Journal article Open Access

Challenges for the Future of Educational Data Mining: The Baker Learning Analytics Prizes

Baker, Ryan S.

Learning analytics and educational data mining have come a long way in a short time. In this article, a lightlyedited transcript of a keynote talk at the Learning Analytics and Knowledge Conference in 2019, I present a vision for some directions I believe the field should go: towards greater interpretability, generalizability, transferability, applicability, and with clearer evidence for effectiveness. I pose these potential directions as a set of six contests, with concrete criteria for what would represent successful progress in each of these areas: the Baker Learning Analytics Prizes (BLAP). Solving these challenges will bring the field closer to achieving its full potential of using data to benefit learners and transform education for the better.

Files (217.2 kB)
Name Size
-9121895
md5:6bfec4f6da7511886df1aa6777213f37
217.2 kB Download
0
0
views
downloads
All versions This version
Views 00
Downloads 00
Data volume 0 Bytes0 Bytes
Unique views 00
Unique downloads 00

Share

Cite as