Exploring the challenges of AI experts to inform AI curriculum

Gautam, Sanjana; Akgun, Mahir; Mitra, Prasenjit

doi:10.1145/3545947.3576284

Search citation statements

Order By: Relevance

Paper Sections

Select...

Fundamental Knowledge Representation and Reasoning1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Within the context of a specific application, students should study how to formulate a task as an AI problem, dealing with ill-posed problems, data availability and cleanliness, and biases in data sets, algorithms, and evaluation. These aspects are particularly important to bridge between the study of AI methods and their practical use (Gautam, Akgun, and Mitra 2023).…”

Section: Fundamental Knowledge Representation and Reasoningmentioning

confidence: 99%

Artificial Intelligence in the CS2023 Undergraduate Computer Science Curriculum: Rationale and Challenges

Eaton,

Epstein

2024

AAAI

View full text Add to dashboard Cite

Roughly every decade, the ACM and IEEE professional organizations have produced recommendations for the education of undergraduate computer science students. These guidelines are used worldwide by research universities, liberal arts colleges, and community colleges. For the latest 2023 revision of the curriculum, AAAI has collaborated with ACM and IEEE to integrate artificial intelligence more broadly into this new curriculum and to address the issues it raises for students, instructors, practitioners, policy makers, and the general public. This paper describes the development process and rationale that underlie the artificial intelligence components of the CS2023 curriculum, discusses the challenges in curriculum design for such a rapidly advancing field, and examines lessons learned during this three-year process.

show abstract

Section: Fundamental Knowledge Representation and Reasoningmentioning

confidence: 99%