Relevant bibliographies by topics / Cognitive engineering

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cognitive engineering'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 December 2024

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Journal articles on the topic "Cognitive engineering"

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Blomberg, Olle. "Conceptions of Cognition for Cognitive Engineering." International Journal of Aviation Psychology 21, no. 1 (January 6, 2011): 85–104. http://dx.doi.org/10.1080/10508414.2011.537561.

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Wilson, Kyle M., William S. Helton, and Mark W. Wiggins. "Cognitive engineering." Wiley Interdisciplinary Reviews: Cognitive Science 4, no. 1 (October 18, 2012): 17–31. http://dx.doi.org/10.1002/wcs.1204.

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Larsson, Jan Eric. "Cognitive systems engineering." Automatica 33, no. 3 (March 1997): 478–79. http://dx.doi.org/10.1016/s0005-1098(97)84591-8.

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Noble, Douglas D. "Cockpit cognition: Education, the military and cognitive engineering." AI & Society 3, no. 4 (October 1989): 271–96. http://dx.doi.org/10.1007/bf01908619.

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Patterson, Robert Earl. "Cognitive engineering, cognitive augmentation, and information display." Journal of the Society for Information Display 20, no. 4 (2012): 208. http://dx.doi.org/10.1889/jsid20.4.208.

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MacIntyre, Hector. "A Design Model for Cognitive Engineering." International Journal of Technoethics 6, no. 1 (January 2015): 21–34. http://dx.doi.org/10.4018/ijt.2015010102.

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The author confronts some of the practical consequences of a technogenic account of cognitive agency. In the first section the author examines the commitment to a narrow locus of control shared by most extended theories of cognition, motivating a normative approach to cognitive design. The author then examines the recent appeal some normative theorists have made to responsibilist theories of knowledge to preserve their commitment. This gives the author an opportunity to explore factitious intellectual virtue as a way to defend these sorts of appeals. In the final section the author argues that factitious virtue has several benefits as a normative design model for the practice of cognitive engineering.
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Wiggins, Sterling. "Aligning Cognitive Engineering with Systems Engineering Practice to Address Cognition More Effectively." INSIGHT 12, no. 1 (April 2009): 23–25. http://dx.doi.org/10.1002/inst.200912123.

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Woods, David D., Jennifer C. Watts, John M. Graham, Daniel L. Kidwell, and Philip J. Smith. "Teaching Cognitive Systems Engineering." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 4 (October 1996): 259–63. http://dx.doi.org/10.1177/154193129604000425.

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Our motivation for this paper is to stimulate discussions within the human factors community about teaching Cognitive Engineering at the undergraduate level. For the last fourteen years, the Cognitive Systems Engineering Laboratory at the Ohio State University has offered an undergraduate course in Cognitive Engineering (multiple offerings per year to Industrial Engineering, Industrial Design, Computer Science and Psychology students). In this paper, we will draw from our teaching experiences and describe our framework for teaching Cognitive Engineering.
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Roth, Emilie, Ryan Kilgore, Catherine Burns, Robert Wears, John D. Lee, Greg Jamieson, and Ann Bisantz. "Cognitive Engineering Across Domains." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57, no. 1 (September 2013): 139–43. http://dx.doi.org/10.1177/1541931213571032.

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Cao, Shi, and Yili Liu. "An Integrated Cognitive Architecture for Cognitive Engineering Applications." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 56, no. 1 (September 2012): 323–27. http://dx.doi.org/10.1177/1071181312561075.

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Dissertations / Theses on the topic "Cognitive engineering"

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Ball, Linden John. "Cognitive processes in engineering design." Thesis, University of Plymouth, 1990. http://hdl.handle.net/10026.1/674.

