geistlogistic

ICSS — the Hawaii International Conference on System Sciences — takes place each January in Hawaii. This coming year, the conference is January 4-7, at the Grand Wailea hotel, on the island of Maui.

http://www.hicss.hawaii.edu/

This is a call for papers for a new minitrack on Learning Analytics and Networked Learning. Papers are due **June 15, 2011** submitted through the conference system. Please feel free to contact me or either of my co-organizers for feedback on suitability for the minitrack.

Other minitracks will be of interest to members of this list, including ‘Social Networking and Communities’ co-chaired by Karine Nahon and Caroline Haythornthwaite. (See:http://haythorn.wordpress.com/hicss-minitracks-cfp/).

CALL FOR PAPERS

LEARNING ANALYTICS & NETWORKED LEARNING

This minitrack calls for papers that address leading edge use of technology or system design to analyze, support, and/or create learning and learning environments. The remit is wide and calls for papers that use technology to examine how social learning happens, use data from learning environments to support learning processes, and examine new practices of formal and informal learning on and through the Internet. Papers that fit this minitrack fall under new and ongoing areas of learning research that may be referred to as learning analytics, networked learning, technology enhanced learning, computer-supported collaborative learning, ubiquitous learning, and mobile learning. Of particular interest are papers that capture, analyze and show novel use of data produced from online learning environments, develop and/or test methodologies for analyzing online learning, address automated data collection and analysis in support of learning, professional development and knowledge creation, and discuss issues and opportunities relating to information literacy, literacy and new media, ubiquitous learning, entrepreneurial learning and/or mobile learning.
We envision papers that

• address the use of automated data capture to follow and analyze learning processes
• develop methodologies for analyzing online learning
• develop metrics for characterizing and following learning trends online
• test the validity of automated data for capturing a true representation of learning and knowledge creation
• analyze and/or support the role of social networks in learning
• report on the development and maintenance of innovative online environments for learning
• discuss trends in learning on and through the Internet, including issues and opportunities relating to information literacy, literacy and new media, ubiquitous learning and entrepreneurial learning
• examine economic models, trends and markets for online learning, including open source and open access models
• examine the foundations for learning in online networks, crowds and communities
• examine the design and facilitation of learning in online networks, crowds and communities
• examine the validity of information and learning processes online, and trust in online information sources for learning
• address the role of particular devices: laptops, mobiles, OLPC  in learning
• examine trends in how we learn with and through technology in secondary and higher education, workplaces, society, developed and underdeveloped nations
• discuss ethical issues relating to learning online, including issues relating to data capture, analysis and display, and learning about controversial subjects or anti-social activities.

SUBMIT INQUIRIES TO:

Caroline Haythornthwaite (Primary Contact)
University of British Columbia
haythorn@interchange.ubc.ca

Maarten de Laat
Open University of the Netherlands
maarten.delaat@ou.nl

Shane Dawson
University of British Columbia
shane.dawson@ubc.ca

Related articles

• Learning Analytics: A foundation for informed change in education (elearnspace.org)
• Learning Analytics: The Holy Grail for Education? (kylemackie.wordpress.com)
• Professional Learning Network (ccmdctechnology.wordpress.com)
• Thoughts On A Learning Network (educationinnovation.typepad.com)

Yesterday, I gave a workshop on “How to use the Handover Toolbox to improve Handovers in Health”.  I presented a so called toolbox that is based on Elgg community portal and customized to the needs of the medical specialists to share knowledge to improve handover practice between General Practitioners and Hospitals. Most of the participants are not Web2.0 users so a lot of explanations and hands-on experiences were needed to disseminate the networked based learning ideas to the partners.

But the workshop was very fruitfully, we had very inspiring discussions on the future of training in health and the role of social networks. There will be some interesting Journal articles coming out of this cooperation. Below you can find the slides I used during the workshop.

