Examining the inseparability of content knowledge from LSP reading ability: an approach combining bifactor-multidimensional item response theory and structural equation modeling
Yuyang Cai, Antony John Kunnan · Language Assessment Quarterly · 2018
This study examined the separability of domain-general and domain-specific content knowledge from Language for Specific Purposes (LSP) reading ability. A pool of 1,491 nursing students in China participated by responding to a nursing English test and a nursing knowledge test. Primary data analysis involved four steps: (a) conducting a bifactor-multidimensional item response theory model (bifactor-MIRT) analysis to establish measurement validity for the assumed domain-general factor and domain-specific factors underlying each test and to compute bifactor-MIRT direct scores; (b) transforming the bifactor-MIRT scores into composite scores; (c) conducting a confirmatory factor analysis with the composite scores to reconstruct the orginal bifactor-MIRT models, and (d) conducting a structural equation modeling analysis to explore the relationship between nursing knowledge factors (domain-general and domain-specific) and the nursing English reading factors (domain-general and domain-specific). The results showed that the domain-specific passage factors were significantly correlated with their corresponding domain-specific nursing knowledge factors and that domain-general nursing knowledge significantly predicted the variance of the domain-general reading factor. Overall, we concluded that content knowledge is inseparable from LSP reading ability. The implications for understanding LSP ability and for LSP reading test scoring are discussed.