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NASA NTRSDate not supplied

HAT m:N Cognitive Task Analysis (CTA)

This Cognitive Task Analysis (CTA) study was designed to understand the capability of the m:N Tactical Operator (TO) interfaces developed by the Human-Autonomy Teaming Laboratory at NASA Ames to support operators responsible for simplified pilot operations of 100 independently operated small UAS (sUAS) in a constrained geographic area. The m:N sUAS TO interface includes a central Tactical Situation Display (TSD) digital map with moving icons reflecting the sUAS location and planned flight route. The interface also has two side panels. The left panel includes a tabular list of UAS assets and mission tasking, a list of recently viewed assets, and a list of events and alerts. The right panel includes a tabular list of UAS assets and their associated telemetry, text-based chat communication window, and a tabbed checklist window. This CTA was adapted from the incident-based applied cognitive task analysis (Militello & Hutton, 1998) and included demographics questions, scenario-based simulations, a task diagram and knowledge audit methods. In addition to examining the support provided by this m:N sUAS TO interface, this CTA study, conducted with aviation subject matter experts in analogous roles to the future tactical operator, was designed to illuminate and project likely cognitive requirements of the tactical operator. Interviewees participated in two scenario-based simulations using the m:N sUAS TO interfaces. In the first simulation, the interviewees supervised 12 sUAS operating in downtown San Diego, California transiting to and from a central sUAS Hive, restaurant locations, and customer drop off locations. Interviewees were asked to react to a UAS Volume Reservation (UVR) event with a two-phase impact on food delivery operations. In the second scenario, the interviewees supervised 100 sUAS operating in the same airspace and with the same mission. Interviewees used the interfaces to recognize and react to two sUAS air vehicle problems. After each scenario, we asked the interviewees a semi-structured list of questions to elicit their reflections about using the interfaces. Interviewees were confident in their ability to respond to two off-nominal situations in each simulation. Interviewees felt that, given high levels of automation on the sUAS, they would be able to manage the events without requiring additional support or handing off the sUAS to a colleague or supervisor in both the n=12 or n=100 sUAS settings. In the n=12 sUAS condition, interviewees used the center map to understand the asset location and progress along with mission tasking. An additional display window, Asset Telemetry, helped interviewees understand battery state and sUAS altitude. When the number of sUAS increased, interviewees altered their behavior. Rather than maintaining awareness of individual assets, interviewees appeared to become more reactive, managing exceptions. Interviewees reported that they spent less time looking at the nominal aircraft, and focused their attention primarily on the off-nominal aircraft. In addition, in the second simulation with n=100 sUAS, interviewees reported that they relied more on the side panels (Mission Timeline and Asset Telemetry) to gather information.

human-autonomy teaming↗
NASA NTRS2025

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗
NASA NTRSDate not supplied

Establishing the Framework for e-VTOL Flight Mission Scenario Development for Urban Air Mobility Research using Cognitive Task Analysis

This paper focuses on applying specific protocol aspects of Cognitive Task Analysis (CTA) methods to formulate non-routine flight mission use-case scenarios in support of a potential research study at the National Aeronautics and Space Administration (NASA) Langley Research Center under the Air Traffic Management – eXploration (ATM-X) Urban Air Mobility (UAM) sub-project. The objective of use-case scenarios is to provide a hypothetical situation to elicit expert knowledge and feedback in a specific subject matter area. Use-case scenarios in the field of aviation, including UAM, can help to support the safe integration of these vehicles into the National Airspace System (NAS) through the examination of airspace procedures during non-routine events. Inherent in this type of research is the need to study in-flight non-routine scenarios that the UAM vehicle could encounter. Situations categorized as non-routine events are any events that occur outside of the original flight plan such as a mechanical malfunction or other in-flight emergency requiring special procedures, which can include diversions to a specified, or non-specified, emergency landing area. In specific instances, some non-routine events could be considered as “routine” during in-flight operations, such as the need to perform a go-around due to a balked landing. As the rate of technological expansion surrounding UAM grows rapidly in modern aviation, so does the need for research that focuses on the safe integration of these vehicles including research with a focus on the methods and development of airspace operational procedures. Research rooted in CTA methods provides a framework for developing use-case scenarios appropriate for environments where mental demands are substantial. Substantial mental demands exist while operating in the NAS for pilots, airline dispatchers, and air traffic controllers among many others. With the focus on UAM in mind, it is critical to frame a baseline use-case scenario using information as it pertains to current-day airspace operations. According to Dr. Robert R. Hoffman’s “Protocols for Cognitive Task Analysis,” one of the first steps to applying CTA methods to research is the concept of “bootstrapping” in which the researcher(s) familiarize themselves with the domain that is being studied. To formulate the non-routine flight mission use-case scenarios for the purpose of this potential NASA ATM-X UAM research study, and to inform the baseline use-case scenario, the practice of bootstrapping was utilized to acquire knowledge of current-day airspace procedures.

