The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Effects of adaptive task allocation on monitoring of automated systems

The effects of infants' age, body dimensions, and experience on the development of crawling was examined by observing 28 infants longitudinally, from children's first attempts at crawling until they began walking. Although most infants displayed multiple crawling postures en route to walking, development did not adhere to a strict progression of obligatory, discrete stages. In particular, 15 infants crawled on their bellies prior to crawling on hands and knees, but the other 13 infants skipped the belly-crawling period and proceeded directly to crawling on hands and knees. Duration of experience with earlier forms of crawling predicted the speed and efficiency of later, quite different forms of crawling. Most important, infants who had formerly belly crawled were more proficient crawling on hands and knees than infants who had skipped the belly-crawling period. Transfer could not be explained by differences in infants' age or body dimensions alone. Rather, experience using earlier crawling patterns may have exerted beneficial effects on hands-and-knees crawling by shoring up underlying constituents common to all forms of crawling postures.

Learning to crawl.

: A prior effort, State of Knowledge Relative to Intelligence Analysis, was initially motivated by the fact that seemingly little change had resulted from numerous studies of the intelligence community. Starting with Pearl Harbor, the U.S. intelligence community has often faced criticism for failing to predict or warn of future events. Though the criticisms have come from different groups, a certain commonality exists among the proposals for change in the intelligence community. The other noteworthy feature of these proposals is how little their content has changed over time. A thorough analysis of the intelligence literature was accomplished. This analysis provided an answer to the question of whether the existing literature on intelligence analysis contains the requisite knowledge to inform the development and application of both the mechanistic and cognitive activities to support doing intelligence analysis. A dominant finding was how little the practice of intelligence analysis had been informed by the findings in related scientific disciplines. The primary objective of this research effort was to understand the research findings in relevant scientific disciplines and to relate these findings to the practice of intelligence analysis. This research effort was based on the full text of over 5,800 documents consisting of nearly 172,000 pages. Our analysis of the current intelligence literature showed a continuation of previously observed trends. The number of publications dealing with intelligence analysis has decreased since 2007; in 2012 publication was at the level observed in 1996-1997. Also, we observed that the literature places less emphasis on the improvement of the quality of intelligence analysis. During the effort described in this report we conducted research syntheses for the topics of critical thinking, thinking dispositions, epistemological beliefs, practice based training, and various facets of cognition.

https://apps.dtic.mil/sti/pdfs/ADA595401.pdf

Advanced Analysis Cognition: Improving the Cognition of Intelligence Analysis

From the Book:

Focusing on human performance in organizational systems as cognitive engineering principles are applied, these eight chapters describe cognitive research at RISO from 1962-1979, the development of adaptability, the use of pathfinder networks, cognitive task analysis, human modeling technology, critical thinking in novel situations, the use of simulations for team research, and research paradigms. The authors are affiliated with various American universities, private companies, and the military. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Advances in Human Performance and Cognitive Engineering Research

This book integrates research into applications that extend from preschool brain development to the memory of adult educators. In layman's terms, it provides explanations and answers to questions such as: Why do children have to read fast before they can understand what they read? How do health, nutrition, and stimulation influence brain development? Why should students learn basic skills in their maternal language? Is there such a thing as an untrained teacher? What signs in a classroom show whether students are getting a quality education? How must information be presented in class so that students can retain it and use it? What training techniques are most likely to help staff put their learning into use? This book is intended for use by policymakers, donor agency staff, teacher trainers, supervisors, and inspectors, as well as university professors and students.

Efficient Learning for the Poor: Insights from the Frontier of Cognitive Neuroscience

