Time: 04:00 PM
April 13, 2021 – 4PM to 7 PM PST (according to LAK pre-conference schedule)
Learning analytics (LA) researchers often fail to collect the necessary data to answer research questions due to a lack of understanding of what types of data they need. This workshop aims to advance understanding of the necessities of iterative processes in data collection and analysis to address the issue. The workshop includes panel talks by the organizers, who have experience in data collection tool design, and discussion to sketch out designs of potential Evidence-Based Iterative (EBI) processes. which can help LA community update the design of the data collection system in consideration of research contexts and findings from previous iterations.
Heeryung Choi, University of Michigan
Christopher Brooks, University of Michigan
Caitlin Hayward, University of Michigan
Neil Heffernan, Worcester Polytechnic Institute
Dragan Gasevic, Monash University
Kirsty Kitto, University of Technology Sydney
Abelardo Pardo, University of South Australia
Phil Winne, Simon Fraser University
Register for this event
Your video, audio and the meeting chat transcript may be recorded at this event. Please advise the facilitator if you do not wish to be recorded.