Special Section on learning analytics and learning theory - Call for Papers
Alyssa Friend Wise
Simon Fraser University
David Williamson Shaffer
University of Wisconsin-Madison
This special issue focuses on the intersection of learning theory and analytics. Specifically it will present a collection of papers demonstrating the ways in which learning theories are being used to craft analytics, how analytics have helped us advance learning theories, and the initial development of theories of learning with analytics.
Topics include, but are not limited to:
- How understanding of specific learning phenomenon (processes, practices) has helped to shape particular approaches to learning analytics
- How learning analytics have helped to refine / improve our understanding of particular learning phenomenon (processes, practices)
- Work contributing to our understanding of how people engage with learning analytics as part of their learning processes or practices
Importantly, papers must include both conceptual and empirical elements, addressing in some way the relationship between theories of learning and information gleaned from analytical techniques. Papers which are purely empirical (e.g. reporting that certain analytics predict success without a theoretical explanation about why) or purely theoretical (an idea for tracking certain data based on a learning theory is described but not actually implemented) are not appropriate for this special issue.
- A method for analyzing the synchronization of multiple participants' activities as a measure a joint attention, one indicator a productive collaborative process
- An analysis of patterns of (re)accessing online resources that informs the way we think about effective studying in an online context
- A study that tests a model for supporting teachers in working with analytics as part of their reflective practice / class preparation process
Deadline for submissions: November 30, 2014
Anticipated publication date: June, 2015
Submissions will take place through JLA’s online submission system at http://learning-analytics.info
All submissions should follow JLA’s standard manuscript guidelines and will undergo peer review.
For any additional questions, please contact the guest editors directly.