Heidi S Glaudel↗
NASA NTRS2001

Cognitive Task Analysis of Business Jet Pilots' Weather Flying Behaviors: Preliminary Results

This report presents preliminary findings from a cognitive task analysis (CTA) of business aviation piloting. Results describe challenging weather-related aviation decisions and the information and cues used to support these decisions. Further, these results demonstrate the role of expertise in business aviation decision-making in weather flying, and how weather information is acquired and assessed for reliability. The challenging weather scenarios and novice errors identified in the results provide the basis for experimental scenarios and dependent measures to be used in future flight simulation evaluations of candidate aviation weather information systems. Finally, we analyzed these preliminary results to recommend design and training interventions to improve business aviation decision-making with weather information. The primary objective of this report is to present these preliminary findings and to document the extended CTA methodology used to elicit and represent expert business aviator decision-making with weather information. These preliminary findings will be augmented with results from additional subjects using this methodology. A summary of the complete results, absent the detailed treatment of methodology provided in this report, will be documented in a separate publication.

Latorella, Kara↗
NASA NTRS1987

Operator function modeling: An approach to cognitive task analysis in supervisory control systems

In a study of models of operators in complex, automated space systems, an operator function model (OFM) methodology was extended to represent cognitive as well as manual operator activities. Development continued on a software tool called OFMdraw, which facilitates construction of an OFM by permitting construction of a heterarchic network of nodes and arcs. Emphasis was placed on development of OFMspert, an expert system designed both to model human operation and to assist real human operators. The system uses a blackboard method of problem solving to make an on-line representation of operator intentions, called ACTIN (actions interpreter).

Mitchell, Christine M.↗
NASA NTRS1990

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

Mitchell, Christine M.↗
NASA NTRS1991

Requirements for psychological models to support design: Towards ecological task analysis

Cognitive engineering is largely concerned with creating environmental designs to support skillful and effective human activity. A set of necessary conditions are proposed for psychological models capable of supporting this enterprise. An analysis of the psychological nature of the design product is used to identify a set of constraints that models must meet if they can usefully guide design. It is concluded that cognitive engineering requires models with resources for describing the integrated human-environment system, and that these models must be capable of describing the activities underlying fluent and effective interaction. These features are required in order to be able to predict the cognitive activity that will be required given various design concepts, and to design systems that promote the acquisition of fluent, skilled behavior. These necessary conditions suggest that an ecological approach can provide valuable resources for psychological modeling to support design. Relying heavily on concepts from Brunswik's and Gibson's ecological theories, ecological task analysis is proposed as a framework in which to predict the types of cognitive activity required to achieve productive behavior, and to suggest how interfaces can be manipulated to alleviate certain types of cognitive demands. The framework is described in terms, and illustrated with an example from the previous research on modeling skilled human-environment interaction.

