We are soliciting 2-8 page position papers that provide detailed discussion about practical issues in collecting and analyzing data for estimating cognitive load. Specifically, we are interested in position papers that accomplish one or more of the following:
- Describe how a few measures of cognitive load are collected and describe the likely advantages and disadvantages of the measurements, problems with their use and solutions that they provide in enhancing understanding: The paper should describe current standard data collection procedures for each measure including subject selection, IRB issues, training, practice, and data logging. The presenter should go beyond recounting standard protocol, describing the practical issues they have experienced with each measure. The focus is on the method.
- Demonstrate how they are collected: Those attending the meeting are invited to bring hardware and software to demonstrate the measures in question. This includes e.g. DRT and eye fixation hardware and software, as well as a driving simulator or driving video game to show how the data are collected.
- Describe how the data from those measures are reduced and analyzed: To some extent, this will involve summarizing existing practice codified in standards. However, we are looking for presenters to go beyond what is in those documents, describing practical problems of filtering and cleaning up the data, censoring, rules for eliminating outliers, methods of quantifying lost data, identifying potential confounding factors and situations that arise with the use of a measure can bias interpretations of results and software that can help produce results. This should not be viewed as an opportunity to present a paper describing results.
Position papers will be published in the conference Adjunct Proceedings. (Note that we are working on including the Adjunct Proceedings in the ACM DL.) Position papers will be presented at the conference in poster format.