[on behalf of Christopher Brooks]
A reminder of the upcoming optional deadline of May 1st to have abstracts
reviewed....
Chris
CFP: Special Section on Learning Analytics Tools and Datasets, Journal of
Learning Analytics
GUEST EDITORS
• Christopher Brooks, University of Michigan (USA)
• Tim McKay, University of Michigan (USA)
AIMS & SCOPE
This special section will include articles on tools and datasets which are
expanding the horizons of learning analytic researchers and practitioners.
We focus on examples which are newly available for research, novel in
application, or substantially expanded in scale. We seek papers describing
applications of learning analytics tools to new areas, rigorous
measurements of their impact on learners, and challenges faced in design
and implementation. We are also interested in papers describing unique
datasets, the technical, ethical and logistical barriers to their use, and
the impact which they have had on learning analytics. While we aim to cast
the net widely, we expect that all tools and datasets described will sit
solidly at the intersection of teaching and learning, involving significant
analytic or computational aspects.
TOPICS OF INTEREST
Papers in this special section will make contributions to our scholarly
understanding of learning analytics tools and the datasets which drive
them. Contributions may take, but are not limited to, research papers
(6,000-10,000 words) one of the following forms:
Conceptual Contributions: papers that develop theoretical positions on what
kinds of tools and datasets are needed to understand and optimize learning
and the environments in which it occurs.
Reviews: papers that review the existing literature on classes of tools,
the data which support them, and their impact on learners.
Design and Application Contributions: papers which present an overview of
the research, development, and delivery of learning analytics tools at
scale, including the ways in which impact measures were obtained and
included in the design process.
Implementation and Adoption Contributions: papers which report on the use
of learning analytics tools by practitioners, analyze the challenges to
adoption and impact, and describe organizational structures which support
the use of learning analytics at scale.
TIMELINE
Optional (but highly encouraged) abstract pre-submission (max 500 words):
May 1, 2018
Deadline for submissions: July 15, 2018
Anticipated publication date: Spring, 2019
SUBMISSION PROCEDURE
Prospective authors are welcomed to reach out to the special issue editors
in advance in order to ascertain fit for the special section. The editors
will reply to prospective authors with feedback on ideas within two weeks.
Final submissions will take place through JLA’s online submission system at
http://learning-analytics.info.
When submitting a paper, select the section “Special Issue on Learning
Analytics Tools and Datasets”. All submissions should follow JLA’s standard
manuscript guidelines and will undergo rigorous peer review. For any
additional questions, please contact the special issue editors at
jla-tools@xxxxxxxxx.
ABOUT THE JOURNAL
The Journal of Learning Analytics is peer-reviewed, open-access, and is the
official publication of the Society for Learning Analytics Research (SoLAR).
--
Christopher Brooks
Research Assistant Professor, School of Information
Director of Learning Analytics & Research, Office of Academic Innovation
E-Mail: brooksch@xxxxxxxxx
Web: http://www.si.umich.edu/people/christopher-brooks
School of Information
University of Michigan
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