Guessing and the Error Structure of Learning Models

Abstract

This paper is broadly concerned with problems associated with the use of test score data to infer the relative strength of inputs to the production of learning. It should be of interest to those employing a typical strategy of economic education research: pretesting students, applying some special educational treatment to a subset of students, and posttesting the students. By this strategy the researcher enquires whether the treated group learned more or learned more efficiently. This paper specifically addresses several concerns raised by Thomas Johnson by laying out a set of structural equations and thereby modelling the probability of answering a test item correctly and by dealing in a novel way with the hypothesis that some test questions are more difficult than others.