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It's About Time: Addressing the Many Challenges of Analyzing Multi-Scale Temporal Data

posted 2 Jul 2012, 02:04 by ICO Education   [ updated 2 Jul 2012, 02:10 ]
Call for participation: Workshop at the Alpine Rendez-Vous 2013
January, 28 - February, 1st 2013
Villard-de-Lans, Vercors, French Alps  -
Summary

We invite all researchers studying technology enhanced learning across time at multiple time scales to join our workshop examining various ways to do such analyses. This workshop will be the third in a series of conversations about examining multiple temporal data streams generated by interactions between people and tools in the course of learning activities. 
Submission deadline is September 1st 2012. 

The workshop will be held at the Alpine Rendez-Vous 2013, January 28 - February 1st 2013 in the French Alps. 

Organisors 
Inge Molenaar (University of Amsterdam), Alyssa Wise (Simon Fraser University), Ming Ming Chiu (University at Buffalo, State University of New York), Britte Haugan Cheng (SRI International), Vanessa Svihla (The University of New Mexico) and Dan Suthers (University of Hawaii at Manoa).

Topic of the Workshop
This workshop aims to bring together researchers who are addressing the challenges of characterizing and analyzing data related to technology enhanced learning over time at multiple time scales. We aim to share, discuss and develop both conceptual understanding of and methodological techniques for the many temporal aspects of learning (e.g. multiple data streams, multiple levels of analysis, multiple timelines etc.), and the requisite coordination needed.
Recent research has begun unpacking learning processes (especially dynamic group interactions ) and their influence on learning outcomes through the lens of time, but improved theories and methods are needed to fully utilize temporal information. In addition, many studies of technology-enhanced learning involve concurrent collection of multiple types of data (for example, computer activity logs and chats, or
discourse and gesture), resulting in distinct but related data streams that are often based on different conceptual frameworks, different kinds of units of analysis (which may be discrete or continuous), differing levels of aggregation, and varying timelines/timescales. New approaches are needed to integrate analysis of data streams, thereby revealing how phenomena co-occur, interact, and facilitate learning, and furthermore, show how they dynamically affect one another over time. This workshop also ties in to an emerging interest in collaborative learning research on connecting levels of analysis by supporting the investigation of questions about how macro-level phenomena at group and network levels can emerge from and constrain micro-level dynamics of interaction over variable time periods. A temporal lens can help develop an understanding of how patterns (e.g., turn-taking) or dynamics (e.g., cycles of collaboration) unfold, providing insights into collaborative activities of connected learning. Additionally, insights from such temporal analyses can consider how the configuration of one event or phase of activity may influence the likelihood of subsequent ones, and the mechanisms of how macro-level group and community properties emerge from and constrain these micro-level dynamics.

For further information please see http://engaged.hnlc.org/story_comments/list/18

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