This lightning talk describes the current effort and status to create recommended curriculum competencies for undergraduate data science programs. In 2023, the ACM Education Board established and chartered a task force to extend the ACM Computing Competencies for Undergraduate Data Science Curricula by producing a multidisciplinary set of competencies for data science with representatives from computing, statistics, and applied mathematics societies. ACM published guidelines in 2021 for delivering appropriate computing competencies in data science programs while acknowledging that computing is one major component of data science, along with mathematics and statistics, along with other components. The ACM Education Board recognized the need to expand on this work and invited participation from numerous statistics and mathematics societies to create a more complete set of guidelines. To that end, the American Statistical Association (ASA), the Mathematical Association of America (MAA), and the Society for Industrial and Applied Mathematics (SIAM) joined the ACM to form a joint task force that would expand on the computing elements and add other appropriate components. This lightning talk will present the status of that effort and provide a means to solicit feedback and input on this process. This session should interest all SIGCSE attendees, especially those developing curricula in Data Science.

The Association of Computing Machinery (ACM) and the Association for Information Systems (AIS) engaged in a project to revise the Information Systems Curriculum. The IS2010 model curriculum has been widely used for nearly a decade. However, its value may be decreasing as new approaches to model curricula have been introduced. The AIS and ACM established an exploratory taskforce which found there have been substantial changes in the IS field, and that current graduates' technical skills do not appear to meet industry needs. The IS discipline must express its core in terms of a standard curriculum that meet stakeholder demands. A joint ACM/AIS taskforce on the Information Systems Model Curriculum (IS2020) was created to develop new IS curriculum guidelines. This panel will introduce the work of the IS2020 taskforce. Panelists will present the key points from the final report. This session should be of interest to faculty and administrators developing college-level curricula in IS.

Prompted by the skyrocketing demand for data scientists, progress made by the ACM Data Science Task Force on defining data science competencies, and inquiries about data science accreditation, ABET is in the process of developing accreditation criteria for undergraduate data science programs. The effort is led by members of a joint data science criteria subcommittee appointed by ABET's Computing Accreditation Commission (CAC) and CSAB (the lead society for computing accreditation). Establishing data science accreditation criteria is a notable milestone in the maturing data science discipline, indicating the presence of an accepted body of knowledge, standards of practice, and ethical codes for practitioners. This position paper motivates the effort and discusses prior work towards defining data science education requirements. It describes the ongoing process for creating and obtaining approval of the accreditation criteria, and how feedback was and will be solicited from the computing and statistical communities. The current draft data science criteria, which was approved in July 2020 by the relevant ABET bodies for a year of public review and comment, is presented. These criteria emphasize the three pillars of data science: computing foundations, mathematical/statistical foundations, and experience in at least one data application domain. This report thus serves both to inform and to stimulate the academic discussion needed to finalize appropriate data science accreditation by ABET.

In this session, members of the ACM Data Science (DS) Task Force will present the final draft of Computing Competencies for Undergraduate Data Science Programs. Drafting this document has been a three-year process, in which the task force has released preliminary drafts, sought input from the community, and responded to the community's helpful feedback. Our intent is that the session be an exchange that will clarify the contents of the report and provide participants with ways to put the report into practice at their own institutions. This session should be of interest to all SIGCSE attendees, but especially to faculty developing college-level curricula in Data Science.

The ACM Data Science Taskforce was established in 2017 by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to the emerging field of data science. This taskforce is seeking to define what the computing contributions are to this multidisciplinary field, in order to provide guidance for computer science or similar departments offering data science programs of study at the undergraduate level. This panel session will provide an update of the work of the ACM Data Science Taskforce and will engage the ITiCSE international community in this effort. Panelists are members of the taskforce and will report on version 2 of a draft report released Fall 2019, and the activities to-date, including a summary of data science curricular efforts, as well as the current articulation of computing competencies. This session should be of interest to all conference attendees, but especially faculty developing bachelors-level curricula in Data Science.

The ACM Data Science Taskforce was established by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to this emerging field. This special session seeks to provide an update of the work of the ACM Data Science Taskforce as well as to engage the SIGCSE community in this effort. Members of the taskforce will report on version 2 of a draft report released Fall 2019, and the activities to-date, including a summary of data science curricular efforts to date, as well as the current articulation of computing competencies. This session should be of interest to all SIGCSE attendees, but especially faculty developing college-level curricula in Data Science.

