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Subject: CFP: Learning Analytics & Knowledge 2012, Vancouver BC
From: Caroline Haythornthwaite <[log in to unmask]>
Reply-To:Caroline Haythornthwaite <[log in to unmask]>
Date:Thu, 8 Sep 2011 09:24:47 -0500
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*****  To join INSNA, visit http://www.insna.org  *****

LAK12: 2nd International Conference on Learning Analytics & Knowledge 

Vancouver, 29 April – 2 May 2012 
http://lak12.sites.olt.ubc.ca 

KEYNOTE SPEAKERS 

KATY BÖRNER is the Victor H. Yngve Professor of Information Science at the 
School of Library and Information Science 

GEORGE SIEMENS researcher and strategist with the Technology Enhanced 
Knowledge Research Institute at Athabasca University in Alberta, Canada 

BARRY WELLMAN  S.D. Clark Professor at the Department of Sociology, 
University of Toronto, Director of NetLab. 

Challenges & Opportunities 

We are experiencing an unprecedented explosion in the quantity and quality 
of information available not only to us, but about us. We must adapt 
individually, institutionally and culturally to the transition in technologies and 
social norms that makes this possible, and question their impacts. What are 
the implications of such data availability for learning and knowledge building 
— not only in established contexts, but also in the emerging landscape of 
free, open, social learning online? 

Within the learning technologies research and development community, this 
question has catalyzed the International Learning Analytics & Knowledge 
Conference, now in its second year. Learning Analytics is concerned with the 
collection, analysis and reporting of data about learning in a range of 
contexts, including informal learning, academic institutions, and the 
workplace. It informs and provides input for action to support and enhance 
learning experiences, and the success of learners. Learning and Knowledge 
Analytics 2012 supports the emerging academic field by connecting the 
community of researchers and developers, creating and disseminating new 
developments and practices, studying transformations, and providing 
ongoing evaluation and critique of the conceptual, technical, and practice 
outcomes. 

Educational institutions are under intense pressure to make improvements 
and savings, while still delivering on their mission to support learners using 
all possible means. The effective use of information about learners can be 
part of the solution to this dilemma. Analytics seeks to provide rapid, real 
time answers to questions such as: 

•	Who is at risk of failing? 
•	What kinds of interventions make most difference to learners? 
•	How am I doing compared to my peers? 
•	How effective is this course? 
•	Who are the key people in this community? 
•	Are there quality learning conversations in this forum? 
•	What is or can be different about learning and learning experiences 
when combined with learning analytics? 

Social media, open data, web analytics, semantic web, data mining and 
recommendation engines may hold the answers, but they also combine to 
create a powerful but complex data deluge, which surpasses the ability of 
organizations to make sense of it. What is needed to tame this technical 
complexity for learners, educators and administrators? 

While ‘business intelligence’ infrastructure is well established for certain kinds 
of performance indicator, is there an equivalent for tracking the rather more 
complex processes of authentic learning and knowledge sharing? Is there the 
risk that learning analytics will damage learning and knowledge flows by 
monitoring and measuring them inappropriately? 

These technical, pedagogical, policy and social domains must be brought into 
dialogue with each other to ensure that interventions and organizational 
systems serve the needs of all stakeholders. 

Topics 

We invite submissions on topics including but not limited to: 

Conceptual & Empirical 
•	Connections between learning analytics and the learning sciences (e.g., 
self-regulated learning, critical thinking, sense making and learning analytics) 
•	New models of learning enabled by analytics 
•	Educational research methods and learning analytics 
•	Learning analytics in relationship to other fields (e.g., institutional 
analytics; educational data mining) 
•	Communicating analytics (e.g., data selection, display, visualization, user 
groups) 
•	Ethical considerations (e.g., privacy and ownership) 
•	Learner modeling 
•	The influence of analytics on designing for learning 
•	The influence of analytics on delivery and support of learning 
•	The study of emotion, flow, and affective data in learning analytics 
•	Validating analytics empirically 
•	The limits of web analytics 

Technical 
•	Social network analysis 
•	Cross-platform and cloud learning analytics 
•	Learning environments that capture different kinds of data 
•	Software development and use in analytics 
•	The role of knowledge representation and ontologies in learning 
analytics 
•	The semantic web and linked data: meaning in connections 
•	Data mining in learning analytics 
•	Artificial intelligence in learning analytics 
•	Internet of things (sensors) and learning applications 
•	“Big Data” applications and opportunities in learning and education 
•	Latent semantic analysis/natural language processing 
•	Attention metadata 
•	Architecture of learning environments and implications to learning 
analytics 

Application 
•	Visualization: data, learner networks, conceptual knowledge 
•	Predictive applications of data 
•	Interventions based on analytics 
•	Social and technical systems to manage information abundance 
•	Personalization and adaptivity in the learning process 
•	Corporate and higher education case studies of learning analytics 
•	Learning analytics for intelligent tutoring systems 
•	Open data: data access for learners 
•	Harmonizing individual learning with organizational learning 
•	Organizational learning and knowledge sharing models 
•	Importing insights for existing analytics 
•	Use of learning analytics in centralized (learning management systems) 
and decentralized (personal learning environments) settings 
•	Planning, deploying, and evaluating enterprise-wide learning analytics 

Submissions 

The following types of submission are invited: 

•	Full Papers: Use a full paper to share substantive conceptual, technical 
and empirical contributions. 10 pages max. 
•	Short Papers: Use a short paper to share preliminary conceptual, 
technical and empirical contributions. 4 pages max. 
•	Design Briefing: Do you spend more time building learning analytics 
tools than writing about them? Specifically with people like interface 
designers, system architects and programmers in mind, use a briefing to 
share a design concept, tool or challenge.  4 pages max. 
•	Demonstrations: A carefully planned, live demonstration of a tool is the 
most engaging and informative way to show interactive software, ranging 
from early prototype to robust product. 1-2 page abstract, clarifying the 
maturity of the tool, including at least one link to a current demo movie. 
•	Panels: Panels provide the chance for delegates to hear a range of 
speakers air a topical issue, e.g. diverse approaches to a problem, or a debate 
on a hot topic. 2 pages max, including the names of confirmed panellists. The 
final paper from the Panel’s chair may be up to 4 pages, including panellists’ 
position statements. 
•	Workshops: Workshops (April 29, 2012) provide the opportunity to 
explore learning theory, analytics, methods and tools in depth. Workshops 
should be designed to be interactive and may reflect for example, 
compilations of short and/or enlightening presentations, demonstrations, and 
instructional workshops. The length of the Workshop sessions can be a half or 
full day allowing for sets of interactive activities for experience sharing and 
brainstorming. Please use the workshop/tutorial template, outlining the 
significance of the topic, the workshop format, and your track record. 
•	Tutorials: Tutorials (also April 29, 2012) provide the chance to take 
participants deep into a specific tool or technique in which you are 
experienced, or an introduction to a topic/class of tools. This could be as 
short as 1 hour, to a half day. Please use the workshop/tutorial template for 
submissions. 

Full and Short Papers, Design Briefings, and the abstracts for Demonstrations 
and Panels will be published in the main proceedings. 

Submission and Publication 

LAK2011 proceedings will be published in the ACM Digital Library 
International Conference Proceedings Series, and we expect 2012 to follow. 

Author guidelines on the website. 
-------------------------------------- 
Caroline Haythornthwaite 
[log in to unmask]
--------------------------------------
Caroline Haythornthwaite
[log in to unmask]

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