Kirlik, Alex↗
NASA NTRS2024

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVA on the Moon and Mars are expected to be higher compared to microgravity EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We used the applied cognitive task analysis method as outlined by Militello and Hutton (1998) and conducted interviews with subject matter experts (SMEs) in EVA at NASA Johnson Space Center in summer 2024. Interviews focused on exploration EVA and elicited feedback from SMEs on the cognitive skills required for specific EVA tasks including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis will inform ongoing work to identify the key cognitive domains for safe decision-making during exploration mission class EVA on the Moon and Mars. This work will importantly provide a link between cognitive domains identified in the cognitive task analysis and operationally-relevant performance metrics collected during spaceflight and simulation EVA that can be tracked and assessed by NASA mission operations. Ultimately, this work will aid in the development and application of exploration class cognitive performance monitoring capabilities to improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗
NASA NTRSDate not supplied

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVAs on the Moon and Mars are expected to be higher compared to microgravity EVAs currently conducted from the International Space Station. Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We conducted a cognitive task analysis with 15 astronauts and subject matter experts in EVA operations and research. Interviews focused on surface exploration EVA and elicited feedback from experts on the cognitive skills required for specific EVA tasks, including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis informs ongoing exploration EVA for Moon to Mars. This work identifies the specific cognitive challenges that astronauts are likely to encounter during surface exploration EVA, and provides the foundation for: (1) prioritized and targeted cognitive performance measurement and functional performance tests, (2) EVA simulation design at varying levels of cognitive workload, and (3) the development of training and other technologies that can improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗
NASA NTRS2001

Preliminary Results Obtained in Integrated Safety Analysis of NASA Aviation Safety Program Technologies

This is a listing of recent unclassified RTO technical publications processed by the NASA Center for AeroSpace Information from January 1, 2001 through March 31, 2001 available on the NASA Aeronautics and Space Database. Contents include 1) Cognitive Task Analysis; 2) RTO Educational Notes; 3) The Capability of Virtual Reality to Meet Military Requirements; 4) Aging Engines, Avionics, Subsystems and Helicopters; 5) RTO Meeting Proceedings; 6) RTO Technical Reports; 7) Low Grazing Angle Clutter...; 8) Verification and Validation Data for Computational Unsteady Aerodynamics; 9) Space Observation Technology; 10) The Human Factor in System Reliability...; 11) Flight Control Design...; 12) Commercial Off-the-Shelf Products in Defense Applications.

Source record↗
NASA NTRS2004

Situation Awareness Implications of Adaptive Automation of Air Traffic Controller Information Processing Functions

The goal of this research was to define a measure of situation awareness (SA) in an air traffic control (ATC) task and to assess the influence of adaptive automation (AA) of various information processing functions on controller perception, comprehension and projection. The measure was also to serve as a basis for defining and developing an approach to triggering dynamic control allocations, as part of AA, based on controller SA. To achieve these objectives, an enhanced version of an ATC simulation (Multitask (copyright)) was developed for use in two human factors experiments. The simulation captured the basic functions of Terminal Radar Approach Control (TRACON) and was capable of presenting to operators four different modes of control, including information acquisition, information analysis, decision making and action implementation automation, as well as a completely manual control mode. The SA measure that was developed as part of the research was based on the Situation Awareness Global Assessment Technique (SAGAT), previous goal-directed task analyses of enroute control and TRACON, and a separate cognitive task analysis on the ATC simulation. The results of the analysis on Multitask were used as a basis for formulating SA queries as part of the SAGAT-based approach to measuring controller SA, which was used in the experiments. A total of 16 subjects were recruited for both experiments. Half the subjects were used in Experiment #1, which focused on assessing the sensitivity and reliability of the SA measurement approach in the ATC simulation. Comparisons were made of manual versus automated control. The remaining subjects were used in the second experiment, which was intended to more completely describe the SA implications of AA applied to specific controller information processing functions, and to describe how the measure could ultimately serve as a trigger of dynamic function allocations in the application of AA to ATC. Comparisons were made of the sensitivity of the SA measure to automation manipulations impacting both higher-order information processing functions, such as information analysis and decision making, versus lower-order functions, including information acquisition and action implementation. All subjects were exposed to all forms of AA of the ATC task and the manual control condition. The approach to AA used in both experiments was to match operator workload, assessed using a secondary task, to dynamic control allocations in the primary task. In total, the subjects in each experiment participated in 10 trials with each lasting between 45 minutes and 1 hour. In both experiments, ATC performance was measured in terms of aircraft cleared, conflicting, and collided. Secondary task (gauge monitoring) performance was assessed in terms of a hit-to-signal ratio. As part of the SA measure, three simulation freezes were conducted during each trial to administer queries on Level 1, 2, and 3 SA.

