Standardization and Transparency in Data Science Masters Degree Programs

An ADSA Working Group

Working Group Charter:

The rapid rise of AI related jobs in the government and private sectors requires a careful classification of the knowledge, skills, and abilities (KSA) that candidates need for filling such jobs and a description of suitable academic training. The ADSA community will collaborate with the NSA and other federal agencies to first develop a taxonomy of learning objectives and competencies commonly found in AI and data science educational efforts (e.g. degree programs). We will concurrently develop a mapping of these to the KSA required by prospective employers.

Desired Outcomes:

  • From the training side (Taxonomy):
    • A taxonomy of topics and student learning objectives (SLO) of programs in data science and AI at different levels – certificate, Bachelors, graduate certificates, Masters, and PhD.
  • From the employer side (KSA):
    • A mapping between knowledge and skills for different data science and AI job categories to the created taxonomy. Establish competency levels and mechanisms for evaluation in the described knowledge and skills underlining the importance of education on “responsible data/AI citizens” in the face of algorithm bias and security issues around data.

 

Working Group Members:

Nairanjana Dasgupta (Lead) - Washington State University
Abani Patra (Lead) - Tufts University
Purush Papatla - University of Wisconsin Milwaukee
Tony Thrall - National Security Agency
Brian Wright - University of Virginia
Claudia Roda - American University of Paris
Laura Biven - National Institutes of Health
Paul Groth - University of Amsterdam
MC Flor - Florida State University
Barney Mccabe - University of Arizona
Kristen Eschenfelder - University of Wisconsin, Madison
Brian Munoz - University of California, Irvine

A whiteboard with all kinds of writing on it

View the Taxonomy

The STIDS working group developed a taxonomy of competencies for data science masters degree programs.

four bar charts depicting survey responses about data science masters degree programs

Pilot Study

The STIDS working group ran a pilot study to exercise the masters degree program taxonomy. Learn more about the results here.

STIDS Background and Previous Work

With the rapid emergence of data science degree programs it has become challenging for students, faculty, staff, and administrators to meaningfully compare program offerings. To start to address this challenge, ADSA established the Standardization and Transparency for Data Science Degrees (STIDS) Working Group. The initial charge for this Working Group was to create a careful taxonomy for data science competencies in Masters degree programs.

The result of this work is the A Taxonomy for Data Science Masters Degree Programs. Using this taxonomy as a framework, the working group created a survey for those implementing Masters degree programs in data science (or similarly named degrees) to collect information about the skills and competencies covered across various degree programs. The ultimate goal is to make this information transparent and openly available for prospective students, administrators, and future employers of graduates. You can find the results of our pilot survey here.