This study was designed to investigate the relationship between arithmetic and reading comprehension, as measured by the Grades 6 and 7 Florida Standards Assessment (FSA), and student success in algebra, as measured by the Florida Algebra I End-of-Course Assessment (EOCA). The intent of the study was to bridge the gap in the literature regarding student performance on the Grades 6 and 7 FSA English Language Arts and Mathematics and subsequent performance on the Algebra I EOCA. Furthermore, this study sought to identify specific skills related to arithmetic and reading comprehension that contribute to student performance in Algebra I. Sequential multiple regression was used to determine the relationship between the overall scale scores and curricular strand sub-scores for the Grades 6 and 7 FSA English Language Arts and Mathematics and the scale scores for the Algebra I EOCA, while controlling for student demographic variables. Additionally, multivariate analyses of variance were used to determine the differences between the Algebra EOCA performance levels in the sub-scores of each middle school assessment. Each of the final models for the scale scores and the sub-scores for all four FSAs were found to be statistically significant and meaningful predictors of student performance on the Algebra I EOCA in at least one regression model. Sub-scores from the FSA Mathematics in Grades 6 and 7 were the most commonly significant and meaningful predictors, particularly knowledge of the number system, ratios and proportions, and expressions and equations. Finally, it was found that there were statistically significant differences in the FSA sub-scores between student groups identified by their performance on the Algebra I EOCA. This study has numerous implications in the areas of data analysis, curriculum design and implementation, mathematics content area reading instruction, and the overall approach to mathematics education for Students with Disabilities, English Learners, and students with low socioeconomic status.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1287 |
Date | 01 January 2020 |
Creators | Serianni, Anthony |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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