Affect-Aware Adaptive Tutoring Based on Human–Automation Etiquette Strategies

Objective: We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human–automation etiquette strategies. Background: Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students’ motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Method: Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. Results: The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. Conclusion: If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn

Multiple two-state classifier output fusion system and method

A system and method for providing more than two levels of classification distinction of a user state are provided. The first and second general states of a user are sensed. The first general state is classified as either a first state or a second state, and the second general state is classified as either a third state or a fourth state. The user state of the user is then classified as one of at least three different classification states

Development of Design Requirements for a Cognitive Assistant in Space Missions Beyond Low Earth Orbit

This study describes the development of requirements for a cognitive assistant (CA) for use onboard a space vehicle/station. For missions beyond low Earth orbit (LEO), delayed communication will limit mission control’s ability to support the space crew in real time. During off-nominal situations, where no procedures have been developed prior to missions, crews must develop responses in real time and may increasingly rely on automation. A systematic approach was used to model the domain knowledge of the collaborative decision-making process of current space operations, extrapolate to missions beyond LEO, and develop the design requirements for a CA. Document analysis and interviews were conducted to create an abstraction hierarchy and a decision-action diagram of the cognitive functions currently performed by space crew, mission control, and onboard automation. These domain models were extrapolated to missions beyond LEO by identifying the breakpoints where current decision-making processes would break down due to increased communication delay between mission control and the space crew. Design requirements were identified for future CA systems that offer real-time decision-making support to mitigate the negative effect of limited support in off-nominal situations. The approach developed for this research can be generalized to identify the design requirements for future support systems in domains beyond space operations

A User-Centered Approach to User-Building Interactions

Providing a task-representative user interface for building operations and control puts the user in charge of their health, safety, and well-being and improves task performance. Enabling users control of building conditions and operations often results in poor overall building performance, such as increased energy usage due to lighting a non-occupied room. As a result, building designers limit the control users have in the spaces they occupy by implementing lighting schedules, for example. However, research has indicated an improved user experience results when users regulate their environment. This conflict produces significant challenges in building interaction design regarding the allocation of control in user-building interactions. An approach is being developed to align user-building interaction design with the building’s purpose – to support users’ tasks. Rather than multiple operation specific interfaces, providing users a unified task-representative interface links building operations, users, and tasks. The result is a more informative interaction between the user and building operations and a more effective, efficient, and enhanced task experience

Cognitive aircraft hazard advisory system (CAHAS)

Integrated surveillance systems and methods for processing multiple sensor inputs and determining a best route for avoiding multiple hazards. An example method performed on a first aircraft includes generating a plurality of routes for avoiding a previously determined alert from a first advisory system. Then, probability of success information is generated at other advisory systems for each of the plurality of routes. The best route of the plurality of routes is determined based on the generated probabilities and output to the flight crew or other aircraft. The probability of success information includes a previously defined uncertainty value. The uncertainty value corresponds to quality of data provided to or provided by the respective advisory system

Evaluating Human–Automation Etiquette Strategies to Mitigate User Frustration and Improve Learning in Affect-Aware Tutoring

Human–automation etiquette applies human–human etiquette conventions to human–computer interaction (HCI). The research described in this paper investigates how to mitigate user frustration and support student learning through changes in the style in which a computer tutor interacts with a learner. Frustration can significantly impact the quality of learning in tutoring. This study examined an approach to mitigate frustration through the use of different etiquette strategies to change the amount of imposition feedback placed on the learner. An experiment was conducted to explore how varying the interaction style of system feedback impacted aspects of the learning process. System feedback was varied through different etiquette strategies. Participants solved mathematics problems under different frustration conditions with feedback given in different etiquette styles. Changing etiquette strategies from one math problem to the next led to changes in motivation, confidence satisfaction, and performance. The most effective etiquette strategies changed depending on if the user was frustrated or not. This work aims to provide mechanisms to support the promotion of individualized learning in the context of high level math instruction by basing affect-aware adaptive tutoring system design on varying etiquette strategies

Comparing Systems Engineering and Project Success in Commercial-focused versus Government-focused Projects

This work looks at the relationship between systems engineering and project success industry lead in aerospace, agriculture, defense & security, energy and related areas. The projects included both commercial-focused and government-focused efforts. Differences were found in both the overall risk levels and the measures of success for the two groups. In addition, government-focused projects showed a notably larger number of significant relationships between system engineering processes and project success than the commercial-focused projects. The research notes that further investigation is warranted, in particular looking at individual industry sectors, exploring the impact of team dispersion, and developing a better understanding of interrelationships between the systems engineering processes. This type of analysis will help further our understanding of both the art and science of systems engineering

Mixed-initiative transfer of datalink-based information

A system and method are provided for transferring datalink-based information into an aircraft flight management system. When a datalink message is received in an aircraft, it is parsed into individual information elements. The operational impact of the received datalink message on the aircraft is determined from the individual information elements. A method of supplying pilot feedback regarding the received datalink message is determined from the determined operational impact. The pilot feedback regarding the received datalink message is supplied using the determined method. At least selected portions of the individual information elements are selectively transferred into the aircraft flight management system (FMS)

Situation aftermath management system and method

A system and method for assisting flight crew recovery in the aftermath of an unexpected event is provided. A processor is used to detect that an unexpected event has occurred in an aircraft and, in response to detecting that the unexpected event has occurred, state data are stored in memory. The processor is also used to detect that the unexpected event has been resolved and, in response to detecting that the unexpected event has been resolved, the processor retrieves the state data from the memory, generates an aftermath plan that includes prompts to guide the flight crew to complete the aftermath plan, and continuously updates the aftermath plan until the aftermath plan is completed

Virtual Operator Models for Off-highway Machine Virtual Prototyping

Increasing demands on the world’s resources require the design of off-highway machines that provide greater functionality and productivity along with greater efficiency. Model-based or virtual design provides a means for achieving these design improvements with reduced time and costs. However, virtual design is often limited by the fidelity with which human operators are modeled. A greater understanding of how highly skilled operators obtain high machine performance and productivity can inform machine development and advance agricultural and construction machine automation technology. This research investigated how machine operator expertise, strategies, and decision-making can be integrated into operator models that simulate authentic human behavior in construction machine operations. The initial effort of this work was to develop a virtual operator model (VOM) through a combination of human factors and physical system modeling techniques. Operator interviews were conducted to build a framework of tasks, strategies, and cues commonly used while controlling an excavator through repeated work cycles. A closed loop simulation demonstrated that a VOM could simulate the trenching work cycle and enable closed-loop virtual equipment operation simulation. Advancing the state of the art in operator modeling requires models that can adapt. Approaches to enable a generic virtual operator model to adapt to changes in the environment based on the operator’s actions were investigated. The closed loop simulation performed successfully when using the VOM, the vehicle model, and an environment model which represented how the VOM adapted during a complete trenching operation