LA@ICCE2019: 6th ICCE workshop on Learning Analytics (LA): scaling up evidence-based institutional LA practices Howard Beach Resort Kenting, Taiwan, December 2-6, 2019 |
Conference website | http://ilt.nutn.edu.tw/icce2019/index.html |
Submission link | https://easychair.org/conferences/?conf=laicce2019 |
Submission deadline | August 16, 2019 |
The increasing amount of data generated in digital learning contexts provides opportunities to benefit from learning analytics as well as challenges related to interoperability, privacy, and pedagogical and organizational models. As a consequence, new methodologies and technological tools are necessary to analyse and make sense of these data and provide personalized scaffolding and services to stakeholders including students, faculty/teachers and administrators, as well as parents. Pedagogical and organisational models must also be incorporated in order to take advantage of the personalized scaffolding and services to ensure productive learning and teaching. In addition, access to data from different sources raises a number of concerns related to data sharing and interoperability, and protection of privacy for individuals and business interests for institutions.
As the field of learning analytics continues to mature, it is increasingly important to analyze evidence of effective LA implementations and facilitate dissemination through the community. The theme this year will focus on evidence at three different levels of a conceptual framework:
- Micro – small scale implementations in an individual class or course
- Meso – implementations that span multiple stakeholders at a single institution
- Macro – multiple institution, state or national level policies/practices
Participants are encouraged to share their research as a paper on either analyzing evidence on effective LA, or relating their contribution from the perspective of the three levels of implementation and adoption of LA. We also call for papers that cover technical, theoretical, pedagogical, as well as organisational issues in learning analytics.
List of Topics
We also welcome submissions on some of the topics concerning LA from the following (though not restrictive) list:
- Making sense of learning analytics
- Software systems and tools
- Implementation and organisational development
- Pedagogical models and learning analytics
- Gathering diverse learning data, e.g., related to linked data
- Algorithms for analytics based on gathered data
- Predictive models, visualisation and statistical analysis
- Privacy concerns and policy aspects related to LA
- Data sharing for learning analytics
- Evaluation and Assessment
- Standardization and Interoperability
- Challenges and approaches for scaling up LA in education practices
Important Dates
- Submission deadline for workshop papers: August 16, 2019
- Acceptance notification of workshop papers: September 6, 2019
- Final camera-ready version due for workshop papers: September 13, 2019
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Full papers (8 - 10 pages)
- Short paper (5 - 6 pages)
Publication
All accepted papers for mini-conference-style workshop will appear in one volume of workshop proceedings with ISBN and will be indexed by Elsevier Bibliographic Database. All paper should follow the paper format of the main conference.
Organizing committee
- Brendan Flanagan (flanagan.brendanjohn.4n@kyoto-u.ac.jp)
- Rwitajit Majumdar (majumdar.rwitajit.4a@kyoto-u.ac.jp)
- Weiqin Chen (weiqin.chen@oslomet.no)
- Hiroaki Ogata (hiroaki.ogata@gmail.com)
PC Members
- Anna Huang
- Atsushi Shimada
- Hsin Tse Lu
- Jayakrishnan Warriem
- Jingyun Wang
- Kiran L.N. Eranki
- Kiriko Komura
- Mei-Rong Alice Chen
- Mohammad Nehal Hasnine
- Ramkumar Rajendran
- Sachio Hirokawa
- Shitanshu Mishra
- Tore Hoel
- Yuichi Ono
Contact
All questions about submissions should be emailed to Brendan Flanagan and/or Rwitajit Majumdar (see contact details above).