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The central aim of the current research programme was to gain an understanding of the cognitive processes involved in engineering design. Since little previous empirical research has investigated this domain, two major exploratory studies were undertaken here. Study One monitored seven final-year students tackling extended design projects. Diary and interview data were used to construct detailed design behaviour graphs that decomposed activities into structured representations reflecting the goals and subgoals that were pursued. Study Two involved individual observation (using video) of six professional engineers "thinking-aloud" as they tackled a small-scale design problem in a laboratory setting. A taxonomic scheme was developed to classify all verbal protocol units and other observable behaviours. In interpreting the data extensive use was made of theoretical concepts (e. g. schemas and mental models) deriving from current research on human problem solving and thinking. Evidence indicated that the engineers studied had many similar methods of working which could be described at a high level of abstraction in terms of a common "design schema". A central aspect of this schema was a problem reduction strategy which was used to break down complex design problems into more manageable subproblems. The data additionally revealed certain differences in design strategy between engineers' solution modelling activities and also showed up tendencies toward error and suboptimal performance. In this latter respect a particularly common tendency was for designers to "satisfice", that is to focus exclusively on initial solution concepts rather than comparing alternatives with the aim of optimising choices. The general implications of the present findings are discussed in relation to both the training of design skills and the development of intelligent computer systems to aid or automate the design process. A final, smaller scale of experimental study is also reported which investigated the possibility of improving design processes via subtle interventions aimed at imposing greater structure on design behaviours.
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Mazzuto, Giovanni. "Fuzzy Cognitive Maps tools for Industrial Engineering." Doctoral thesis, Università Politecnica delle Marche, 2014. http://hdl.handle.net/11566/242871.

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La tesi "Fuzzy Cognitive Maps tools for Industrial Engineering", riguarda la valutazione dell'applicazione di uno strumento quale la Mappa Cognitiva Fuzzy nell'ambito industriale. Ciò risiede nel fatto che, il suddetto strumento, nato nel settore delle scienze sociale, considera rilevante l'aspetto sociale ed umano associato ad un particolare problema. In tutti i problemi di ottimizzazione di un processo, o di risoluzione di un particolare problema, è possibile scegliere macchine che lavorino di più e meglio, oppure compiere azioni di correzione svariate, ma è necessario considerare che, chi lavora con tali macchine o esegue tali azioni è un individuo, soggetto a paure, insicurezze e stati d'animo differenti. Tutti aspetti che ne possono modificare le azioni comportamentali e di conseguenza anche la produttività. Con le Mappe Cognitive Fuzzy, si vuole quindi far interagire i diversi operatori nel processo decisionale di un'azienda. Punto focale di tale metodo è il lavoro in gruppi di esperti per l'identificazione e risoluzione di un dato quesito. Gruppo di esperti che deve, necessariamente, coprire tutte le aree di competenza associate al problema in questione. Ogni individuo ha modalità di approccio ad un problema in relazioni alle sue mansioni nello stesso. È proprio questa la potenza di tale strumento. La diversa astrazione mentale di un problema, condivisa con il gruppo, permette di evidenziare connessioni causali tra fenomeni, finora sconosciuti o conosciuti da pochi. Nell'elaborato presentato, tale strumento è stato impiegato per la gestione di quattro problemi differenti: Gestione del farmaco, Selezione dei fornitori, Analisi degli infortuni e Analisi criticità. In tutte e quattro le situazioni analizzate, gli esperti hanno individuato alcuni aspetti positivi della tipologia di approccio. Il coinvolgimento di tutti i livelli di operatività nel processo di decision making ha infatti prodotto una maggiore attenzione da parte degli operatori alla vita delle aziende prese in considerazione.
The proposed thesis highlighted the potential of cognitive maps in their explanatory and reflective functions and their value in support of decision making within organizations in a phase of any consolidation of the cognitive distances involved. Intelligent agents use mental models and have various “internal” processes (physical, mental, emotional) as they interact with other agents. Encourage group members to produce their own learning and cognitive maps represent their mental models that can have multiple functions in the formation, whether or not assisted by the network. The considered areas of study are characterized by complexity requiring the investigation of new advanced methods for modelling and development of sophisticated systems. In order to improve the communication between the different actors in relation to the factors, it becomes important to recognize that the mental models that characterize them influence the way they perceive the world and, consequently, the risks. The information collected through this analysis have been used both as a basis for the definition of strategies of risk communication, and as a guide for the negotiation process aimed at reducing existing levels of conflict and, at improving the mitigation measures to be taken. On the basis of the results obtained, it becomes important to encourage administrators to increase the dissemination of information about previous responsibilities relating to risk management, and the future ones relating to possible measures to be undertaken in a specific area. The proposed PhD thesis analyses some cases of study. It has been described the application of the FCM in the suppliers' selection sector, specifically, in the new product development process; in the analysis of injury events on workplace, where the social aspect has a great relevance; it has been analysed in order to define a new ranking method, in an Italian company, for defining a criticality indicator for the equipment and a proper maintenance program and, finally, the FCM has been applied in the Healthcare sector and, specifically, it has been used to define the main causes affecting the drug administration risk.
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Cox, David Daniel. "Reverse engineering object recognition." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42042.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Page 95 blank.
Includes bibliographical references (p. 83-94).
Any given object in the world can cast an effectively infinite number of different images onto the retina, depending on its position relative to the viewer, the configuration of light sources, and the presence of other objects in the visual field. In spite of this, primates can robustly recognize a multitude of objects in a fraction of a second, with no apparent effort. The computational mechanisms underlying these amazing abilities are poorly understood. This thesis presents a collection of work from human psychophysics, monkey electrophysiology, and computational modelling in an effort to reverse-engineer the key computational components that enable this amazing ability in the primate visual system.
by David Daniel Cox.
Ph.D.
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Pallotta, Vincenzo. "Cognitive language engineering towards robust human-computer interaction /." Lausanne, 2002. http://library.epfl.ch/theses/?display=detail&nr=2630.

