Semester of Graduation

Fall 2025

Degree

Master of Science (MS)

Department

Mathematics

Document Type

Thesis

Abstract

Data science has emerged as a cornerstone of innovation, shaping an ever-expanding range

of professional careers. As technology advances and the volume of data expands expo-

nentially, the ability to extract meaningful insights from data has become indispensable

across industries. Far from representing a single career path, data science enables profes-

sionals in nearly every domain to make informed decisions, optimize systems, and drive

innovation. Yet, many high school students and incoming college freshmen have limited

exposure to data science fundamentals or the career opportunities they unlock. This is

the gap that Computational Data Analysis, a high school-level curriculum I developed,

seeks to address.

This curriculum originated during the 2022–2023 academic year, when I was awarded

a Public Service Assistantship through the Department of Mathematics at Louisiana

State University in partnership with the Gordon A. Cain Center. As part of this role, I

taught LSU STEM Pathway courses at Liberty High School in Baton Rouge, including

Data Manipulation and Analysis, a course originally designed by Mr. Alegre for the

LSU STEM Pathways program. Following his departure in 2023–2024, I redesigned and

expanded the curriculum to better prepare students for both professional and academic

pathways in data science, particularly LSU’s newly launched undergraduate data science

major.

Computational Data Analysis introduces students to core principles in data analysis,

computing, and statistical thinking, while incorporating industry-standard tools such as

R. The course culminates in the Certified Internet Web Professional (CIW) Data Analyst

certification exam, a nationally recognized credential that enhances students’ credibility in

both academic and professional contexts. Based on classroom experience, the curriculum

demonstrates strong potential for high certification pass rates and meaningful student

engagement.

Beyond the previously discussed certification benefits, the course also functions as a

bridge to collegiate-level degree paths, aligning with a nation-wide educational shifts to-

ward earlier specialization in data science. Whereas students once pursued general STEM

degrees before entering data-focused fields, new undergraduate majors now provide direct

pathways into the discipline. This curriculum serves as a practical precursor to those pro-

grams, which give students earlier exposure to the analytical and technical competencies

essential for success.

In conclusion, with Computational Data Analysis, I have sought to contribute to math-

ematics and statistics education by designing a curriculum that helps prepare high school

students to thrive in a data-driven world and to pursue further study in quantitative

disciplines. The long-term vision is to refine and distribute this curriculum through a

digital platform, making it accessible to high schools across Louisiana and, eventually the United States.

Date

11-5-2025

Committee Chair

Dr. Frank Neubrander

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