Kaber, David B.↗
NASA NTRS1989

View graphs for GSFC Colloquium on OFMspert

Viewgraphs providing an overview of activities concerned with the development and testing of the Operator Function Model (OFM) expert system (OFMspert) are presented. The OFM is a mathematical tool for representing operator interaction with predominantly automated space ground control systems. OFM provides cognitive task analysis and served as the basis for the design of an intelligent operator's associate called OMFspert. An experimental implementation of OFMspert, referred to as Ally, was developed. An empirical evaluation of Ally was conducted to determine the effectiveness of a supervisory control team consisting of a human operator and Ally versus a control team consisting of two human operators. The experiment was carried out in the GT-MSOCC (Georgia Tech MultiSatellite Operations Control Center) domain, a research tool consisting of a high fidelity implementation of the operator interface to a GSFC ground control system. The viewgraphs outline the experimental design, operator performance measures, and preliminary results.

Mitchell, Christine M.↗
NASA NTRS1990

Graphical interfaces for cooperative planning systems

Based on a cognitive task analysis of 5 airline flight crews in a simulator study, researchers have designed a testbed for studying computer aids for en route flight path planning. This testbed runs on a Mac II controlling three color monitors, and is being used to study the design of aids for both dispatchers and flight crews. Specifically, the research focuses on design concepts for developing cooperative problem-solving systems. We use en route flight planning (selecting alternate routes or destinations due to unanticipated weather, traffic, malfunctions, etc.) as the context for studying the design of such systems. Researchers are currently exploring three questions in this test environment: (1) When interacting with a flight planning aid, how does the role of the pilot influence overall system performance; (2) Can the architecture for a cooperative planning system be built around Sacerdoti's (1983) concept of an abstraction hierarchy, where the pilot can interact with the system at many different levels of detail (but where the computer aid by default handles lower level details that the pilot has chosen not to deat with); and (3) Can graphical displays and direct manipulation of these displays provide perceptual enhancements (Larkin and Simon, 1987) of the pilot's problem-solving activities. Information is given in viewgraph form.

Smith, Philip J.↗
NASA NTRS1990

A testbed for the evaluation of computer aids for enroute flight path planning

A simulator study of the five airline flight crews engaged in various enroute planning activities has been conducted. Based on a cognitive task analysis of this data, a flight planning workstation has been developed on a Mac II controlling three color monitors. This workstation is being used to study design concepts to support the flight planning activities of dispatchers and flight crews in part-task simulators.

Smith, Philip J.↗
NASA NTRS1989

Frame of reference for electronic maps - The relevance of spatial cognition, mental rotation, and componential task analysis

Three experiments are reported that examine the difference between north-up and track-up maps for airborne navigation. The results of the first two experiments, conducted in a basic laboratory setting, identified the cost associated with mental rotation, when a north-up map is used. However, the data suggest that these costs are neither large nor consistent. The third experiment examined a range of tasks in a higher fidelity helicopter flight simulation, and associated the costs of north-up maps with a cognitive component related to orientation, and the costs of track-up maps with a cognitive component related to inconsistent landmark location. Different tasks are associated with different dependence on these components. The results are discussed in terms of their implications for map design, and for cognitive models of navigational processes.

Wickens, Christopher D.↗