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Tan, Kok Keng. "Cognitive Systems Engineering as an Ontology for Design." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1269531460.

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Thoms, Joanne. "Human centric systems engineering." Thesis, University of Bath, 2009. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501636.

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This thesis is a study into an engineering technology that enables us to investigate the cognitive aspects of systems. Where previous techniques have focused on individual human roles undertaking defined tasks, this work develops engineering technologies to understand the cognitive contribution of the human team participating in the system and how the deployment of machine decision making technologies can influence and change the possible human contribution in that system. This work first develops a framework for understanding an individual’s cognitive focus and then an engineering process that enables us to model the individual human cognitive contribution to the system and by combining these models to create a rich system model. This model can then be used to consider the deployment of advanced machine technologies, to identify new human or machine interaction requirements that are focused on maintaining the effectiveness of the human contribution. It then operationalises and verifies these engineering techniques by applying them to two systems. The first study chosen took an existing system whose effectiveness had been changed by the deployment of machine automation which has known problems; the use of the framework enabled the prediction of these problems and the identification of potential solutions. The second study investigated an existing human system and the potential deployment of machine technology. This study used the framework to create models of the human cognitive focus and joined them together to form a rich system model, into which the deployment of the machine technology was considered. This resulted in the ability to identify the impact of the machine technology across the entire human team, enabling the identification of additional requirements to support the human cognition and to maintain human knowledge.
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Cardella, Monica E. "Engineering mathematics : an investigation of students' mathematical thinking from a cognitive engineering perspective /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/10692.

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Timmer, Peter Robin. "Expression of operator planning horizons : a cognitive engineering approach." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325012.

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Dowell, John. "Cognitive engineering and the rationalisation of the flight strip." Thesis, University College London (University of London), 1993. http://discovery.ucl.ac.uk/1350070/.

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Pinto, Nicolas. "Forward engineering object recognition : a scalable approach." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/62622.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2011.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 254-302).
The ease with which we recognize visual objects belies the computational difficulty of this feat. Despite the concerted efforts of both biological and computer vision research communities over the last forty years, human-level visual recognition remains an unsolved problem. The impact of a robust yet inexpensive solution would dramatically change computer science and neuroscience, unleashing a host of innovative applications in our modern society. In this thesis, we identify two operational barriers that have obstructed progress towards finding a solution { namely the lack of clear indicators and operational definitions of success, and the currently limited exploration of the staggeringly large hypothesis space of biologically- inspired solutions. To break down these barriers, we first establish new neuroscience-motivated baselines and new suites of fully-controlled benchmarks for object and face recognition. We also compare and contrast a variety of high-level visual systems, both artificial (state-of-the- art computer vision) and biological (humans). Then, we propose a simple high-throughput approach to undertake a systematic exploration of the biologically-inspired model class. By leveraging recent advances in massively parallel computing, we show that it is possible to generate a multitude of candidate models, screen them for desirable properties and discover robust solutions. Finally, we validate the scalability of our approach by showing its potential on large-scale real-world" applications. Taken together, this thesis represents a humble attempt towards an integrated approach to the problem of brain-inspired object recognition { spanning the engineering, specification, evaluation, and application of an interesting set of biologically-inspired ideas, driven and enabled by massively parallel technology. Even relatively early instantiations of this approach yield algorithms that achieve state-of-the-art performance in object recognition tasks and can generalize to other image domains. In addition, it offers insight into which computational ideas may be important for achieving this performance. Such insights can then be "fed back" into the design of new candidate models, constraining the search space and suggesting improvements, further guiding "evolutionary" progress. We hope that our results will point a new way forward, both in the creation of powerful yet simple computer vision systems and in providing insights into the computational underpinnings of biological vision.
by Nicolas Pinto.
Ph.D.
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Books on the topic "Cognitive engineering"