The first presentation this year was given at the Learning Network seminar series at CELSTEC. Special guest was Wolfgang Reinhardt from the University of Paderborn who provided his view on data science in relation to awareness improvement for knowledge workers. The dataTEL presentation is based on the ECTEL10 but it also includes the latest developments on TEL recommender after the dataTEL System Marketplace at the RecSysTEL workshop what was a point of change in the research community. In the presentation below I show some of the changes and the new developments. Surprisingly, we had a very controversial discussion, more controversial than at the ECTEL conference.

I sum up the comments shortly:

• The collected datasets are far to small to conduct proper information retrieval on it.

But maybe they present the majority of datasets that are available in education so we have to adjust our techniques.

• Not all of the datasets are related to learning, esp. Mendeley.

Yes, that is correct but why should we limit our self as it is already quite a challenge to get a datasets.

• The privacy protection right will stay so we will never have the opportunity to use the student data from a LMS like Blackboard for further analysis.

But we could ask the students if they agree to give us there data for research purposes and be very explicit what we want to do with it. European Schoolnet did the same with the users of the eTwinning project.

One of my Bachelor groups developed a SQL wrapper for Netlogo.
At CELSTEC we work quite frequently with simulation environments for social science simulation. Netlogo is nice to get a fast prototype for a social phenomena especially when it is about swarm-based behavior and emerging effects like in Learning Networks. Until now it was always a pity that we could not connect real data like from the ReMashed system to the simulation to create a forecast of a certain Learning Network. But it looks like that the students Jan Blom, Rene Quakkelaar and Mark Rotteveel created a promising solution for that.

We will test the wrapper in the upcoming weeks; critical is how the wrapper reacts when the traffic between the simulation and the database is increasing.

Related articles

• Taking a fresh look (eurekalert.org)
• http://ccl.northwestern.edu/netlogo/
• http://cress.soc.surrey.ac.uk/s4ss/

Because of the Aging Society and the growing-together of Europe the number of handovers is increasing dramatically. A handover in the medical domain is a referral or a discharge between general practitioners and hospitals. Incorrect handovers are cost intensive and risky in Europe’s medical domain. They often lead to adverse and life threatening events. It is therefore important to improve handover practices between all involved medical parties and between the European member states in general.

We address these challenges in the European FP7 funded HANDOVER project that investigates how to improve the current situation and increase the quality of medical care. Medical training for handovers has been identified as the major intervention to improve the handover practice.

In the presentation below we present our methodology approach for the design of a customized Learning Network for the target group. For the requirement analysis we examined 222 interviews with medical professionals and patients from four European countries (Spain, Poland, Netherlands, Sweden) to explore the factors that inhibit or facilitate the handover practices. In addition, 92 medical professionals filled out a questionnaire and 99 training experts from the participating countries were interviewed.
The results from the questionnaire and interviews were used to create writing personas from which a use cases analysis was performed leading to the prototype design of a web-based training toolbox that follows the Learning Network concept. The toolbox addresses the design of effective handover training, and the awareness rising of the importance of handover practice in general. The toolbox has a strong communication functionality. In this way the toolbox not only helps training experts to design their own customized training but also to communicate with other training experts and exchange digital training content with them. The overall toolbox can be seen as a community of practitioners that contribute, share, combine and enrich knowledge about handover training in Europe. The project brings Web2.0 technologies and communication approaches to the health field.

Here you can find the presentation given at Tallinn University, Estonia 03.09.2010. It gives an overview of the things we are developing in the Learning Networks program and how we want to move on to address Digital Ecosystems. It is the first scratch of the new cluster we are building at CELSTEC. The Educational Technology Group at Tallinn has similar ambitions so it is worthwhile to align our research agendas and look for synergies. Many thanks for the invitation to Tallinn!

