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Model Selection for Cogitative Diagnostic Analysis of the Reading Comprehension Test.

ABSTRACT: Reading subskills are generally regarded as continuous variables, while most models used in the previous reading diagnoses have the hypothesis that the latent variables are dichotomous. Considering that the multidimensional item response theory (MIRT) model has continuous latent variables and can be used for diagnostic purposes, this study compared the performances of MIRT with two representatives of traditionally widely used models in reading diagnoses [reduced reparametrized unified model (R-RUM) and generalized deterministic, noisy, and gate (G-DINA)]. The comparison was carried out with both empirical and simulated data. First, model-data fit indices were used to evaluate whether MIRT was more appropriate than R-RUM and G-DINA with real data. Then, with the simulated data, relations between the estimated scores from MIRT, R-RUM, and G-DINA and the true scores were compared to examine whether the true abilities were well-represented, correct classification rates under different research conditions for MIRT, R-RUM, and G-DINA were calculated to examine the person parameter recovery, and the frequency distributions of subskill mastery probability were also compared to show the deviation of the estimated subskill mastery probabilities from the true values in the general value distribution. The MIRT obtained better model-data fit, gained estimated scores being a more reasonable representation for the true abilities, had an advantage on correct classification rates, and showed less deviation from the true values in frequency distributions of subskill mastery probabilities, which means it can produce more accurate diagnostic information about the reading abilities of the test-takers. Considering that more accurate diagnostic information has greater guiding value for the remedial teaching and learning, and in reading diagnoses, the score interpretation will be more reasonable with the MIRT model, this study recommended MIRT as a new methodology for future reading diagnostic analyses.

SUBMITTER: Liu H

PROVIDER: S-EPMC8422035 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundReading is important for children's success in school and beyond, yet many adolescents fail to reach expected levels of proficiency. This highlights the need to better understand the factors that influence reading effectiveness over time, including genes and environment. Greater expression of genetic influence on first- and second-grade reading fluency has been observed in higher quality classroom reading environments. To what degree this early environment continues to influence genetic and other environmental influences on later reading is unknown and was tested in this study.MethodsThe quality of the early classroom reading environment was approximated by gains in oral reading fluency (ORF) across the school year among first- or second-grade classmates of 546 MZ and 1,016 DZ twin children (mean age = 7.13 years; SD = 0.45) who had reading comprehension scores from a state-wide mandatory test in school year 2013-2014 when most twin pairs were in seventh to tenth grade (mean age = 14.41; SD = 1.13) in a variable called Class ORF Gain. Biometrical models were fit to the data to assess whether Class ORF Gain moderated the genetic, shared environmental and/or nonshared environmental variance associated with adolescent reading comprehension.ResultsClass ORF Gain moderated shared environmental influences on reading comprehension 6-9 years later. When early classroom reading gains were poor, variability in reading comprehension in adolescence was high and was associated largely with shared environmental influences. When early classroom reading gains were good, overall and shared environmentally influenced variability in adolescent reading comprehension was lower so that genetic influences were most relevant in explaining that variability.ConclusionsOur findings suggested that classroom reading environment experienced when children were learning to read had a lasting influence on the factors underlying variability in later reading effectiveness.

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Model Selection for Cogitative Diagnostic Analysis of the Reading Comprehension Test.

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