Data Science Foundations Course Pilot

The Need for Data Science

Contemporary mathematics education has not been keeping up with the rapid emergence of data and computing. Looking at the world’s job market, many fields deal with big data sets. According to research, a vast majority of faster-growing job categories include data-centered, well-paid, exciting and challenging jobs. To help students thrive in data-related fields of education or careers, students should be exposed not only to Statistics and Probability but also be well-equipped with a basic understanding of data science. It is evident that students who develop data fluency are better prepared for 21st century careers.

What is Data Science?

Data science is a blend of quantitative reasoning, statistics and computer science to gain meaningful insights from data. The difference between data science and statistics is that where statistics focuses on explaining the data, data science focuses on using data to make predictions and decisions. Students will reason with and think critically about data in all forms. They will develop their understanding of data analysis, sampling, correlation/causation, bias and uncertainty, probability, modeling with data, making and evaluating data-based arguments, the power of data in society and more. 

Data Science

Data Science venn diagram

Description of Data Science Foundations Course

The Data Science Foundations course teaches students to reason with and think critically about data in all forms. Ohio’s Learning Standards for Mathematics relevant to data science are taught along with the data demands of good citizenship in the 21st century. Although this course still is being developed, it may include things such as describing big data; usability and usefulness of data; structured vs unstructured data; data extraction techniques; data storage; privacy issues; and data mining.


The Ohio Department of Education and Workforce is partnering with the Ohio Department of Higher Education and Ohio Math Initiative to create courses that will satisfy the credit requirement for Algebra 2. Several groups were formed: (1) An advisory council, made up of representatives from a variety of education organizations; (2) Math Pathways Architects, made up of higher education and high school math faculty; and (3) course-specific workgroups. 
The advisory council is focusing on equity, communication and supports surrounding systems and structures. The Math Pathways Architects group is focusing on aligning the math pathways between high school and college and career. These groups proposed a Data Science Foundations course as an Algebra 2-equivalent course.

The following districts and Educational Service Centers (ESCs) are participating in the pilot during the 2023-2024 school year:

K-12 School Districts

  • Alternative Education Academy (OHDELA)
  • Barberton City School District
  • Bedford City Schools
  • Brecksville-Broadview Heights City
  • Cincinnati College Preparatory Academy
  • Columbus City
  • Cory-Rawson Local
  • Cuyahoga Falls City School District
  • EHOVE Career Center
  • Fairborn City Schools
  • Fostoria City Schools  
  • Fremont City
  • Gahanna-Jefferson Public Schools
  • Goshen Local School District
  • Green Local 
  • Greene County Career Center
  • Harding High school
  • Horizon Science Academy Columbus
  • Hilliard City Schools 
  • James A. Garfield Local Schools
  • Kettering City Schools
  • Loudonville-Perrysville Exempted Village Schools
  • Marion City Schools 
  • Medina City School District
  • Milford Exempted Village
  • Mt. Healthy City Schools
  • New Richmond Exempted Village Schools
  • Noble Local STEM-Designated School District
  • Nordonia Hills City Schools 
  • North Central Local
  • North College Hill City Schools
  • North Union Local Schools 
  • Northwest Local School District 
  • Oak Hills Local School District
  • Ohio Connections Academy
  • Olentangy Local School District 
  • Paint Valley Local Schools
  • Perry Local Schools
  • Perrysburg Exempted Village Schools
  • Piqua City Schools
  • Riverside Local School District
  • Ross Local Schools
  • Sandusky City Schools 
  • Scioto Valley Local Schools 
  • Shadyside Local School District
  • South-Western City School District
  • Springfield City Schools
  • St. Mary’s City Schools
  • Talawanda City Schools 
  • Teays Valley Local Schools 
  • Toledo Public Schools 
  • Upper Valley JVS
  • Vandalia-Butler City Schools
  • Wadsworth City Schools 
  • Wayne Local Schools
  • West Geauga Local School District
  • Wilmington City Schools 
  • Xenia Community Schools

Participating ESCs

  • Butler County ESC
  • Clark County ESC 
  • Clermont County ESC
  • East Central Ohio ESC 
  • ESC of Central Ohio
  • ESC of Eastern Ohio
  • Hamilton County ESC
  • Hancock County ESC
  • Lake County 
  • Lake Erie West ESC
  • Medina County ESC
  • Mercer County ESC 
  • Miami County ESC
  • Midwest Regional ESC
  • Montgomery County ESC
  • North Central Ohio ESC
  • Northwest Ohio ESC
  • Ohio Valley ESC
  • Pickaway County ESC
  • South Central ESC
  • Stark County ESC
  • Summit County ESC
  • Tri-County ESC
  • Trumbull County ESC

Target Students

The Data Science Foundations course is beneficial for students who needs a third or fourth credit in mathematics and is not intending to pursue a career that requires calculus. It is appropriate for students with limited or no prior programming, statistics, and data analytics knowledge. The Data Science Foundations course is ideal for absolute beginners, who want to acquire a basic working knowledge of data science. It is designed to be a hands-on course that promotes reasoning and the standards for mathematical practice.

This course would be especially appropriate for a student with the following characteristics:

  • Anticipating a career in behavioral sciences;
  • Anticipating a career in the emerging fields of Computer Science, Computational Data Analysis or/and Statistics;
  • Is interested in applied fields of study which use mathematics; 
  • Enjoys exploring engaging, real-world issues involving data;
  • Desires to become a better-informed citizen;
  • Pursuing a pathway that does not require calculus; and/or
  • Pursuing computer technology or STEM fields in a postsecondary institution.
Students who succeed in this course may take an Algebra 2 (or other equivalent) course, College Credit Plus (CCP) course or Advanced Placement (AP) math course for their fourth unit of mathematics credit. Although students who take this course have flexibility in which follow-up math courses they take, this course pairs especially well with AP Statistics and Probability, AP Computer Science, a CCP Introductory Statistics course, a CCP Quantitative Reasoning course, or a CCP Data Science course. Although, there are many careers in data science that do not require Calculus, if students become interested in an advanced degree in data science, they may want to consider pursuing the Calculus pathway and take an Algebra 2 course or CCP College Algebra course.

Participating in the Pilot

The Ohio Department of Education and Workforce, in partnership with the Ohio Educational Service Center Association (OESCA), is providing opportunities to expand the High School Mathematics Pathways Initiative to support districts for the 2024-2025 school year.

To ensure the fidelity and implementation of the course, the completed application form requires the following information: 

  • The signature of the local school board president or district treasurer;
  • The signature of the local superintendent/building administrator; and
  • The signature of the professional staff bargaining unit leader. 

To express interest in participating in the training and implementation, districts and schools submit their application starting Wednesday, Nov. 29-Friday, Dec. 22, 2023.

To help support a more successful implementation, professional development will be required for all teachers participating in the course. Teachers will be expected to attend a summer workshop and ongoing professional development throughout the school year.

For questions, email Yelena Palayeva at


  • Data Science Foundations Application [Read-only PDF]
  • Application window opens Wednesday, Nov. 29. 
  • Application window closes Friday, Dec. 22 
  • Applications must be completed online. A read-only PDF version of each application is available for planning purposes only.
  • A confirmation email will be sent via email upon submission of the application.
Note: Submitting interest does not guarantee selection into the pilot.


Last Modified: 6/18/2024 4:36:22 PM