Everyday learning becomes more and more important as learners, educators, knowledge workers, professionals etc. need to stay-up-to date for their daily learning and working activities. As technology evolves rapidly continuous everyday learning in fast changing environments will become a crucial part of the personal development.
The workshop will include a paper session, a demo and prototype slam as well as an interactive session. The workshop aims at:
- Providing a forum for presenting and discussing research on learning analytics for everyday learning.
- Creating an interactive experience that connects participants’ research, current tools or latest prototypes and models with real end users’ learning experiences and requirements regarding analytics for everyday learning.
- Creating an agenda for future everyday learning research and development.
We are looking forward to contributions that feed the debate about learning analytics in the context of everyday learning on many levels. Thus, we are looking for contributions out of science, technology and practice to discuss learning analytics for everyday learning from different perspectives.
Furthermore, participants are invited to submit innovative technologies that support learning analytics for everyday learning but also novel and advanced approaches based on artificial intelligence, augmented reality or ubiquitous computing technologies for learning. We are also highly appreciating papers on practices and different pedagogical approaches, types of learning settings, and application domains that can be used for everyday learning.
The main goal of our workshop is to illuminate everyday learning from different perspectives. Thus, the topics of interest include but are not limited to:
Theoretical discussion about everyday learning and related concepts
Conceptual discussion about learning analytics for everyday learning
Methodologies to identify, study, and analyze everyday learning in different contexts and to discuss the application areas for learning analytics
Empirical studies on analytics for everyday learning
Technologies and tools for analytics for everyday learning
Analytics for everyday learning in social context, knowledge, artefacts, processes and in contexts like higher education, work-place learning, learning organizations and networks
Challenges, requirements and solutions for analytics for everyday learning in various contexts
- Full papers: Description of novel theoretical, empirical or development work on learning analytics in TEL, including a substantial contribution to the field (up to 15 pages).
- Work in progress: Ongoing research and current approaches on investigating the field, with initial insights for the community (up to 7 pages).
- Demos: Prototypes, design studies and tools for the support of learning analytics in TEL, which can be demoed and discussed (up to 3 pages)
All contributions will be peer reviewed by at least two members of the programme committee evaluating their originality, significance, and rigour. The papers will be published in the CEUR workshop proceedings (ceur-ws.org). Submissions should use the Springer LNCS template (www.springer.com)
Please submit your paper via EasyChair: easychair.org