Team Performance in Long-Duration Space Exploration

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NASA astronauts Andrew Morgan and Jessica Meir collect research samples in the International Space Station for analysis. Credit: NASA. (Apr. 5, 2020)

2020 has been an important year for space exploration, amongst other things. Space missions of a startling variety and ambition are scheduled for launch this year. Indeed, space engineers have not planned so much activity – for both manned and robot projects – since the heady days of the space race between the United States and the Soviet Union in the 1960s. However, it is not just the US and Russia that are dominating this year’s space agenda. India, Japan and China are all planning complex programmes and are vying to become space powers in their own rights. Their plans for 2020 include missions to the moon, Mars and the asteroids.

Space programs around the world are no longer content with robot missions. NASA is preparing to send the first US woman and the next man to the moon in 2024 and a space crew to Mars in 2030. In fact, Bob Behnken and Doug Hurley quite recently were the first two NASA astronauts to have successfully launched from and returned to American soil since the last Space Shuttle mission in 2011 and the first in a commercially built and operated American spacecraft, beginning “a new era in human spaceflight,” says NASA administrator Jim Bridenstine. As we continue to venture farther from Earth, astronauts will face extended communication delays with mission control (6-28 minutes from Mars). With such large communication gaps, astronauts will have to deal with any surprises with almost no help from scientist on Earth. This makes it critical to construct crews that can operate autonomously of mission control.

Previous research suggests that social network relationships among team members impact their performance on job related tasks. By looking at how teams work together, it is possible to predict how the team as a whole will do on different kinds of tasks, including those unplanned tasks that they might need to carry out in space. By doing so, future space crews can be appropriately selected that are capable of operating independently of mission control and survive the harshest conditions of space as they travel to the moon and beyond.

What information is used?

To best select teams for future space missions with challenging autonomous tasks, 2 main aspects need to be considered – team composition and team performance. Data from the Human Exploration Research Analog (HERA), an extended simulation of space exploration that is operated by NASA at the Johnson Space Centre, illustrates these dimensions clearly: 8 4-person crews in HERA missions completed tasks over the course of a 30 or 45 day mission that simulated space exploration, remaining confined in the HERA capsule for the entire duration, and completing various tasks.

During their time in HERA, 4-dimensions of team-level performance were measured – how they did on tasks which required the crew to develop new ideas, solve survival scenarios, resolve ethical dilemmas incorporating multiple conflicting viewpoints, and skill based tasks like operating robots and rovers.

Data via sociometric surveys was also collected over the mission to learn more about the relational networks between crew members (team composition). The relationships between work among the team members were observed over time, and how it changed through 4 different networks – who enjoyed working with who, who made tasks difficult to complete, who provided leadership, and who seeked leadership from others. Matching performance scores to these network surveys allowed for analysis of behaviour that impacted performance.

How is all of this information analysed?

The unique thing about this is that crews were looked at over a period of time. If that was not the case, a simple correlation test would be enough to get the answers we want. However, the aspect of time changes everything. For example, given two individuals (Person A and Person B), A’s relationship towards B most likely depends on B’s relationship towards A – if A does not like B, there is a good chance that B probably does not like A. Or, A’s relationship towards B is independent of all of A’s relationships towards other people. As a result, a novel method is needed to solve this problem: adding controls that models how the network changes over time while controlling for interdependencies that might exist. So, if A does not like B on day 1, there is a high probability that A will continue to not like B during day 2.

It is also important to control for other dimensions like elapsed time in isolation, race of members, military experience of members, etc. This would help  see how performance changes over time and how dependent the performance is on crew relationships.

What do you see?

By looking at these models, we were able to learn a lot about how crews perform –

When crews had to develop new ideas, they performed better when

  • Members disliked working with each other
  • Members did not provide leadership to each other
  • Members did not seek the crew commander’s leadership

When crews had to solve survival scenarios, they performed better when

  • Members enjoyed working with each other
  • Members provided leadership to each other
  • Members saw the commander as a leader
  • Members made tasks difficult to complete for each other

When crews had to conduct skill based tasks, they performed better when

  • Members made tasks difficult to complete for each other
  • Members provided leadership to each other
  • Members saw the commander as a leader

When crews had to resolve ethical dilemmas, they performed better when

  • Members thought that the commander made tasks difficult to complete
  • Members provided leadership to each other
  • Members saw the commander as a leader

What does this mean?

Using these findings, crews can be selected for optimal functionality and cooperativity in a mission. For example, if the mission to Mars is deemed extremely dangerous and mission control expects something to go wrong during the mission, they can send a crew that best solves survival scenarios. When Apollo 13 ran into issues and had to return to Earth, they had the full support of the smartest minds in the planet working tirelessly to get them back home. As astronauts continue to venture farther from earth, space crews might not have that luxury – in order to make these missions a success, choosing the right crew is going to be one of the most challenging tasks.

More posts by Aryaman Gupta.
Team Performance in Long-Duration Space Exploration
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