An Empirical Study About Calibration of Adaptive Hints in Web-Based Adaptive Testing Environments

In this paper we present a proposal for introducing hint adaptive selection in an adaptive web-based testing environment. To this end, a discussion of some aspects concerning the adaptive selection mechanism for hints is presented, which results in the statement of two axioms that such hints must fulfil. Then, an empirical study with real students is presented, whose goal is to evaluate a tentative bank of items with their associated hints to determine the usefulness of such hints for different knowledge levels and to calibrate both test items and hints.