The model curriculum used to develop, update, and assess IS programs (IS2010) is now nearly a decade old, and an assessment of the curriculum itself indicates that its value is decreasing due to the changing technological and skills demands in the information systems environment. Therefore, the ACM and AIS established an Exploratory Task Force that assessed IS2010 and recommended a taskforce be created to update the content and structure for a new model curriculum. One recurring theme is that current graduates' technical skills do not appear to meet industry needs. The IS discipline must express its core in terms of a standard curriculum to provide a foundation upon which to develop and offer undergraduate IS programs that meet stakeholder demands. A taskforce on the Information Systems Model Curriculum (IS2020) was created following the report and recommendation of the Exploratory Taskforce. This panel seeks to introduce the work of this taskforce as well as engage the IS education community in this effort. Panelists will introduce key components of this process and seek input and feedback. This session should be of interest to all attendees, especially faculty developing college-level curricula in Information Systems.

The ACM Data Science Task Force was established by the ACM Education Council and tasked with articulating the role of computing discipline-specific contributions to this emerging field. This special session seeks to introduce the work of the ACM Data Science Task Force as well as to engage the SIGCSE community in this effort. Members of the task force will introduce key components of a draft report, including a summary of data science curricular efforts to date, results of ACM academic and industry surveys on data science, as well as the initial articulation of computing competencies for undergraduate programs in data science. This session should be of interest to all SIGCSE attendees, but especially faculty developing college-level curricula in Data Science.

The inclusion of social issues, including ethical and professional topics, in computing curricula has become commonplace two decades after being incorporated into the ACM Computing Curricula. However, authors of academic papers and conference presentations often concentrate on integrating the broader issues of societal impact and best practices into computing curricula, while neglecting the assessment of their benefits. This panel explores how the institutions of the panelists include social issues in projects and the curriculum as a whole, and additionally how they assess the benefits of doing so. Special attention is given to an appreciation of the social good emanating from the use of community-based and non-profit organizations in student projects. Additionally, ways to assess the effectiveness of these approaches are presented in an effort to help meet model curriculum guidelines and accreditation requirements.

This poster updates a paper [3] presented at ITiCSE 2006 and re-examines a ten-year effort of our institution's use of community-based non-profit organizations (NPOs) in the information systems capstone course. Computer science or information systems majors often have adequate technical skills but lack an understanding of organizational processes, team project experience, and the ability to integrate information technology into an organizational setting. To bridge this gap, we use service-learning group projects that leverage local organizations. We document this effort to provide recommendations for successfully implementing similar courses.

In 2003, Grand Valley State University started a Masters program in Medical & Bioinformatics. This M.S. degree, together with related degrees in Biostatistics and Biotechnology, were part of the "Professional Science Masters" development and implementation initiative supported by the Sloan Foundation. The interdisciplinary curriculum includes common core courses, the promotion and development of "soft skills" through teamwork and project management experiences, and an applied research focus with a mandatory business/industry internship. Instrumental to achieving these goals is a strong lab component to the curriculum that incorporates familiarity with industry-standard and widely-used software packages. We here give an update on details of the system architecture, software components, and their adaptations through the first six years of our program.

Complaints often expressed about undergraduate computer science or information systems programs,,, is that students graduate with adequate technical skills but often lack an understanding of organizational processes, team project experience, and the ability to integrate information technology in an organizational setting. To address this, educators have historically created service-learning group projects, which leverage local organizations. These types of projects can be very rewarding for students and offer excellent educational opportunities for the students within the group. Educators who have taught service-learning group projects know there are significant problems with using this type of project. These problems include: motivation of students to do their best work, fair individual and overall group assessment, appropriate workload for a semester, and minimizing disruptive outside influences. In addition, the creation of new projects on a continuous semester basis would be very useful for the instructor of a project course. To solve these issues and problems, the following capstone course design was used with success at Grand Valley State University (GVSU). A socially-relevant, community-based assignment with local non-profit organizations provided the basis for the capstone information systems project course described in this paper. This project course produced working applications for actual clients that gave students a unique capstone experience.

Grand Valley State University has recently created a new Masters program in Medical & Bioinformatics. The M.S. degree, along with related degrees in Biostatistics and Biotechnology, are components of the "Professional Science Masters" development and implementation initiative supported by the Sloan Foundation. Key features of the new curriculum include an interdisciplinary framework with common core courses, the promotion and development of "soft skills" through teamwork and project management experiences, and an applied research focus highlighted by a mandatory business/industry internship. Instrumental to achieving these goals is a strong lab component to the curriculum that incorporates familiarity with industry-standard software packages. The laboratory infrastructure will be utilized by multiple courses, thus interconnecting different foci of the program and providing a complete experience for students.

No abstract available.