AKADAM: Eliciting user knowledge to support participatory ergonomics

Within cooperative learning great emphasis is placed on the benefits of aetwo heads being greater than oneAE. However, further examination of this adage reveals that the value of learning groups can often be overstated and taken for granted for different types of problems. When groups are required to solve ill-defined and complex problems under real world constraints, different socio-cognitive factors (e.g., metacognition, collective induction, and perceptual experience) are expected to determine the extent to which cooperative learning is successful. Another facet of cooperative learning, the extent to which groups enhance the use of knowledge from one situation to another, is frequently ignored in determining the value of cooperative learning. This paper examines the role and functions of cooperative learning groups in contrast to individual learning conditions, for both an acquisition and transfer task. Results for acquisition show groups perform better overall than individuals by solving more elements of the Jasper problem as measured by their overall score in problem space analysis. For transfer, individuals do better overall than groups in the overall amount of problem elements transferred from Jasper. This paradox is explained by closer examination of the data analysis. Groups spend more time engaged with each other in metacognitive activities (during acquisition) whereas individuals spend more time using the computer to explore details of the perceptually based Jasper macrocontext. Hence, results show that individuals increase their perceptual learning during acquisition whereas groups enhance their metacognitive strategies. These investments show different pay-offs for the transfer problem. Individuals transfer more overall problem elements (as they explored the context more) but problem solvers who had the benefit of metacognition in a learning group did better at solving the most complex elements of the transfer problem. Results also show that collective induction groups (ones that freely share) – in comparison to groups composed of dominant members – enhance certain kinds of transfer problem solving (e.g., generating subgoals). The results are portrayed as the active interplay of socio-cognitive elements that impact the outcomes (and therein success) of cooperative learning.

Socio-cognitive factors in the acquisition and transfer of knowledge

: This report documents the creation, development, and evaluation of an advanced knowledge and design acquisition methodology. The methodology develops user requirements along three separate yet integrated perspectives: (1) intuitive/experiential knowledge, (2) structural/functional models, and (3) knowledge as design. Three specific tools to implement perspectives; concept mapping, IDEF modeling, and design storyboarding are discussed. An integrative structure is proposed as an interactive way to let users and other design team members assimilate, deepen, and combine knowledge for the purpose of developing intelligent systems and human machine interface designs. Hence, system designs are directly derived from 'user engineering' and from user conceptualization and participation. The project applies this methodology to the Pilot's Associate program which resolves complex knowledge acquisition/representation requirements. Results indicate that pilots could successfully reveal their own comprehension of an air to ground mission and transform this conceptual knowledge into actual designs for an intelligent pilot vehicle interface. The ability of this methodology to elicit multiple knowledge perspectives and to preserve them in an integrated form (which facilitates interaction with new domain experts in the future) creates an effective means for all phases of the system design.

An Advanced Knowledge and Design Acquisition Methodology: Application for the Pilot's Associate

The ultimate concern of cognitive engineering is how complex sociotechnical systems might be designed so that humans can work within them and control them safely and effectively. Because of this, large amounts of observational data analysis and knowledge elicitation are incorporated in cognitive engineering. At many points, these two methodologies coalesce. In this paper, we describe two complementary cognitive engineering software tools—MacSHAPA and COGENT—that are being developed alongside each other. MacSHAPA is designed for observational data analysis, and COGENT is designed for knowledge elicitation and cognitive engineering, but both sup-port requirements gathering. We first outline current trends in cognitive engineering that have given rise to the need for tools like MacSHAPA and COGENT. We then describe the two tools in more detail, and point to their similarities and differences. Finally, we show how the two tools are complementary, and how they can be used together in engineering psychology research.

/pdf/handling-complex-real-world-data-with-two-cognitive-1l2vk1wo7y.pdf

Handling complex real-world data with two cognitive engineering tools: COGENT and MacSHAPA

Cognitive field studies are useful in understanding human cognitive activities in naturalistic settings and are essential in effectively designing human-system integration in complex systems. Several methodological challenges confront a researcher conducting the study of cognitive systems in context. Decisions need to be made regarding the field research experimental world, knowledge acquisition methods, representational schemes, and evaluative procedures. These decisions involve tradeoffs based on goals of the research, domain characteristics, and task constraints. This article proposes an integrative framework for cognitive field research, reviews several studies in the literature, and highlights decision alternatives in cognitive field research in the context of the proposed framework. We also apply the framework in the case study of fighter aircraft systems and briefly outline methodological issues encountered in the research.

Michael D. McNeese

Papers

AKADAM: Eliciting user knowledge to support participatory ergonomics

Socio-cognitive factors in the acquisition and transfer of knowledge

An Advanced Knowledge and Design Acquisition Methodology: Application for the Pilot's Associate

Handling complex real-world data with two cognitive engineering tools: COGENT and MacSHAPA

A Framework for Cognitive Field Studies