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McNeese, Michael, and Peter Forster, eds. Cognitive Systems Engineering. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155401.

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Mark, Pejtersen Annelise, and Goodstein L. P, eds. Cognitive systems engineering. New York: Wiley, 1994.

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Harris, Don, and Wen-Chin Li, eds. Engineering Psychology and Cognitive Ergonomics. Cognition and Design. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49183-3.

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Harris, Don, ed. Engineering Psychology and Cognitive Ergonomics. Understanding Human Cognition. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39360-0.

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Harris, Don, ed. Engineering Psychology and Cognitive Ergonomics: Cognition and Design. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58475-1.

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1952-, Woods David D., ed. Joint cognitive systems: Foundations of cognitive systems engineering. Boca Raton, FL: Taylor & Francis, 2005.

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Harris, Don, and Wen-Chin Li, eds. Engineering Psychology and Cognitive Ergonomics. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77932-0.

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Harris, Don, and Wen-Chin Li, eds. Engineering Psychology and Cognitive Ergonomics. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06086-1.

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Harris, Don, ed. Engineering Psychology and Cognitive Ergonomics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73331-7.

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Harris, Don, ed. Engineering Psychology and Cognitive Ergonomics. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22507-0.

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Book chapters on the topic "Cognitive engineering"

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Boy, Guy André. "Cognitive Engineering." In Orchestrating Human-Centered Design, 35–57. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4339-0_3.

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Shekhar, Shashi, and Hui Xiong. "Cognitive Engineering." In Encyclopedia of GIS, 97. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_142.

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O'Hare, David. "Cognitive Engineering." In Introduction to Safety Science, 179–202. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003038443-11.

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Holmqvist, Kenneth. "Conceptual Engineering." In Cognitive Semantics, 153. Amsterdam: John Benjamins Publishing Company, 1999. http://dx.doi.org/10.1075/pbns.55.08hol.

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Haun, Matthias. "Vorgehensmodell: Brainware Engineering." In Cognitive Computing, 129–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_3.

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Bukowski, Lech A. "Resilience Engineering." In Cognitive Dependability Engineering, 129–47. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003020752-11.

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Bukowski, Lech A. "Safety Engineering." In Cognitive Dependability Engineering, 99–114. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003020752-9.

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Bukowski, Lech A. "Security Engineering." In Cognitive Dependability Engineering, 115–28. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003020752-10.

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Bukowski, Lech A. "Systems Engineering*." In Cognitive Dependability Engineering, 28–42. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003020752-4.

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Bukowski, Lech A. "Reliability Engineering." In Cognitive Dependability Engineering, 79–98. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003020752-8.

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Conference papers on the topic "Cognitive engineering"

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Zhang, Dong, Zhiyuan Hu, Huijun Chen, Guangming Liu, Fangyuan Li, and Jinghui Lu. "Cognitive pitfalls of LLMs: a system for generating adversarial samples based on cognitive biases." In International Conference on Optics, Electronics, and Communication Engineering, edited by Yang Yue, 138. SPIE, 2024. http://dx.doi.org/10.1117/12.3049302.

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Calpin, Nicole, and Jessica Menold. "The Cognitive Costs of Design Tasks: The Evolution of Cognitive Load in Design and Its Relationship With Design Outcomes." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-89995.

