2.2. The Multi-Attribute Task Battery II (MATB-II)

The MATB-II, depicted in Figure 1, was used as the task environment in the experiment (Santiago-Espada et al., 2011). The MATB-II is a computer-based task, popularized within the human factors research community, to assess human cognitive performance (Kennedy and Parker, 2017). The task interface presents four subtasks that target different cognitive functions of the user (e,g., sustained attention, executive functioning, auditory processing) (Santiago-Espada et al., 2011). The subtask interfaces were designed to present an aviation-familiar setting purposed with inducing stress within pilots and crew members within aviation sectors (Kennedy and Parker, 2017; Nixon and Charles, 2017). However, its applicability for other complex working domains has been supported, as the frequent, uncontrollable and unpredictable stressors imposed throughout tasks elicit similar responses across various domains (Kennedy and Parker, 2017). Furthermore, the subtasks are simple to learn and require short training periods; with task load and complexity adjustable through manipulations of temporal and spatial characteristics (Mortazavi et al., 2019). The MATB-II also facilitates flexible programming that allows for the subtasks to be presented simultaneously, alternatively, or singularly (Santiago-Espada et al., 2011).

MATB-II user interface. RESMAN task located within red boundaries.

The MATB-II's resource management (RESMAN) subtask was implemented to measure the dynamic resilience of users' executive functioning during a dynamic task. The RESMAN subtask was selected as it offers a dynamic, complex, and unpredictable task environment that targets the dynamic decision-making functions of one's executive functioning through requirements of strategizing, scheduling and executing actions (Buehler, 2018). This is achieved by presenting a generalized fuel management task in which individuals must manage the numeric “fuel” levels of two primary tanks. During the task, the primary tanks consume fuel leading to depleted fuel tanks. Users overcome depleting fuel tanks by transferring fuel from secondary tanks to the primary tanks via connecting pumps. However, over the course of the task, connecting pumps may fail and become temporally disabled, and preventing fuel transfer between tanks. In these situations, the user must then strategize the best way to overcome pump failures and redirect fuel to other tanks to counteract depletion in the primary tanks' fuel level. Lastly, the RESMAN subtask's performance output is formatted as a time series, thereby offering compatibility with the dynamic resilience framework.

As depicted in Figure 1, the task's interface presents six tanks connected by eight pumps. Each tank has specific roles and parameters within the task. Tanks “A” and “B” are primary tanks, in which individuals must manage to ensure that the fuel level is always as close to 2,500 units as possible. Tanks “C” and “D” are the finite supply tanks that have connecting pumps to supply additional fuel to the primary tanks. However, as tanks “C” and “D” only have a finite amount of “fuel,” the tanks are susceptible to becoming empty if mismanaged; leading to insufficient “fuel” levels to replenish fuel level depletions in the primary tanks. Lastly, tanks “E” and “F” are secondary tanks that have infinite quantities of fuel. Tanks “E” and “F” have pumps connecting to both the primary tanks and finite secondary tanks, which can be activated to replenish fuel depletion in fuel-needy tanks. Fuel is represented as the green component in the tanks and is further expressed via the numeric value overlaid across the tank graphics. All pumps have a one-directional fuel transfer as each pump have varied units of flow rate that determines how quick the “fuel” can be transferred between tanks. Flow rates are predetermined, in which the individual operator cannot alter.