The document "ACM 2023: CS + X—Challenges and Opportunities in Developing Interdisciplinary-Computing Curricula" discusses the growing interest in interdisciplinary undergraduate computing curricula, which integrate foundational computing concepts with other disciplines, such as the natural sciences, social sciences, humanities, and the arts. These programs, known as "CS+X," aim to broaden participation in computing and address the increasing demand for computational literacy across various sectors. They also have the potential to increase diversity in computing, particularly by attracting more women and underrepresented groups.

The document covers various types of CS+X programs, ranging from single interdisciplinary courses to full majors. Examples of successful CS+X programs are provided, such as "Computing in the Arts" at the College of Charleston, interdisciplinary degrees at the University of Illinois Urbana-Champaign, and integrated media computation courses at Georgia Tech. These programs not only enhance students' computational skills but also equip them with complementary knowledge from other fields, making them highly desirable to employers.

Key challenges discussed include enrollment pressures in computer science departments, the need for collaboration between different academic departments, and potential difficulties in achieving diversity across different disciplines. The report emphasizes the importance of institutional support, faculty collaboration, and the development of synthesis courses that integrate computing with other disciplines.

The paper "The State of Undergraduate Computational Science Programs" reviews the challenges and opportunities in undergraduate computational science education in the U.S. Computational science is increasingly critical for advancements in fields like biomedicine, energy, and nanomanufacturing, and is vital for economic competitiveness. Despite its importance, the growth of undergraduate programs has been slow, with only 29 programs identified and modest graduation rates. Major challenges include difficulty in student recruitment due to unclear career paths and additional credit requirements. Faculty participation is limited, often due to expertise gaps and teaching burdens. Programs also face resource constraints, such as insufficient hardware, software, and adjunct faculty support. Recommendations include introducing mandatory modeling and simulation courses, fostering industry partnerships, and creating better recruitment strategies. Emphasis on interdisciplinary projects and capstone courses can help highlight the field’s real-world relevance. National campaigns and collaboration with high schools could increase awareness and interest. Ultimately, the field requires sustained institutional support and alignment with industry needs to scale effectively. 

Computational science is increasingly essential for scientific and industrial advancements but faces significant challenges in undergraduate education. A survey of 29 U.S. programs highlights issues like difficulty recruiting students, limited faculty participation, and resource constraints. Programs struggle with unclear career pathways for graduates and additional credit hour requirements, deterring student enrollment. Recommendations include introducing mandatory modeling and simulation courses, fostering industry partnerships, and improving national awareness of the field. Sustained institutional support and innovative strategies are needed to grow these programs and prepare a workforce skilled in computational science. 

Undergraduate computational science programs are critical for advancing science and industry but face challenges like low student recruitment, limited faculty participation, and resource constraints. These programs provide essential skills in modeling, simulation, and computational techniques, yet unclear career paths and additional credit requirements deter students. Faculty engagement is hampered by expertise gaps and high teaching loads, while resource limitations restrict the development of courses and internships. Recommendations include introducing mandatory modeling courses, fostering industry partnerships, and increasing national awareness of the field's importance. Sustained support and innovative strategies are essential to scale up these programs and meet workforce demands.