Premium
Using Restricted Latent Class Models to Map the Skill Structure of Achievement Items
Author(s) -
Haertel Edward H.
Publication year - 1989
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1989.tb00336.x
Subject(s) - reading comprehension , class (philosophy) , reading (process) , set (abstract data type) , test (biology) , latent class model , comprehension , mathematics education , psychology , achievement test , sample (material) , range (aeronautics) , scale (ratio) , item response theory , binary number , cognitive psychology , natural language processing , computer science , artificial intelligence , statistics , mathematics , psychometrics , developmental psychology , linguistics , standardized test , arithmetic , philosophy , materials science , chemistry , composite material , biology , paleontology , chromatography , quantum mechanics , programming language , physics
This paper presents a new method for using certain restricted latent class models, referred to as binary skills models, to determine the skills required by a set o f test items. The method is applied to reading achievement data from a nationally representative sample o f fourth‐grade students and offers useful perspectives on test structure and examinee ability, distinct from those provided by other methods o f analysis. Models fitted to small, overlapping sets o f items are integrated into a common skill map, and the nature o f each skill is then inferred from the characteristics o f the items for which it is required. The reading comprehension items examined conform closely to a unidimensional scale with six discrete skill levels that range from an inability to comprehend or match isolated words in a reading passage to the abilities required to integrate passage content with general knowledge and to recognize the main ideas o f the most difficult passages on the test.