NASA’s future deep space missions to the lunar environment, lunar surface, and to Mars involve both a long-duration and long communication delays. These factors drive a requirement for durable training, specifically training that can survive long delays between time of training and actual use of the learned knowledge and skills. In addition, the training needs to be flexible to allow for transfer to new and unexpected situations beyond those included in a standard training regimen, as it will not be possible to accurately anticipate all possible situations in which crewmembers might encounter. Furthermore, onboard just-in-time (JIT) training and performance support tools will be required.
On such long-duration space missions with communication delays, the crew will need to be semi-autonomous at minimum. Current crew training practices are based on the assumption that ground support is available continuously and in real-time, which will not be the case in future long-duration space missions. With no direct experience with long-duration space missions, serious gaps exist in current data upon which new crew training must be based. This experiment aims to test the retention and transfer of specific motor, perceptual and cognitive processes learned pre-launch to assess the need for onboard refresher and JIT training.
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Two experimental tasks were conducted with crew and crew-like subjects tested at NASA’s Johnson Space Center, and with university undergraduate students tested at the University of Colorado, performing the same tasks under the exact same experimental paradigm. Six experimental sessions were conducted over a period of 480 days, in the following order:
Session 1: Pretest. Subjects performed 50 trials of the standard data entry task (typing 4-digit numbers, e.g., 2154, using right hand), 50 trials of a word task (typing 4-digit numbers presented as words, e.g., two one five four, using right hand), 50 trials a left-hand task (typing 4-digit numbers, e.g., 2154, using left hand), 50 trials of a 3-digit task (typing 3-digit numbers, e.g., 215, using right hand), and 50 trials of a code task (typing positions of letters within the alphabet, e.g., baed, using right hand).
Session 2: Training Session 1. Subjects competed three blocks of trials of the standard data entry task. Each block consisted of 100 trials, and the same 100 numbers were repeated in each of the three blocks.
Session 3: Training Session 2. Identical to Training Session 1; subjects competed three blocks of trials of the standard data entry task. Each block consisted of 100 trials, and the same 100 numbers were used as during the first training session.
Session 4: Onboard Session 1. Subjects completed 100 trials of the standard task followed by 100 trials of the left-hand task. For both the standard task and the left-hand task, fifty trials were on old numbers (numbers that had been practiced during training), and fifty trials were on new numbers.
Session 5: Onboard Session 2. Subjects completed 100 trials of the standard task followed by 100 trials of the code task. For both the standard task and the code task, fifty trials were on old numbers (numbers that had been practiced during training), and fifty trials were on new numbers. To create old numbers for the code task, digits for each old 4-digit number were replaced with letters (a = 1, b = 2, etc.).
Session 6: Post-test. The post-test was identical to the pre-test.
Training: Averaging across training sessions and blocks, there were differences in accuracy between subject types; crew and crew-like subjects demonstrated higher accuracy than did undergraduate subjects. Average total response time (TRT) decreased from the first training session to the second training session, as well as across blocks within each training block. There was a marginally significant difference in TRT between subject types, with faster TRT for crew than for crew-like and undergraduate subjects. A post-hoc test revealed that the difference between NASA subjects (combining crew and crew-like) and undergraduate subjects was significant.
Test 1 (Standard, Left Hand): For the standard task, accuracy was higher for old numbers than for new numbers for crew and crew-like subjects; the opposite pattern was observed for undergraduate subjects. For the left-hand task the opposite pattern was observed: accuracy was higher for new numbers than for old numbers for crew and crew-like subjects, but accuracy was higher for old numbers than for new numbers for undergraduate subjects. Subjects were faster to perform the standard task than the left-hand task. Averaging across task, old numbers were entered more quickly than new numbers. However, the repetition priming effect was larger for the left-hand task than for the standard task. The repetition priming effect was marginally significant for the standard task but significant for the left-hand task.
Test 2 (Standard, Code): Overall accuracy was higher for the standard data entry task than for the code task. There were also differences in accuracy between subject types; on average, accuracy was higher for crew and crew-like subjects than for undergraduate subjects. However, the increase in accuracy for crew and crew-like subjects was restricted to the code task; accuracy was similar for the three subject types on the standard task. Subjects were also faster to perform the standard task than the code task, with a significant repetition priming effect. Averaging across tasks, old numbers were entered more quickly than new numbers. The repetition priming effect was larger for the code task than for standard task, although it was significant for both the standard task and the code task.
Overall, similar results were obtained for the crew and crew-like subjects as found for university students, although the crew and crew-like subjects consistently performed at a higher level than the university students. Importantly on both tasks, the crew and crew-like subjects showed different patterns of response under cognitive load (i.e., by the extra requirements of the code task in the first task and by the secondary counting task in the second task) than the patterns shown by the university students. Thus, crew members’ performance under cognitive load on the ground cannot be predicted from the performance of university undergraduate students. Given the criticality of cognitive performance during space missions and given the significant cognitive loads space missions impose on the astronaut crew, this finding has important implications for research assumptions that are driven by university-based research.
Crew health and performance is critical to successful human exploration beyond low Earth orbit.
The Human Research Program (HRP) investigates and mitigates the highest risks to human health
and performance, providing essential countermeasures and technologies for human space exploration.
Risks include physiological and performance effects from hazards such as radiation, altered gravity,
and hostile environments, as well as unique challenges in medical support, human factors,
and behavioral health support. The HRP utilizes an Integrated Research Plan (IRP) to identify
the approach and research activities planned to address these risks, which are assigned to specific
Elements within the program. The Human Research Roadmap is the web-based tool for communicating the IRP content.
The Human Research Roadmap is located at: https://humanresearchroadmap.nasa.gov/
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for information of how this experiment is contributing to the HRP's path for risk reduction.