Open AccessFACTORS AFFECTING DIFFICULTY IN THE GENERATING EXAMPLES ITEM TYPE
Author(s) -
Katz Irvin R.,
Lipps Audrey W.,
Trafton J. Gregory
Publication year - 2002
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.2002.tb01874.x
Subject(s) - generality , predictive power , set (abstract data type) , variance (accounting) , cognition , test (biology) , affect (linguistics) , selection (genetic algorithm) , item response theory , type (biology) , psychology , cognitive psychology , ask price , computerized adaptive testing , computer science , artificial intelligence , machine learning , psychometrics , developmental psychology , paleontology , philosophy , ecology , accounting , communication , epistemology , neuroscience , business , psychotherapist , biology , programming language , economy , economics
This paper investigates the predictive validity of various features of Generating Examples (GE) test items – algebra problems that pose mathematical constraints and ask examinees to provide example solutions meeting those constraints. Selection of item features was motivated by a cognitive model of how examinees solve GE items using informal solution strategies such as generate‐and‐test. Experiment 1 examined the extent to which examinee performance can be explained by features predicted to affect difficulty, and Experiments 2 and 3 investigated the generality and cognitive bases of the difficulty model. The factors studied accounted for approximately 55% of the variance among item difficulty levels, and this predictive power was maintained on a more heterogeneous set of items. Cognitive strategies underlying the difficulty factors were also examined.