It’s About Time: 4th International Workshop on Temporal Analyses of Learning Data
Learning occurs over time and interest in analyses that probe temporal aspects continues to grow as a powerful way to understand the processes through which learning occurs. The study of common and consequential sequences of events (such as learners accessing resources, interacting with other learners and engaging in self-regulatory activities) and how these associate with learning outcomes, as well as the ways in which knowledge and skills grow or evolve over time are both core areas of interest. However, the emerging area of temporal analysis presents both technical and theoretical challenges in appropriating suitable techniques and interpreting results in the context of learning. The learning analytics community offers a productive focal ground for exploring and furthering efforts to address these challenges as it is already positioned in the “middle space” where learning and analytic concerns meet. In addition, learning analytics datasets are replete with fine-grained temporal data: click streams; chat logs; document edit histories (e.g. wikis, etherpads); motion tracking (e.g. eye-tracking, Microsoft Kinect), and so on. This workshop, the fourth in a series on temporal analysis of learning data, provides a focal point for analytics researchers to consider the larger issues of and approaches to temporality in learning analytics. The focus is on the particular opportunities and challenges of temporal analysis for learning analytics and how learning analytics data, methods and approaches can inform the larger community working with temporal analyses of learning data.
For more details, see the the short workshop paper published in the LAK 2015 proceeding.
Discussion on the day included breakout groups organized around distinctive analytical approaches, with members from the different roles. This design aimed to facilitate an inclusive and effective discussion on the day, and onwards. Prior to the day some core themes and questions were identified for discussion in each analytical group. Question prompts for each analytical group included:
- What kinds of data is the explored analytic approach suitable for?
- What grain size of ‘time’ does it address?
- What dimensions of temporality does it deal with (i.e., duration, sequence, etc.)?
- What kinds of insights about learning does it provide? (i.e why does that aspect of temporality matter, does the tool foreground particularly important features, etc.?)
- What new learning/learning process constructs could emerge from the analytic approach?
- How could you apply the approach in your own work/research?
- (How) could an educator interact with information produced by the analytic approach/tool as part of their teaching, assessment or other practice?
- (How) could students interact with information produced by the analytic approach/tool as part of their learning process?
- What limitations, gaps or other issues are there with the approach? How could the approach be developed further?
March 16, 2015, 8:30am - 12:30pm; Location: MU 3204.
- 8:30-9:00 - Introduction to the Workshop: Temporal Analyses and Learning Analytics (led by organizers)
- 9:00-10:00 - Group Work Session 1 (Conceptual): Introduction to the Approach, Tools & Data Types it can work for (analytic & data presenters)
- 10:00-10:15 - Coffee Break
- 10:15-11:45 - Group Work Session 2 (Application): Hands-on putting data into the tools and/or critical discussion of its application to specific data sets (all group members)
- 11:45-12:30 - Group Share Out, General Discussion and Wrap-Up (whole workshop)
Participants and Analytical Groups
Those interested in participating were invited to submit short (1 page maximum) applications for one of the following roles briefly describing which role they would like to participate in at the workshop and what they would bring to the position (e.g., past experience working with temporal analyses, how this area relates to your research interests). Participation roles include the following:
- Conceptual presenters: those who submit short conceptual papers on temporality for discussion at the workshop
- Data presenters: those who provide a salient dataset for discussion of its temporal properties and potential analyses
- Analytic presenters: those who provide an analytic technique relevant to temporal analysis
- Commentators: those who commit to reading, and responding to, at least one of the above kinds of submission – note that we welcome commentators with all backgrounds and levels of experience
- Simon Knight, Open University
- Alyssa F. Wise, Simon Fraser University
- Bodong Chen, University of Minnesota
- Britte Haugan Cheng, SRI International