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Abstract Problem solving can be a cognitively intensive undertaking; as design is characterized by ambiguity and unknowns, design problems in particular can be cognitively expensive. Few studies examine the evolution of cognitive load during the engineering design process and the linkages between sub-dimensions of cognitive load and design task outcomes. To address this issue, the goal of this work is to establish a relationship between cognitive load, design task, and design outcomes. Twenty participants were recruited to perform a design task where their mental workload was recorded at each stage of the design process. Their ideation and prototype outcomes were then evaluated to determine if there is a relationship between cognitive load, design task, and design outcomes. Results suggest that there is a significant difference in cognitive load experienced by the designer during each stage of the design process and while cognitive load is correlated with idea generation design outcomes, it may not be tied to prototyping design outcomes.
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Campbell, Susan G., J. Isaiah Harbison, Petra Bradley, and Lelyn D. Saner. "Cognitive engineering analysis training." In the 2014 Workshop. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2609876.2609879.

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Hilpert, Jonathan C., and Jennifer Hyppolite. "Cognitive pathways to engineering." In 2013 IEEE Frontiers in Education Conference (FIE). IEEE, 2013. http://dx.doi.org/10.1109/fie.2013.6685019.

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Wang, Yingxu. "Cognitive robotics and mathematical engineering." In 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2015. http://dx.doi.org/10.1109/icci-cc.2015.7259425.

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McDowell, Kaleb, and Harry J. Zywiol. "THE ARMY’S NEED FOR COGNITIVE ENGINEERING." In 2024 NDIA Michigan Chapter Ground Vehicle Systems Engineering and Technology Symposium. 2101 Wilson Blvd, Suite 700, Arlington, VA 22201, United States: National Defense Industrial Association, 2024. http://dx.doi.org/10.4271/2024-01-3108.

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<title>ABSTRACT</title> <p>Imagine Soldiers reacting to an unpredictable, dynamic, stressful situation on the battlefield. How those Soldiers think about the information presented to them by the system or other Soldiers during this situation – and how well they translate that into thinking into effective behaviors – is critical to how well they perform. Importantly, those thought processes (i.e., cognition) interact with both external (e.g., the size of the enemy force, weather) and internal (e.g., ability to communicate, personality, fatigue level) factors. The complicated nature of these interactions can have dramatic and unexpected consequences, as is seen in the analysis of military and industrial disasters, such as the shooting down of Iran Air flight 655, or the partial core meltdown on Three Mile Island. In both cases, decision makers needed to interact with equipment and personnel in a stressful, dynamic, and uncertain environment. Similarly, the complex and dynamic nature of the contemporary operating environment faced by the United States Army makes it clear that mission performance depends on systems that are engineered to ensure that the complex systems of people and technology (i.e., sociotechnical systems) can sustain high levels of cognitive performance needed for succeed. This session overview highlights cognitive engineering and illustrates how modeling and simulation can address different aspects of this important field.</p>
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Hallihan, Gregory M., Hyunmin Cheong, and L. H. Shu. "Confirmation and Cognitive Bias in Design Cognition." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71258.

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The desire to better understand design cognition has led to the application of literature from psychology to design research, e.g., in learning, analogical reasoning, and problem solving. Psychological research on cognitive heuristics and biases offers another relevant body of knowledge for application. Cognitive biases are inherent biases in human information processing, which can lead to suboptimal reasoning. Cognitive heuristics are unconscious rules utilized to enhance the efficiency of information processing and are possible antecedents of cognitive biases. This paper presents two studies that examined the role of confirmation bias, which is a tendency to seek and interpret evidence in order to confirm existing beliefs. The results of the first study, a protocol analysis involving novice designers engaged in a biomimetic design task, indicate that confirmation bias is present during concept generation and offer additional insights into the influence of confirmation bias in design. The results of the second study, a controlled experiment requiring participants to complete a concept evaluation task, suggest that decision matrices are effective tools to reduce confirmation bias during concept evaluation.
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Adams, Ray. "Cognitive science meets computing science: The future of cognitive systems and cognitive engineering." In Proceedings of the ITI 2009 31st International Conference on Information Technology Interfaces (ITI). IEEE, 2009. http://dx.doi.org/10.1109/iti.2009.5196041.

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Marques, Carla V. M., Carlo E. T. Oliveira, and Cibele Ribeiro C. Oliveira. "An engineering model of the cognitive mind." In 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2017. http://dx.doi.org/10.1109/icci-cc.2017.8109762.

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Ackers, Frederick, and Darush Davani. "Engineering a Cognitive Robotics Platform." In 2011 9th International Conference on Software Engineering Research, Management and Applications (SERA). IEEE, 2011. http://dx.doi.org/10.1109/sera.2011.47.

