachers can add tags in their own language(s) to learning resources. We try our best to be able to recognise the language of the tags, as we think cool things can be done with it. But more about that another time.

Sites that I looked at

French:

• social bookmarks =signet sociaux
• tag, taguer
  

Blogmarks, http://blogmarks.net/
- most popular tags are in English
- 577366 bookmarks
- people sometimes add tags both in French and English (e.g. blogue, blog; tag cloud nuage de tags)
- Tags in French also, but they don't seem to have that many users, tried some about 10 or so


Bookmakrs, http://bookmarks.fr
- call bookmarks "favoris" and tags "tags"
- most popular tags in different languages, in 50 most popular tags: 14 in French and 1 in Russian
- maybe only about 2500 bookmarks (25x107 pages)
- some people had indicated the language of the source page in En

In German:

• Tags as "Schlagworte", "tags"
• "Tag-Wolke"
• bookmarks " Lesezeichen" (Soziale Lesezeichen)
  

Netselektor, http://netselektor.de/

Mister Wong, http://www.mister-wong.de/?tag_type=list
- 2.142.735 Bookmarks
- very techy, lots of En tags

Oneview http://www.oneview.de/home/index.jsf
- Trendwolke http://www.oneview.de/home/discover.jsf
- more tags in German in general areas


Yahoo! MyWeb

Yahoo! Fr
- top tags http://fr.myweb2.search.yahoo.com/myweb?dg=6&sort=pop
- 1 116 436 tags in the "nuage de tags", although 873 in French.
- in top 50 tags mostly in French, however, many terms are easily understandable like web2.0, internet, google, yahoo..

Yahoo! De
- top tags http://de.myweb2.search.yahoo.com/myweb?ei=UTF-8&dg=6&dmode=vtags&sortby=count
- 1.116.436 tags in "Tag-Wolke", although only 1079 in German
- in top 50 most entirely in German, but many terms like computer, software

Yahoo! es
- toptags http://es.myweb2.search.yahoo.com/myweb?dg=6&sort=pop
- call tags "Etiquetas" and tagcloud
- 1.116.436 tags in "Nube de etiquetas", 1052 in Spanish
- the top 50 mostly in Spanish, only a few terms like web2.0, blog, yahoo



Flickr
http://www.flickr.com/photos/tags/

- interface offered in different languages, however,
- most popular tags are the same in all different interface languages, thus could think that there is no separation of languages.


Delicious

- All top 50 tags in English
- no other interface languages
- some tags do exist in different languages e.g. achat, shopping; ..
- some tags indicate the language of the source; lang:fi,..

Google

if I understand right, google does not even display the tags from their users? Please, correct me if you know anything about using their bookmarks.

Last.fm

- in LastFM all the tags are the same, although they offer different interface languages
- tags in many language exist, especially if you look for bands from different countries e.g. suomipoppia

Massively multiplayer object sharing by R.Sinha

I've followed some stuff from Rashmi Sinha, and I think every once in a while she comes up with good ideas. Like I liked the stuff early on that she did on the recommenders and the focus on user-centric design. Sometimes I just don't like her stuff, it sounds very popularistic and her references are, well, not very academic. But then again, maybe she does not need to be either..

Anyway, this slideshow has cool ingredients. I like the idea of object/artefacts in the center of the social networks, that's why I'm a big fan of social bookmarking, for example. I really don't care that much about connecting to people that I don't know (mySpace) or even using LinkedIn (what's the point, you get a list of people, but no substance..), but when I can connect through items and tags to people's stuff that I find interesting, I find it useful.

In the slideshow Sinha talks about models of 2nd generation networks (the 1st g was only about people):

• Model 1: Watercooler conversations
  (around objects e.g., Flickr, Yahoo answers)
• Model 2: Viral sharing (passing on interesting stuff, e.g., YouTube videos)
• Model 3: Tag-based social sharing (linked by concepts. e.g., del.icio.us)
• Model 4: Social news creation (rating news stories, e.g., digg, Newsvine)
  

Then, further on, she talks about Cognitive Diversity, which I also find really important. It's related to the continuum of wisdom of crowds vs. stupidity of mobs. What I got out of the slide 29:

• Good answers need many perspectives, thus many perspectives are needed otherwise groups become too homogenous, which might have its dangers also (stupidity of mobs, see Digg for that ;). If all the new members are too similar and like-minded, they don't bring anything new to the group (that's why we want serendipity from recommenders!). Diversity reduces groupthink (think of Digg again and how fast not favourable stuff gets buried), groupthink is bad and only way to fight that is diversity.
  

Moreover, she also talks about the importance of social influence condition and about Watt's study.

Lastly, some design principles:

• Make system personally useful: For end-user system should have strong personal use; Self-expression (e.g., Newsvine);Social status: Digg
• Don’t count on altruism: System should thrive on people’s selfishness
  

A kid-Ceo designs an educational game

A kid designing a game for other kids, that's not SO new. But this kid designs an educational game for other kids and plans to make a million out of it by middle school, that is in a year's time! This kid is pretty amazing! I have no doubt that he won't do it. After all, he's already in the Wally.



Makes me think if we got it all wrong with all the e-learning things and going digital..

More semantics to tags - emerging trends in tagging

Sometimes a word is not enough, so many more words are needed to explain what is it that is meant by that word.

That seems to be the case with tags. Uumh, they are ambiguous, did you know that?

First I think it was Technorati, they came up with the concept of WTF .

WTFs are short blurbs that explain the buzz around people, things, or events—why the hot topics are so hot—and you can vote the best ones to the top.

Now I saw it in del.icio.us, you can create a tag description to explain to others what is it that you really mean by your tag (it's really getting from being personal to being public). Very interesting. You now add metadata to your tags (e.g. meta-metadata) to describe the meaning by an author of that tag.

Well, if this trend keeps going, soon we can expect to fill-in all the LOM metadata fields ;) No, seriously, Sir Berners-Lee must be exited about this turn!