Many researchers who study the relations benveen school resources and student achievement haveworkedfrom a cautsal model, wvhich typically is implicit. In this model, some resouirce orset of resourcesis the causal variable and student achievement is the ozutcome. In afewv recent, more nu(anced versions,resource effects depend on intervening influences on their use. We argue for a model in wvhich the keycautsal agents are situated in instruction; achievement is their outtcome. Conventional resources canenable or constrain the causal agents in instnrction, thus moderating their impact on student achieve-ment. Becautse these causal agents interact in wvays thzat are unlikely to be sorted out by multivatiateanalysis of natutralistic data, experimental trials of distinctive instnrctional systems are more likely tooffer solid evidence on instnrctional effects.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education