Work2018

Introducing Computational Thinking into Archival Science Education

William Underwood · David Weintrop · Michael J. Kurtz · Richard J. Marciano

15 citations0/0 files storedIEEE International Conference on Big Data (BigData)

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Digital and Traditional Archives Management Teaching and Learning Programming Digital Humanities and Scholarship

Abstract

The discipline of professional archivists is rapidly changing. Most contemporary records are created, stored, maintained, used and preserved in digital form. Most graduate programs and continuing education programs in Archival Studies address this challenge by introducing students to information technology as it relates to digital records. We propose an approach to addressing this challenge based on introducing computational thinking into the graduate archival studies curriculum.

Citations in this library

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References

2002Preservation of the Integrity of Electronic Records 1984Society of American Archivists 2018Archival Records and Training in the Age of Big Data 2018Computer-Assisted Appraisal and Selection of Archival Materials

Cited by

2022Archives, Access and Artificial Intelligence 2018Automating the Detection of Personally Identifiable Information (PII) in Japanese-American WWII Incarceration Camp Records 2021Computational Archival Science is a Two-Way Street 2023The Utility of Standards and Good Practice Guidelines for Records Professionals: comparing apples, oranges, and other fruits 2023Can GPT-4 Think Computationally about Digital Archival Practices?2024Training in Computational Archival Science: Do CAS Educational Frameworks meet Professional Expectations?

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