Effects of Note-Taking Method on Knowledge Transfer in Inspection Tasks

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Abstract

International nuclear safeguards inspectors visit nuclear facilities to assess their compliance with international nonproliferation agreements. Inspectors note whether anything unusual is happening in the facility that might indicate the diversion or misuse of nuclear materials, or anything that changed since the last inspection. They must complete inspections under restrictions imposed by their hosts, regarding both their use of technology or equipment and time allotted. Moreover, because inspections are sometimes completed by different teams months apart, it is crucial that their notes accurately facilitate change detection across a delay. The current study addressed these issues by investigating how note-taking methods (e.g., digital camera, hand-written notes, or their combination) impacted memory in a delayed recall test of a complex visual array. Participants studied four arrays of abstract shapes and industrial objects using a different note-taking method for each, then returned 48–72 h later to complete a memory test using their notes to identify objects changed (e.g., location, material, orientation). Accuracy was highest for both conditions using a camera, followed by hand-written notes alone, and all were better than having no aid. Although the camera-only condition benefitted study times, this benefit was not observed at test, suggesting drawbacks to using just a camera to aid recall. Change type interacted with note-taking method; although certain changes were overall more difficult, the note-taking method used helped mitigate these deficits in performance. Finally, elaborative hand-written notes produced better performance than simple ones, suggesting strategies for individual note-takers to maximize their efficacy in the absence of a digital aid.

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APA

Stites, M. C., Matzen, L. E., Smartt, H. A., & Gastelum, Z. N. (2019). Effects of Note-Taking Method on Knowledge Transfer in Inspection Tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11569 LNCS, pp. 594–612). Springer Verlag. https://doi.org/10.1007/978-3-030-22660-2_44

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