Teaching computational archival science: context, pedagogy, and future directions

Abstract

Introduction. The paper describes the development of the new transdisciplinary field of computational archival science (CAS) and the integration of computational thinking (CT) concepts into archival science.

Method. The authors show how CAS can be introduced into graduate archival training through two case studies at the University of Maryland and the University of British Columbia and discuss building and sustaining CAS educator networks.

Analysis. The paper argues that, given the increasing use of AI in archival work and research, the acquisition of computational skills and competencies is urgent for those entering the profession, but sees several barriers, including the willingness of archival educators to engage in this space, and the shortage of CAS educators. There is also a perceived conflict among some in the archival profession between CAS and recent archival scholarship emphasizing postcolonialism themes.

Results. Results show this is a false dichotomy, as demonstrated by the many CAS papers focusing on ethical and social justice aspects of computing and archival work.

Conclusion. The teaching of CAS is a necessity for archivists to stay relevant and responsive to the changing landscape. We offer CAS graduate curriculum learning guidelines, ensuring that archives remain accessible, trustworthy, and reflective of our evolving society.