Call for Papers / Workshop Background
There is no simple path that will take us immediately from the contemporary amateurism of the college to the professional design of learning environments and learning experiences. The most important step is to find a place on campus for a team of individuals who are professionals in the design of learning environments — learning engineers, if you will. - Herbert Simon
The emerging discipline of Learning Engineering is focused on putting into place tools and processes that use the science of learning as a basis for improving educational outcomes [2]. An important part of Learning Engineering focuses on improving the effectiveness of educational software. In many software domains, A/B testing has become a prominent technique to achieve the software’s goals [3], but educational software tends to lag other fields in the use of A/B testing, particularly at scale. This workshop will explore ways in which A/B testing in educational contexts differs from other domains and proposals to overcome these challenges so that A/B testing can become a more useful tool in the learning engineer’s toolbox.
We invite papers (up to 4 pages in CHI Proceedings format) addressing issues with conducting A/B tests and random assignment experiments at scale, including those addressing:
managing unit of assignment issues
measurement, including both short and long-term outcomes
practical considerations related to experimenting in school settings, MOOCs, & other contexts
ethical and privacy issues
relating experimental results to learning-science principles
understanding use cases (core, supplemental, in-school, out-of-school, etc.)
accounting for aptitude-treatment interactions
A/B testing within adaptive software
adaptive experimentation
attrition and dropout
stopping criteria
user experience issues
educator involvement and public perceptions of experimentation
balancing practical improvements with generalizable science
We welcome participation from researchers and practitioners who have either practical or theoretical experience related to running A/B tests and/or randomized trials. This may include researchers with backgrounds in learning science, computer science, economics and/or statistics.
The submission deadline is June 11, 2021.
References
[1] Herbert A. Simon. 1967. The job of a college president. Educational Record, 48, 68-78.
[2] Melina R. Uncapher (2018): From the science of learning (and development) to learning engineering, Applied Developmental Science, https://doi.org/10.1080/10888691.2017.1421437
[3] Kohavi, R., Deng, A., Frasca, B., Walker, T., Xu, Y., & Pohlmann, N. (2013, August). Online controlled experiments at large scale. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1168-1176).