[edm-announce] Workshop on Data Analysis and Interpretation for Learning Environments (DAILE’13) at 4th STELLAR Alpine Rendez-Vous (ARV) in Villard‐de‐Lans, Vercors, French Alps
- From: Vanda Luengo <Vanda.Luengo@xxxxxxx>
- To: edm-announce@xxxxxxxxxxxxx
- Date: Mon, 16 Jul 2012 14:16:35 +0200
Workshop on Data Analysis and Interpretation for Learning Environments
(DAILE’13)
*Held at the 4^th STELLAR Alpine Rendez-Vous (ARV) in Villard‐de‐Lans,
Vercors, French Alps*
*January 28 - February 1, 2013*
**
Website:http://jedi.wu.ac.at/DAILE13/
*Deadline for submission: *
·*Initial Experiential Report:31^st August 2012*
·*Final Paper: 15^th October 2012*
**
Goal
The main focus of the workshop DAILE’13 is to elaborate as well as
integrate various computational approaches for /analysing/ and
/interpreting/ data from technology-enhanced learning (TEL)
environments, thereby serving three goals: (i) improving learning and
instruction; (ii) designing learning software; (iii) developing deeper
understand of learner and teacher models.
In the spirit of “learning analytics”, we will extend the focus from
closed within-system usage of computational analyses towards putting
humans in the loop of making use of analysis results, for instance, in
terms of monitoring and reflection support. This entails adequate
modalities of information provision, including visualisation techniques
and visual metaphors.
Contributors are invited to share sample datasets of user interactions
with TEL environment and an analysis approach in the form of an
experiential report, which will then be further developed into a
scientific paper in the scope of the workshop.
Rationale
“/If you cannot measure it, you cannot improve it/” (a.k.a. Sir William
Thomson, n.d.). This dictum has been employed to justify the
quantification of theoretical concepts of various disciplines. We
further claim that /“if you cannot *interpret* what is measured, you
cannot improve it“/. Arguably one can measure (almost) anything in some
arbitrary way. The compelling concern is whether the measure is
/meaningful/, /useful/ and /valid/ to reflect the state or nature of the
object or event in question. The key attribute “meaningfulness” hinges
critically upon *interpretability* of data.
Recent initiatives in the field of technology-enhanced learning (TEL)
consider establishing an open learning environment built upon a
dynamically evolving network of people, artefacts, and tools as the most
important outcome of learning. Consequently, measuring and interpreting
the *dynamics of and interactions within flexible TEL environments*
based on digital traces (action logs, versions of digital artefacts) is
of tremendous importance for various target groups.
In the context of open learning environments, a specific challenge is
the specification, identification and interpretation of errors through
error patterns. However, error identification is not a clear-cut process
in certain situations as evaluators may diverge on what constitutes an
error. Besides, the issue of data interpretability (and the
transferability of findings) will further be complicated by
collaborative learning scenarios, and community effects in large-scale
learning environments with huge networks of learners are intriguing to
explore.
Workshop Topics
Given the interdisciplinary nature of the workshop, researchers and
practitioners from TEL, Human-Computer Interaction (HCI), the Semantic
Web, and data-driven research (Learning Analytics, TEL Recommenders,
Educational Data Mining etc.) are relevant contributors. The following
topics of interest, albeit non-exhaustive, are identified to invite
submissions:
·Modelling, capturing, and processing of user interaction data in
learning environments
·Anonymization and privacy preservation of real-world datasets
·Educational data mining on interaction traces and user-generated content
·Learning and Visual Analytics for institutions and individuals
·Interpretability and transferability of user interaction patterns in
learning environments
·Evaluation of pedagogical models using digital traces of learners
·Effects of learning technology on user behaviour and competence development
·Implications of continuous and discrete values for user interface and
usability issues
·Social network analysis and community effects in large-scale learning
environments
·Feedback for teachers, learners and developers
·Process analysis (description of traces analysis and transformations steps)
Workshop Format and Submission Procedure
Contributors are invited to submit experiential reports including
example datasets, a proposed approach to analyse the data as well as
preliminary or expected findings. Based on a voluntary mentoring
process, contributors could be supported by the programme committee (PC)
members in co-authoring a scientific paper from the experiential report.
There will be two types of contributions:*full papers with up to 6
pages* describing substantial, completed work or *position papers with 2
pages* describing either results that can be concisely reported or work
in progress. Papers should be formatted with the template
(http://www.acm.org/sigs/publications/proceedings-templates) and
submitted as PDF-file to:
http://www.easychair.org/conferences/?conf=daile13. All peer-reviewed
scientific contributions will be published as CEUR workshop proceeding
(http://ceur-ws.org/).
Important Dates
·Submission of experiential reports (example dataset, approach): August
31, 2012
·Paper submission (end of the mentoring process, if applicable): October
15, 2012
·Notification of acceptance: October 31, 2012
·Camera ready submission and online discussions until: November 30, 2012
·Workshop date: January 28 - January 31, 2013
Programme Committee (to be confirmed)
·Denis Bouhineau, University Joseph Fourier, France
·Maria Francesca Costabile, University of Bari, Italy
·Hendrik Drechsler, CELSTEC Heerlen, The Netherlands
·Gregory Dyke, Carnegie Mellon University, USA and CNRS Lyon, France
·Denis Gillet, EPFL, Switzerland
·Sergio Gutierrez Santos, Birkbeck, UK
·Milos Kravcik, RWTH Aachen, Germany
·Marten de Laat, Open University, The Netherlands
·Manolis Mavrikis, London Knowledge Lab, UK
·Agathe Merceron, Beuth University of Applied Sciences, Germany
·Niels Pinkwart, Clausthal University of Technology,Germany
·Christoph Reffay, ENS Cachan, France
·Wolfgang Reinhardt, University of Paderborn, Germany
·Cristóbal Romero, University of Cordoba, Spain
·Markus Strohmaier, Graz University of Technology, Austria
·Dan Suthers, University of Hawaii, USA
·Stefan Trausan-Matu, University Politehnica of Bucharest, Romania
·Sebastián Ventura, University of Cordoba, Spain
·Stephan Weibelzahl, National College of Ireland, Ireland
Organisers
·Felix Mödritscher, Vienna University of Economics and Business, Austria
·Vanda Luengo, Domaine Universitaire de Saint-Martin d'Hères, France
·Effie Lai-Chong Law, University of Leicester, UK
·Ulrich Hoppe, University of Duisburg-Essen, Germany
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