1989/12/01 by Edward H. Haertel · 3 citations
Decision Sciences · Mathematics · Psychology · Social Sciences · #Achievement test #Arithmetic #Artificial intelligence #Binary number #Class (philosophy) #Cognitive psychology #Comprehension #Computer science #Developmental psychology #Educational Assessment and Pedagogy #Item response theory #Latent class model #Linguistics #Mathematics #Mathematics education #Natural language processing #Psychology #Psychometric Methodologies and Testing #Psychometrics #Range (aeronautics) #Reading (process) #Reading comprehension #Sample (material) #Scale (ratio) #Set (abstract data type) #Standardized test #Statistics #Test (biology)
paper · doi:10.1111/j.1745-3984.1989.tb00336.x
crossref issued 1989/12/01 · crossref published 1989/12/01 · crossref published-print 1989/12/01 · openalex publication_date 1989/12/01 · crossref published-online 2005/09/12 · crossref created 2005/09/12 · crossref deposited 2025/01/04 · openalex created_date 2025/10/10 · crossref indexed 2026/07/29 · openalex updated_date 2026/07/30
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.