TY - GEN
T1 - Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research
AU - Ritter, Steven
AU - Heffernan, Neil
AU - Williams, Joseph Jay
AU - Lomas, Derek
AU - Motz, Ben
AU - Basu Mallick, Debshila
AU - Bicknell, Klinton
AU - McNamara, Danielle
AU - Kizilcec, Rene F.
AU - Roschelle, Jeremy
AU - Baraniuk, Richard
AU - Baker, Ryan
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - Learning engineering adds tools and processes to learning platforms to support improvement research. One kind of tool is A/B testing, which is common in large software companies and also represented academically at conferences like the Annual Conference on Digital Experimentation (CODE). A number of A/B testing systems focused on educational applications have arisen recently, including UpGrade and E-TRIALS. A/B testing can be part of the puzzle of how to improve educational platforms, and yet challenging issues in education go beyond the generic paradigm. For example, the importance of teachers and instructors to learning means that students are not only connecting with software as individuals, but also as part of a shared classroom experience. Further, learning in topics like mathematics can be highly dependent on prior learning, and thus A or B may not be better overall, but only in interaction with prior knowledge. In response, a set of learning platforms is opening their systems to improvement research by instructors and/or third-party researchers, with specific supports necessary for education-specific research designs. This workshop will explore how A/B testing in educational contexts is different, how learning platforms are opening up new possibilities, and how these empirical approaches can be used to drive powerful gains in student learning. It will also discuss forthcoming opportunities for funding to conduct platform-enabled learning research.
AB - Learning engineering adds tools and processes to learning platforms to support improvement research. One kind of tool is A/B testing, which is common in large software companies and also represented academically at conferences like the Annual Conference on Digital Experimentation (CODE). A number of A/B testing systems focused on educational applications have arisen recently, including UpGrade and E-TRIALS. A/B testing can be part of the puzzle of how to improve educational platforms, and yet challenging issues in education go beyond the generic paradigm. For example, the importance of teachers and instructors to learning means that students are not only connecting with software as individuals, but also as part of a shared classroom experience. Further, learning in topics like mathematics can be highly dependent on prior learning, and thus A or B may not be better overall, but only in interaction with prior knowledge. In response, a set of learning platforms is opening their systems to improvement research by instructors and/or third-party researchers, with specific supports necessary for education-specific research designs. This workshop will explore how A/B testing in educational contexts is different, how learning platforms are opening up new possibilities, and how these empirical approaches can be used to drive powerful gains in student learning. It will also discuss forthcoming opportunities for funding to conduct platform-enabled learning research.
KW - A/B testing
KW - educational software
UR - http://www.scopus.com/inward/record.url?scp=85132176181&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132176181&partnerID=8YFLogxK
U2 - 10.1145/3491140.3528288
DO - 10.1145/3491140.3528288
M3 - Conference contribution
AN - SCOPUS:85132176181
T3 - L@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale
SP - 252
EP - 254
BT - L@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale
PB - Association for Computing Machinery, Inc
T2 - 9th Annual ACM Conference on Learning at Scale, L@S 2022
Y2 - 1 June 2022 through 3 June 2022
ER -