Examination of Factors Affecting Students’ Reading-Comprehension Achievement with Structural Equation Modeling
It is noted in the light of several studies associated with the reading-comprehension skills that fluent word reading, connectives knowledge and fluent text reading are closely related to the comprehension skill. Hence it seems possible to create a model over these concepts and their interrelationsh...
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Veröffentlicht in: | International journal of assessment tools in education 2018-01, Vol.5 (3), p.428-442 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | It is noted in the light of several studies
associated with the reading-comprehension skills that fluent word reading,
connectives knowledge and fluent text reading are closely related to the
comprehension skill. Hence it seems possible to create a model over these concepts
and their interrelationships. Within the scope of this research two different
models are proposed considering theoretical information. The
study group of the research was composed of 263 secondary school students at a
state school in Burdur province. Three different confirmatory factor analysis
(CFA) were performed to see whether factor structures were confirmed on the
sample by using the maximum estimate method of the AMOS 18 software. Analysis
of Covariance and Multivariate Analysis of Covariance were performed to
determine whether the demographic variables grade level and gender had a
significant effect on the scale scores. These analyzes were also performed in
the SPSS 18 program. It has been found that as the grade level of the students
increases, connective usage konowledge increases, the fluent silent word
reading, the fluent silent text reading, the reading comprehension and the
academic achievements increase as the grade level increases. This research
concluded that reading comprehension strongly and significantly predicted
academic achievement. But however, fluent silent text reading did not predict
reading comprehension significantly. According to the results of the research,
the model formed by the sub-dimensions of binding usage information shows
better fit. |
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ISSN: | 2148-7456 2148-7456 |
DOI: | 10.21449/ijate.404205 |