|Title||The Use of Decision Trees for Adaptive Item Selection and Score Estimation|
|Publication Type||Conference Paper|
|Year of Publication||2011|
|Authors||Riley, BB, Funk, R, Dennis, ML, Lennox, RD, Finkelman, M|
|Conference Name||Annual Conference of the International Association for Computerized Adaptive Testing|
|Keywords||adaptive item selection, CAT, decision tree|
Conducted post-hoc simulations comparing the relative efficiency, and precision of decision trees (using CHAID and CART) vs. IRT-based CAT.
Decision tree methods were more efficient than CAT
CAT selects items based on two criteria: Item location relative to current estimate of theta, Item discrimination
Decision Trees select items that best discriminate between groups defined by the total score.
CAT is optimal only when trait level is well estimated.