@inbook {692501, title = {Making Static Lessons Adaptive through Crowdsourcing \& Machine Learning}, booktitle = { Design Recommendations for Intelligent Tutoring Systems: Domain Modeling}, volume = {4}, year = {2016}, abstract = {Text\ components\ of\ digital\ lessons\ and\ problems\ are\ often\ static:\ they\ are\ written\ once\ and\ too\ often\ not\ improved\ over\ time.\ This\ is\ true\ for\ both\ large\ text\ components\ like\ webpages\ and\ documents\ as\ well\ as\ the\ small\ components\ that\ form\ the\ building\ blocks\ of\ courses:\ explanations,\ hints,\ examples,\ discussion\ questions/answers,\ emails,\ study\ tips,\ motivational\ messages.\ This\ represents\ a\ missed\ opportunity,\ since\ it\ should\ be\ technologically\ straightforward\ to\ enhance\ learning\ by\ improving\ text,\ as\ instructors\ get\ new\ ideas\ and\ data\ is\ collected\ about\ what helps\ learning.\ We\ describe\ how\ instructors\ can\ use\ recent\ work\ (Williams,\ Kim,\ Rafferty,\ Maldonado,\ Gajos,\ Lasecki,\ \&\ Heffernan,\ 2016a)\ to\ make\ text\ components\ into\ adaptive\  resources\  that\  semi-automatically\  improve\  over\  time,\  by\  combining\  crowdsourcing methods\ from\ human\ computer\ interaction\ (HCI)\ with\ algorithms\ from\ statistical\ machine\ learning\ that\ use\ data for\ optimization.\ }, author = {Williams, Joseph Jay and Juho Kim and Elena Glassman and Anna Rafferty and Walter Lasecki} }