- Simon Knight, University of Technology Sydney (Australia)
- Alyssa F. Wise, Simon Fraser University (Canada)
- Britte Haugan Cheng, SRI International (USA)
- Bodong Chen, University of Minnesota—Twin Cities (USA)
AIMS & SCOPE
This special section focuses on the analysis of temporal features of learning. Specifically it will present a collection of focal papers bringing together key perspectives on conceptual, methodological, and implementation based concerns in dealing with sequence, trajectory, duration, and other temporal constructs for the analysis of learning data. The special section is intended to bring the analytics and learning scholarly communities together to support researchers in interrogating and incorporating new approaches to the analysis of multiple data-streams.
Temporal considerations are important in understanding learning, yet understudied in educational research, resulting in a gap in resources available for research and educators wishing to employ temporally-aware approaches. This becomes a missed opportunity as formal and informal learning environments are replete with fine grained temporal data sources such as click streams, chat logs, document edit histories, and motion tracking (e.g. eye-tracking, Microsoft Kinect). This call for submissions is the culmination of a series of five international workshops on that topic, and aims to further dialogues in this area.
TOPICS OF INTEREST
Papers in this special section will make contributions to our scholarly understanding of the analysis of temporal features of learning data with respect to theory, design methodology, technology implementation, or evidence of impact and translation for practitioners. Contributions may take, but are not limited to, one of the following forms:
- Technical Contributions, e.g., papers that describe particular methods, techniques, or tools for temporal analysis; present principles and methodologies for combining complementary analytical approaches; or analyse specific technical challenges or opportunities for temporal analytics.
- Conceptual Contributions and Reviews, e.g., papers that develop theoretical positions related to temporality and learning data; posit particular conceptualisations of aspects of the temporal nature of learning data; or review the extant literature on an aspect of the temporal analysis of learning data.
- Design and Application Contributions, e.g., papers that: present visualisations of temporal analytics (for different educational contexts and user groups); describe the use of temporal approaches to address particular challenges in research or practice; or address questions of validity in the use of temporal analyses in assessment.
- Implementation and Adoption Contributions (e.g., papers that report on the use of temporal analytics in practice; present use cases of temporal analytics; or analyse practitioner and organisational adoption issues for temporal analytics.
- Submission: 10 January 2017 EXTENDED: 12 February 2017
- Authors' notification: 10 April 2017
- Revised submission: 10 May 2017
- Final feedback: 10 June 2017
- Final version submission: 10 July 2017
- Special Section publication (expected): Fall 2017
Authors should submit following the journal’s Information For Authors, selecting the special section “It's About Time: Temporal Analysis of Learning Data" when uploading the paper.