An official website of the United States government
Over the past decade, data science courses have been growing more popular across university campuses. These courses often involve a mix of programming and statistics and are taught by instructors from diverse backgrounds. In our experiences launching a data science program at a large public U.S. university over the past four years, we noticed one central tension within many such courses: instructors must finely balance how much computing versus statistics to teach in the limited available time. In this experience report, we provide a detailed firsthand reflection on how we have personally balanced these two major topic areas within several offerings of a large introductory data science course that we taught and wrote an accompanying textbook for; our course has served several thousand students over the past four years. We present three case studies from our experiences to illustrate how computer science and statistics instructors approach data science differently on topics ranging from algorithmic depth to modeling to data acquisition. We then draw connections to deeper tradeoffs in data science to help guide instructors who design interdisciplinary courses. We conclude by suggesting ways that instructors can incorporate both computer science and statistics perspectives to improve data science teaching.
more »
« less
This content will become publicly available on February 18, 2026
Alignment of Data Science Programs with ACM Competencies
The rapid expansion of data science programs across a wide range of academic disciplines - including computer science, engineering, business, and other applied data domains - presents a challenge for standardizing curricula in line with established competencies. This paper critically examines whether university data science programs are aligned with the ACM Competencies for Undergraduate Data Science Curricula. Using a systematic review of 788 data science program offerings and 9,322 course titles, we assess levels of alignment with ACM's eleven competency areas. Additionally, we evaluate the inclusion of additional common skills course offerings, such as math/statistics, data analytics, and capstone courses. Our findings highlight significant variability in programs' adherence to the ACM competencies. This underscores the need for greater interdisciplinary collaboration towards integrating computing, statistics, and domain-specific coursework into the broad range of data science curricula, ensuring that data science graduates have a well-rounded, interdisciplinary skill set suited to the diverse applications of data science.
more »
« less
- Award ID(s):
- 2419005
- PAR ID:
- 10625187
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400705328
- Page Range / eLocation ID:
- 1760 to 1760
- Subject(s) / Keyword(s):
- Data science, Curriculum, ACM Competencies
- Format(s):
- Medium: X
- Location:
- Pittsburgh PA USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Data Science is one of the fastest growing fields with unmet demand from employers. Many academic institutions have taken on the task of creating programs to meet both current and future needs and demands. Data science, as a field, integrates aspects of computer science, statistics, and subject matter expertise which encourages cross-disciplinary conversations and collaboration. In this talk, we present results from a broad survey of instructors of introductory college-level data science courses for undergraduates. In addition, we explore the alignment of these findings with the recommendations of various professional organizations. We conducted a national survey on topics covered in introductory, college-level data science courses. With responses from computer scientists, statisticians, and allied fields, these results represent a wide array of instructors of data science. The survey identifies topics commonly covered, the amount of time spent on each, common and divergent definitions of data science, and course materials used. These results will be presented. We will then discuss the alignment of these results through a rigorous review and synthesis of recommendations from various professional organizations. These include Association for Computing Machinery's Computing Competencies for Undergraduate Data Science Curricula[1], the National Academies of Science, Engineering, and Medicine’s Data Science for Undergraduates: Opportunities and Options[2], the Park City Math Institute's report Curriculum Guidelines for Undergraduate Programs in Data Science[3], and the American Statistical Association’s Two-Year College Data Science Summit Final Report[4] and Curriculum Guidelines for Undergraduate Programs in Statistical Science[5]. We will also explore alignment with ABET’s accreditation of data science.[6]more » « less
-
Since the 1960s, the ACM has provided routinely updated guidelines for what concepts constitute a computer science curriculum, with the latest version currently in development in 2023. These guidelines have traditionally provided a model curriculum from which universities can choose to adopt or modify for their own purposes. What is unclear, however, is to what degree schools follow the curriculum recommendations that the ACM provides. While most faculty and students likely have knowledge of their own institution's curriculum, as well as what courses are offered at a small selection of other schools, the goal of the work presented in this poster is to distill a cohesive view of what computer science curriculums in their second and third years look like across a broad range of universities across a range of institutions. Our goal with this work was to answer the following question: What do computer science course requirements look like at a wide range of different institutions? We believe the work will help those who are trying to develop curriculum changes within their own institutions and aims to provide a more cohesive view of what trends and patterns exist in course offerings and degree requirements for computer science in the second and third years across a wide range of universities.more » « less
-
Businesses are increasingly facing economic, social, and environmental sustainability challenges. Science, technology, engineering, and math (STEM) are needed to address business sustainability needs, yet such competencies are noticeably absent from academic literature and business curricula. To mend the curricular gap, we make the case for developing cross-disciplinary STEM-based business sustainability curricula that enhance students’ sustainability literacy and cognitive abilities related to STEM and sustainability. A literature review is provided that documents curricular gaps specific to STEM and sustainability in the academic literature and in business sustainability program offerings. We then present a framework that can be used to integrate STEM and sustainability across the curricula and to evaluate curricular implementation. This review provides timely and relevant information that can help business management educators, instructors, and administrators justify, design, develop, implement, and evaluate STEM-based business sustainability curricula.more » « less
-
ABSTRACT Materials science skills and knowledge, as an addition to the traditional curricula for physics and chemistry students, can be highly valuable for transition to graduate study or other career paths in materials science. The chemistry and physics departments at Weber State University (WSU) are harnessing an interdisciplinary approach to materials science undergraduate research. These lecture and laboratory courses, and capstone experiences are, by design, complementary and can be taken independently of one another and avoid unnecessary overlap or repetition. Specifically, we have a senior level materials theory course and a separate materials characterization laboratory course in the physics department, and a new lecture/laboratory course in the chemistry department. The chemistry laboratory experience emphasizes synthesis, while the physics lab course is focused on characterization techniques. Interdisciplinary research projects are available for students in both departments at the introductory or senior level. Using perovskite materials for solar cells, WSU is providing a framework of different perspectives in materials: making materials, the micro- and macrostructure of materials, and the interplay between materials to create working electronic devices. Metal-halide perovskites, a cutting-edge technology in the solar industry, allow WSU to showcase that undergraduate research can be relevant and important. The perovskite materials are made in the chemistry department and characterized in the physics department. The students involved directly organize the collaborative exchange of samples and data, working together to design experiments building ownership over the project and its outcomes. We will discuss the suite of options available to WSU students, how we have designed these curricula and research, as well as some results from students who have gone through the programs.more » « less