My first blog posting in 2009, the year started with good news regarding my theoretical article that I submitted to the  Journal of Digital Information (JoDI) in January 2008. Now, I have 3 publication out of 4 needed to finilise my PhD project. The article with the title: ‘Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning’ is finally published in JoDI Vol 10, No 2 (2009)! The article argues why recommender systems have to be adjusted to the specific characteristics of learning in Learning Networks. It describes a number of distinctive differences for personalised recommendation to learners when compared to recommendations for consumers. Similarities and differences for informal and formal learning are discussed and used to define the recommendation goal that recommender systems in informal learning networks have to address. The article further suggests an evaluation approach for recommender systems in Learning Networks.

What I really like about this issue are the prominent Co-authors. I still remember reading the latest research findings from Tiffany Y. Tang, Gordon McCalla (I-Help System) and being inspired by Jon Dron, Terry Anderson when I was starting my PhD in 2006. Now, my article stands next to their contributions .

To my surprise, Tang and McCalla took a similar focus for their article like me. They also discuss differences for recommendations in e-learning compared to recommendations to commercial domains. They also identify pedagogical features which are necessary to make appropriate recommendations of papers to students in an e-learning domain. These pedagogical features distinguish e-learning domains from many commercial domains where the only key factor is a user’s likes and dislikes. I especially like the method they use to evaluate the pedagogy reasoning for recommendations in e-learning.

For the near future, I focus now on the submission of my final Journal paper for the thesis and I want to prepare a conference paper where I present ReMashed – Recommendations for Mashup Environments. ReMashed is a kind of technical solution coming along with my thesis. I will present ReMashed the first time next Monday at the Winterschool in Innsbruck. Afterwards I will inform you more detailed about it.

Now it’s time for bug fixing.

On Sunday the last day of the RecSys08 was the Doctorial Symposium. The academic world was represented by Pearl Pu (Switzerland), Joeseph Konstan (USA), Alexander Felfernig (Austria) and Francesco Ricci (Italy). 9 PhD projects were invited to present their recent results and to get feedback for their further development. The invited PhDs beside me were: Olga Santos (Spain), Danielle Lee (USA), Erich Teppan (Austria), Marcos Domingues (Portugal), Akhmed Umyarov (USA), Linas  Baltrunas (Italy), Leobino Sampaio (Brazil) and Youngok Kwon (USA). It was a very good an intensive day with lots of discussions which I missed a bit during the main conference.
I presented the follwing slides in the symposium:

The overall comments on my project were quite positive. The Symposium enjoyed the clear structure and the experimental design of the studies in my PhD project.

Alexander suggested me to apply also model based recommendations like Bayesian predictions for my recommendation task. Actually, in the beginning of my project we decided to focus on memory based techniques and for collaborative filtering. However, after having some experiences with recommenders in TEL I agree with Alexander that model based predictors are also suitable. Alexander further asked for the development of new algorithms and I explain that the focus of my research is on using existing algorithm in the TEL field to finally find the most suitable for informal learners.

Joseph stressed the aspect of recommending learning items and sequence of items (based on the emerging behavior of the learners in a Learning Network – a learning path). He emphasized the challenges of recommending sequence of items and further explained that he could imagine that the TEL field might offer some interesting findings because differently to product recommender the world of education is quite well known. Finally, he stressed the informal learning aspect of my project. He highlighted that in informal learning you never know the structure of a learning item like in formal learning offers. He further described differences of the recommendation task in informal and formal learning like I did in one of my papers. The big challenge therefore is to mine the purpose of an informal learning item. Joe could imagine to analyze the purpose of a particular learning item based on sequences of learning items. A very inspiring idea, I haven’t thought of so far.

The DS was really great and I only can encourage PhDs that are working on recommender systems to present their ideas in this setup.

Another updated on the current simulation project. My paper about the experimental design of the simulation was accepted for the SIRTEL workshop (Social Information Retrieval in Technology Enhanced Learning) at the EC-TEL conference 2008. The paper with the title ‘Using Simulations to Evaluate the Effects of Recommender Systems for Learners in Informal Learning Networks’ reports the theoretical background, underlying models and the experimental design for the ongoing simulation study. I’m looking forward to the conference and the feedback I will get on the workshop. The article is available in Dspace and will be published in the CEUR workshop proceedings.