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Reports on the topic "Cognitive engineering"

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Cagan, Jonathan, and Kenneth Kotovsky. Cognitive Approaches to Automated Engineering Design. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada465633.

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Deal, Steven V. Embedding Cognitive Systems into Systems Engineering Practice. Fort Belvoir, VA: Defense Technical Information Center, December 2008. http://dx.doi.org/10.21236/ada501511.

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Caudell, Thomas P., David Eugene Peercy, Eva O. Caldera, and Wendy L. Shaneyfelt. A surety engineering framework to reduce cognitive systems risks. Office of Scientific and Technical Information (OSTI), December 2008. http://dx.doi.org/10.2172/952809.

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Cooke, Nancy J., and Steven M. Shope. Facility for Cognitive Engineering Research on Team Tasks (CERTT). Fort Belvoir, VA: Defense Technical Information Center, March 1998. http://dx.doi.org/10.21236/ada340948.

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Flach, John, and Golbert G. Kuperman. Victory by Design: War, Information, and Cognitive Systems Engineering. Fort Belvoir, VA: Defense Technical Information Center, February 1998. http://dx.doi.org/10.21236/ada358305.

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6

Cooke, Nancy J., Steven M. Shope, and Preston A. Kiekel. Shared-Knowledge and Team Performance: A Cognitive Engineering Approach to Measurement. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada387718.

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7

Ruff, Grigory, and Tatyana Sidorina. THE DEVELOPMENT MODEL OF ENGINEERING CREATIVITY IN STUDENTS OF MILITARY INSTITUTIONS. Science and Innovation Center Publishing House, December 2020. http://dx.doi.org/10.12731/model_of_engineering_creativity.

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The troops of the national guard of the Russian Federation are equipped with modern models of weapons, special equipment, Informatization tools, engineering weapons that have artificial intelligence in their composition are being developed, " etc., which causes an increase in the requirements for the quality of professional training of future officers. The increasing complexity of military professional activities, the avalanche-like increase in information, the need to develop the ability to quickly and accurately make and implement well-known and own engineering solutions in an unpredictable military environment demonstrates that the most important tasks of modern higher education are not only providing graduates with a system of fundamental and special knowledge and skills, but also developing their professional independence, and this led to the concept of engineering and creative potential in the list of professionally important qualities of an officer. To expedite a special mechanism system compact intense clarity through cognitive visualization of the educational material, thickening of educational knowledge through encoding, consolidation and structuring Principle of cognitive visualization stems from the psychological laws in accordance with which the efficiency of absorption is increased if visibility in training does not only illustrative, but also cognitive function, which leads to active inclusion, along with the left and right hemispheres of the student in the process of assimilation of information, based on the use of logical and semantic modeling, which contributes to the development of engineering and creative potential.
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8

Gualtieri, James, Scott Potter, William Elm, and Jack McKee. AIE CSEDS: Initial Cognitive Systems Engineering Design Specification (CSEDS) for the ACWA(Trademark) Integrated Environment (AIE). Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada427006.

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9

Morkun, Volodymyr S., Сергій Олексійович Семеріков, and Svitlana M. Hryshchenko. Use of the system Moodle in the formation of ecological competence of future engineers with the use of geoinformation technologies. Видавництво “CSITA”, 2016. http://dx.doi.org/10.31812/0564/718.

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At present the information and communication technologies in education can be a catalyst in solving important social problems connected with increasing the educational resources and services availability and quality, real and equal opportunities in getting education for citizens despite their residence, social status and income. One of the most important education tasks is to develop students’ active cognitive attitude to knowledge. Cognitive activity in universities is a necessary stage in preparing for further professional life. The solution of task of formation of ecological competence of mining profile engineer requires the reasonable selection of the means of information and communication technologies conducing formation of ecological competence. Pressing task is constructive and research approach to preparation of future engineers to performance of professional duties in order to make them capable to develop engineering projects independently and exercise control competently. The relevance of the material covered in the article, due to the need to ensure the effectiveness of the educational process in the preparation of the future Mining Engineers. We analyze the source with problems of formation of ecological competence. The article focuses mainly general-purpose computer system support learning Moodle, which allows you to organize individual and collective work of students to master the specialized course teaching material used in teaching special course "Environmental Geoinformatics" in the implementation of educational research.
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