A Cognitive and Affective Neuroergonomics Approach to Game Design

Chamberland, Cindy; Grégoire, Mathieu; Michon, Pierre‐Emmanuel; Gagnon, Jean‐Christophe; Jackson, Philip L.; Tremblay, Sébastien

doi:10.1177/1541931215591301

Cited by 10 publications

(6 citation statements)

References 11 publications

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“…Such a research and development endeavour—that is, to develop intelligent systems that adapt their intervention to the cognitive and affective functional state of its user—is long-standing and requires measurements that capitalize on the online monitoring of multiple physiological sensors used as proxies to psychological dimensions (such as attention, stress, engagement and workload; see Durantin, Gagnon, Tremblay, & Dehais, 2014), and conceptually valid metrics capable of providing diagnostic information about the variability in the functional state of the operator (Gagnon, Lafond, Rivest, Couderc, & Tremblay, 2014). Promising results have identified physiological markers for attentional tunnelling (Dehais, Causse, & Tremblay, 2011) and the level of fun in video games (Chamberland et al, 2015), as well as methods to approximate mental models of decision makers (Lafond, Tremblay, & Banbury, 2013) that are the core of adaptive systems and individually-tailored cognitive assistants.…”

Section: Potential Solutions To Cognitive Limitationsmentioning

confidence: 99%

See no evil: Cognitive challenges of security surveillance and monitoring.

Hodgetts

Vachon

Chamberland

et al. 2017

Journal of Applied Research in Memory and Cognition

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RUNNING HEAD: Cognitive challenges of security surveillanceWord count of main text: 9,377Challenges of security surveillance 2 AbstractWhile the development of intelligent technologies in security surveillance can augment human capabilities, they do not replace the role of the operator entirely; as such, when developing surveillance support it is critical that limitations to the cognitive system are taken into account.The current article reviews the cognitive challenges associated with the task of a CCTV operator: visual search and cognitive/perceptual overload, attentional failures, vulnerability to distraction, and decision-making in a dynamically evolving environment. While not directly applied to surveillance issues, we suggest that the NSEEV (noticingsalience, effort, expectancy, value) model of attention could provide a useful theoretical basis for understanding the challenges faced in detection and monitoring tasks. Having identified cognitive limitations of the human operator, this review sets out a research agenda for further understanding the cognitive functioning related to surveillance, and highlights the need to consider the human element at the design stage when developing technological solutions to security surveillance. General Audience SummaryHigh expectations are placed upon surveillance technologies to protect infrastructure and public places. While technological systems can automate some aspects of the surveillance process, the human operator is still ultimately responsible for detection of suspicious activities and decisionmaking. Thus, the optimal design and development of new technology should not focus solely on the capabilities of the system itself, but on supporting the operator's cognitive vulnerabilities.Observations and interviews with closed-circuit television personnel have previously highlighted several challenges with the task and control room environmentincluding information overload, distraction, and long work shiftswhich we review in terms of the cognitive science literature.We set out a research agenda to investigate these issues in relation to a recent psychological theory of detection, and suggest ways in which progress can be made regarding training of operators, visualization and workspace design, and the use of intelligent and automated systems. Challenges of security surveillance 4 See no evil: Cognitive challenges of security surveillance and monitoring What Is Surveillance?Surveillance can take many forms, such as monitoring of crowds (e.g., riots, lifeguarding), a particular individual (shoplifter, terrorism suspect, drug dealer), objects (vehicles, unattended baggage), infrastructure (both public and remote; e.g., government buildings, railways, hydroelectric dams), or computer systems (cyber-attacks), as well as radarbased monitoring and risk assessment such as that required by air traffic controllers or military personnel. These supervisory monitoring tasks are all similar in that they involve concentration for long periods on a complex and dynamically evolving sit...

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Section: Potential Solutions To Cognitive Limitationsmentioning

confidence: 99%

See no evil: Cognitive challenges of security surveillance and monitoring.

Hodgetts

Vachon

Chamberland

et al. 2017

Journal of Applied Research in Memory and Cognition

Self Cite

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“…Not only can emotional content capture attention such as in the scream illustration, but the affective state of the learner can also alter perceived task load, and thus in turn learning (Chamberland et al, 2015). The affective mediation assumption of Moreno's Cognitive-Affective Theory of Learning with Media (CATLM; Moreno, 2006) posits that emotional factors may mediate the cognitive engagement of the learner, ultimately leading to an increase in learning.…”

Section: Emotionmentioning

confidence: 99%

Video Game Design for Learning to Learn

Pasqualotto

Parong

Green

et al. 2022

International Journal of Human–Computer Interaction

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Over the past 20 years, the proposal that immersive media, such as video games, can be leveraged to enhance brain plasticity and learning has been put to the test. This expanding literature highlights the extraordinary power of video games as a potential medium to train brain functions, but also the remaining challenges that must be addressed in developing games that truly deliver in terms of learning objectives. Such challenges include the need to: (1) Maintain high motivation given that learning typically requires long-term training regimens, (2) Ensure that the content or skills to be learned are indeed mastered in the face of many possible distractions, and (3) Produce knowledge transfer beyond the proximal learning objectives. Game design elements that have been proposed to support these learning objectives are reviewed, along with the underlying psychological constructs that these elements rest upon. A discussion of potential pitfalls is also included, as well as possible paths forward to consistently ensure impact.

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“…Finding a signature from those data sources would open the door to new possibilities in affective gaming by adapting content to the player's experience and reinforcing motivation for the game. This research is part of the FUNii project introduced in previous papers [25], where participants played off-the-shelf popular games from Ubisoft's Assassin's Creed series. Preliminary results were reported in [26], in which only a subset of the modalities (limited number of physiological measures) from a small set of 63 participants were leveraged.…”

Section: P R E -P R I N T V E R S I O Nmentioning

confidence: 99%

Predicting Video Game Players’ Fun from Physiological and Behavioural Data

Fortin-Côté

Chamberland

Parent

et al. 2018

Advances in Intelligent Systems and Computing

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Finding a physiological signature of a player's fun is a goal yet to be achieved in the field of adaptive gaming. The research presented in this paper tackles this issue by gathering physiological, behavioural and self-report data from over 200 participants who played off-the-shelf video games from the Assassin's Creed series within a minimally invasive laboratory environment. By leveraging machine learning techniques the prediction of the player's fun from its physiological and behavioural markers becomes a possibility. They provide clues as to which signals are the most relevant in establishing a physiological signature of the fun factor by providing an importance score based on the predictive power of each signal. Identifying those markers and their impact will prove crucial in the development of adaptive video games. Adataptive games that tailor their gameplay to the affective state of a player in order to deliver the optimal gaming experience. Indeed, an adaptive video game needs a continuous reading of the fun level to be able to respond to these changing fun levels in real time. While the predictive power of the presented classifier remains limited with a gain in the F1 score of 15% against random chance, it brings insight as to which physiological features might be the most informative for further analyses and discuss means by which low accuracy classification could still improve gaming experience.

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A Cognitive and Affective Neuroergonomics Approach to Game Design

Cited by 10 publications

References 11 publications

See no evil: Cognitive challenges of security surveillance and monitoring.

See no evil: Cognitive challenges of security surveillance and monitoring.

Video Game Design for Learning to Learn

Predicting Video Game Players’ Fun from Physiological and Behavioural Data

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