A Model for Types and Levels of Human Interaction with Automation
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Abstract
286 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 30, NO. 3, MAY 2000 A Model for Types and Levels of Human Interaction with Automation Raja Parasuraman, Thomas B. Sheridan, Fellow, IEEE, and Christopher D. Wickens Abstract—Technical developments in computer hardware and software now make it possible to introduce automation into virtually all aspects of human-machine systems. Given these technical capabilities, which system functions should be automated a
Summary
HFES conference proceedings report (Aspire Conference) documenting N-back temporal instability findings. Two-experiment study showing N-back performance improvement and workload decrease over 26+ on-road driving sessions. Experiment 1: 10 participants with 26+ exposures show systematic accuracy increases and cognitive demand decreases. Experiment 2: Old vs New digit sequences tested with 20 participants; equivalent performance confirms strategy-based improvement.
Key finding
N-back accuracy and DRT-based workload measures show systematic drift over repeated on-road sessions, with improvements attributable to general strategy acquisition (subvocal rehearsal, automatization) rather than sequence-specific learning.
Methodology
Exp 1: 10 participants, repeated measures across 6 sessions from 26 total. Exp 2: 20 participants, Old/New sequence comparison. On-road driving paradigm with DRT and NASA-TLX measures.
Sample size: Exp 1: N=10; Exp 2: N=20
Quality score: 5 / 5