The Relationship Between Using A Computer-Assisted Instruction Program and End-Of-Course Performance Of Algebra 1 Students

Date

2020-08

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Abstract

Background: Each year in a large urban district in southeast Texas, students enter middle and high school classrooms with achievement gaps in mathematics. Students have various levels of prerequisite knowledge, and individual differentiation is necessary for success. The district implemented an initiative where every student enrolled in a high school course was assigned a laptop to address these disparities. A computer-assisted instruction program was also purchased to provide differentiated instruction to under-achieving students within mathematics classrooms. Since Algebra 1 is the prerequisite for all high school mathematics courses, the program is currently used in algebra classes. Purpose: The purpose of this study was to examine any relationship between the use of a computer-assisted program, Imagine Math, by Algebra 1 students, and their performance on the State of Texas Assessment of Academic Readiness (STAAR) end-of-course assessment. In this study, we investigated whether using a computer-assisted program helped with mastery of mathematical concepts and consequently enhanced performance on the State of Texas Assessment of Academic Readiness (STAAR). The proposed study addressed the following research question: What is the relationship between the number of successfully completed computer-assisted Algebra 1 mathematics instruction lessons and performance on the State of Texas Assessment of Academic Readiness? Methods: This correlation study examined the relationship between the number of lessons passed in Imagine Math and students’ performance on the STAAR end-of-course assessment. Participants for this study included approximately 4,800 students enrolled in Algebra 1 for the first time in the 2018-2019 school year. All participants were part of a large urban school district in southeast Texas. Correlation and linear regression were used to examine the relationship between the number of lessons completed in a computer-assisted program and students’ performance on the STAAR exam. Results: A hierarchical and quantile regression was used to analyze the data. The statistical analysis showed there was a positive linear relationship between the number of lessons passed in Imagine Math and students’ scale scores on the STAAR Algebra 1 end-of-course assessment. Results from the hierarchical regression showed the full model of gender, grade level, ethnicity, and total Imagine Math lessons passed to predict students’ scale scores on the STAAR Algebra 1 end-of-course assessment was statistically significant, R squared = .295, F(4, 12782) = 1339.220, p < .001, adjusted R squared = .295. Results from the quantile regression showed a moderate positive relationship between the variables, with a Pearson’s r-value of .39. Quantile-25 and Quantile-50 accounted for more than 16% of the explained variability in scale scores. Conclusion: Although there is no definitive proof that the relationship is strictly due to the passing of lessons in the program, Imagine Math could be one instructional tool to assist students in learning and mastering concepts in Algebra 1.

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Keywords

computer-assisted instruction, differentiation, Imagine Math, Algebra 1, algebra instruction, secondary mathematics, distance learning

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