A5072465067- Human-Automation Interaction and Safety
- Cognitive Science and Mapping
- Sleep and Work-Related Fatigue
- Intelligent Tutoring Systems and Adaptive Learning
- AI-based Problem Solving and Planning
- Cardiac Arrest and Resuscitation
- Complex Systems and Decision Making
- Innovative Teaching and Learning Methods
- Spatial Cognition and Navigation
- Online Learning and Analytics
- Sleep and related disorders
- Decision-Making and Behavioral Economics
- Simulation-Based Education in Healthcare
- Cognitive Computing and Networks
- Bayesian Modeling and Causal Inference
- Visual and Cognitive Learning Processes
- Child and Animal Learning Development
- Ergonomics and Musculoskeletal Disorders
- Software System Performance and Reliability
- Time Series Analysis and Forecasting
- Aerospace and Aviation Technology
- Forecasting Techniques and Applications
- Neural Networks and Applications
- Healthcare Technology and Patient Monitoring
- Air Traffic Management and Optimization
Florida Institute for Human and Machine Cognition
2024
Clinical Solutions
2022
Wright-Patterson Air Force Base
2012-2021
National League for Nursing
2021
United States Air Force Research Laboratory
2009-2020
Laerdal (Norway)
2020
Princeton University
2018
University of Strathclyde
2016
University of Michigan
2016
Indiana University
2008
This article presents a new research area called interactive task learning (ITL), in which an agent actively tries to learn not just how perform better but the actual definition of through natural interaction with human instructor while attempting task. The authors provide analysis desiderata for ITL systems, review related work, and discussion possible application areas systems.
A long history of research has revealed many neurophysiological changes and concomitant behavioral impacts sleep deprivation, restriction, circadian rhythms. Little research, however, been conducted in the area computational cognitive modeling to understand information processing mechanisms through which neurobehavioral factors operate produce degradations human performance. Our approach understanding this relationship is link predictions overall functioning, or alertness, from existing...
Aim Although evidence supports brief, frequent CPR training, optimal training intervals have not been established. The purpose of this study was to compare nursing students' skills (compressions and ventilations) with 4 different spaced intervals: daily, weekly, monthly, quarterly, each for times in a row. Methods Participants were students (n = 475) the first year their prelicensure program 10 schools across United States. They randomly assigned into schools. Students trained on Laerdal...
Incorporating dynamic realistic human behaviors in population-scale computational models has been challenging. While some efforts have leveraged behavioral theories from social science, validated specifically applicable to Agent-based modeling remain limited. Existing approaches lack a comprehensive framework model the situated, adaptive nature of cognition and choice. To address these challenges, this paper proposes novel framework, Psychologically-Valid Generative Agents. These agents...
The spacing effect is one of the most widely replicated results in experimental psychology: Separating practice repetitions by a delay slows learning but enhances retention. current study tested suitability underlying, explanatory mechanism three computational models effect. relearning forgotten material was measured, as differ their predictions how initial conditions should affect relearning. Participants learned Japanese-English paired associates presented massed or spaced manner during an...
The study examined how the spacing of training during initial acquisition cardiopulmonary resuscitation (CPR) skill affects longer-term retention and sustainment these skills.This was a multiphased, longitudinal study. Nursing students were randomly assigned to 2 conditions in which they completed 4 consecutive CPR sessions spaced by shorter (1 or 7 days) longer (30 90 intervals. Students additionally randomized refresh skills for 1 year every 3 months, 6 at personalized interval prescribed...
A good fit of model predictions to empirical data are often used as an argument for validity. However, if the is flexible enough a large proportion potential outcomes, finding becomes less meaningful. We propose method estimating outcomes that can fit: Model Flexibility Analysis (MFA). MFA aids evaluation by providing metric gauging persuasiveness given fit. demonstrate be more informative than merely discounting number free parameters in model, and show how does not necessarily correlate...
Objective: The effects of fatigue on multiple-task performance were explored through computational cognitive modeling. Background: Fatigue typically has a negative impact human performance. Biomathematical models exist that characterize the dynamics alertness, but link between alertness and in situ specific tasks is tenuous. Cognitive architectures offer principled means establishing link. Method: We implemented mechanisms for fatigue, which produce microlapses processing, into an existing...
This study investigated the effects of practice opportunities and learner control on short- long-term learning from a computer-based introductory statistics curriculum. In all, 380 participants were assigned to one five conditions. The first four conditions differed in terms number problems solve per problem set. fifth condition allowed learners choose amount practice. A subset (n = 120) original returned for testing following six-month interval. Overall, fixed-practice showed gains that...
When playing games of strategic interaction, such as iterated Prisoner's Dilemma and Chicken Game, people exhibit specific within-game learning (e.g., a game's optimal outcome) well transfer between outcome occurring at higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate effects. Recently, computational cognitive model using novel mechanism has been shown account for human behavior in both games, including games....
The cognitive modeling and artificial general intelligence research communities may reap greater scientific return on investmentsmay achieve an improved understanding of architectures modelsif there is more emphasis systematic sensitivity necessity analyses during model development, evaluation, comparison.We demonstrate this methodological prescription with two the models submitted for Dynamic Stocks Flows (DSF) Model Comparison Challenge, exploring complex interactions among architectural...