Anticipated Date of Graduation

Summer 2022

Document Type

Thesis

Degree Name

Master of Science in Mathematical Sciences

Department

Mathematical Sciences

First Advisor

Douglas Darbro

Abstract

The intent of this study was to explore the extent to which the academic performance in mathematics differs between high school students with virtual learning and students with traditional classroom face-to-face learning. The study focused on Tennessee public high schools, and this thesis was a quantitative study. The data were collected from credible Internet sources such as the Tennessee Department of Education website, where the data were made available for the public to use and analyze for research purposes.

A total of 143 high schools located in 58 counties participated in the study. The selection of the sample was done by stratification, and the participating schools were selected from 20 economically disadvantaged counties and 38 economically non-disadvantaged counties. Ultimately, a total of 36 selected schools were located in economically disadvantaged counties and 107 schools were located in economically non-disadvantaged counties.

The two-way ANOVA followed by multi-regression analysis along with the software R were employed to carry out the statistical design and analyze the data. The designated statistical hypotheses were tested at 0.05 significance level. For the two-way ANOVA analysis, two types of instruction and two classifications of economic status were considered for the difference in math proficiency rates. For the multi-regression analysis, 8 independent variables including a covariate, were considered to identify the significant predictors for a valid prediction of the math proficiency rate of students with the virtual instruction method.

The sample size, sampling method, and reviewed literature supported the reliability and validity of the data results obtained from the study. The data showed a significant decline of 9.6028 ± 2.7839 percentage points in the academic performance in mathematics for students with virtual instruction. The data also resulted in a reliable predictive mathematical model with a ii coefficient of determination R2 Adj of 0.5518 and two significant predictors for the academic performance in mathematics of high school students with virtual instruction. The explicit predictive model was:

Rate of students achieving proficient academic performance in mathematics of high school students with virtual learning ≈ 5.7383 + 0.51279 × Rate of students achieving proficient academic performance in mathematics of high school students with face-to-face learning – 0.128 × Percentage of people of color constituent.

Included in

Mathematics Commons

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