Learning Mental Models of Human Cognitive Processing by Creating Cognitive Models

2015 ◽  
pp. 287-296 ◽  
Author(s):  
Kazuhisa Miwa ◽  
Nana Kanzaki ◽  
Hitoshi Terai ◽  
Kazuaki Kojima ◽  
Ryuichi Nakaike ◽  
...  
Keyword(s):  
Mental Models ◽  
Cognitive Processing ◽  
Cognitive Models

scholarly journals Know Your Cognitive Environment! Mental Models as Crucial Determinant of Offloading Preferences

2020 ◽  
pp. 001872082095686
Author(s):  
Patrick P. Weis ◽  
Eva Wiese
Keyword(s):  
Mental Models ◽  
Cognitive Processing ◽  
Strong Impact ◽  
Cognitive Tools ◽  
Smartphone Apps ◽  
Model Adjustment ◽  
Problem Solvers ◽  
Cognitive Environment ◽  
Human Problem ◽  
Specific Expertise

Objective Human problem solvers possess the ability to outsource parts of their mental processing onto cognitive “helpers” ( cognitive offloading). However, suboptimal decisions regarding which helper to recruit for which task occur frequently. Here, we investigate if understanding and adjusting a specific subcomponent of mental models—beliefs about task-specific expertise—regarding these helpers could provide a comparatively easy way to improve offloading decisions. Background Mental models afford the storage of beliefs about a helper that can be retrieved when needed. Methods Arithmetic and social problems were solved by 192 participants. Participants could, in addition to solving a task on their own, offload cognitive processing onto a human, a robot, or one of two smartphone apps. These helpers were introduced with either task-specific (e.g., stating that an app would use machine learning to “recognize faces” and “read emotions”) or task-unspecific (e.g., stating that an app was built for solving “complex cognitive tasks”) descriptions of their expertise. Results Providing task-specific expertise information heavily altered offloading behavior for apps but much less so for humans or robots. This suggests (1) strong preexisting mental models of human and robot helpers and (2) a strong impact of mental model adjustment for novel helpers like unfamiliar smartphone apps. Conclusion Creating and refining mental models is an easy approach to adjust offloading preferences and thus improve interactions with cognitive environments. Application To efficiently work in environments in which problem-solving includes consulting other people or cognitive tools (“helpers”), accurate mental models—especially regarding task-relevant expertise—are a crucial prerequisite.

A Cognitive Processing Account of Individual Differences in Novice Logo Programmers' Conceptualisation and Use of Recursion

1995 ◽  
Vol 13 (3) ◽  
pp. 211-226 ◽  
Author(s):  
Pamela Gibbons
Keyword(s):  
Individual Differences ◽  
Mental Models ◽  
Cognitive Processing ◽  
Mental Activity ◽  
Cognitive Profiles ◽  
Progressive Development ◽  
Relative Contribution ◽  
Processing Abilities ◽  
Logo Programming ◽  
Problem Solving Behavior

This article describes a study which investigated individual differences in the construction of mental models of recursion in Logo programming. It was hypothesized that differences in individuals' cognitive profiles would be reflected in differences in their computer programming problem solving behavior. The learning process was investigated from the perspective of Norman's mental models theory and employed diSessa's ontology regarding distributed, functional, and surrogate mental models. Analysis of the processes underlying mental model construction and of individual differences in these processes was based on the Luria model of brain function with particular regard to the relative contribution of simultaneous and successive cognitive processing abilities to conscious mental activity. Results generally confirmed predictions regarding the involvement of these abilities in the manifestation of individual differences in the stages of conscious mental activity contributing to the progressive development of mental models of recursion.

scholarly journals Know your cognitive environment! Mental models as crucial determinant of offloading preferences

2019 ◽  
Author(s):  
Patrick P. Weis ◽  
Eva Wiese
Keyword(s):  
Mental Models ◽  
Cognitive Processing ◽  
Strong Impact ◽  
Cognitive Tools ◽  
Smartphone Apps ◽  
Model Adjustment ◽  
Problem Solvers ◽  
Cognitive Environment ◽  
Human Problem ◽  
Specific Expertise

Objective: Human problem solvers possess the ability to outsource parts of their mental pro-cessing onto cognitive “helpers” (cognitive offloading). However, suboptimal decisions regarding which helper to recruit for which task occur frequently. Here, we investigate if understanding and adjusting a specific subcomponent of mental models –beliefs about task-specific expertise – regarding these helpers could provide a comparatively easy way to improve offloading decisions. Background: Mental models afford storage of beliefs about a helper that can be retrieved when needed. Methods: Arithmetic and social problems were solved by 192 participants. Participants could – in addition to solving a task on their own – offload cognitive processing onto a human, a robot, or one of two smartphone apps. These helpers were introduced with either task-specific (e.g., stating that an app would use machine learning to “recognize faces” and “read emotions”) or task-unspecific (e.g., stating that an app was built for solving “complex cognitive tasks”) descriptions of their expertise. Results: Providing task-specific expertise information heavily altered offloading behavior for apps but much less so for humans or robots. This suggests 1) strong pre-existing mental models of human and robot helpers and 2) a strong impact of mental model adjustment for novel helpers like unfamiliar smartphone apps. Conclusion: Creating and refining mental models is an easy approach to adjust offloading preferences and thus improve interactions with cognitive environments. Application: To efficiently work in environments in which problem solving includes consulting other people or cognitive tools (“helpers”), accurate mental models –especially regarding task-relevant expertise– are a crucial prerequisite.

The Role of Physical Affordances in Multifunctional Mobile Device Design

2010 ◽  
Vol 5 (4) ◽  
pp. 40-57 ◽  
Author(s):  
Sorin Adam Matei ◽  
Anthony Faiola ◽  
David J. Wheatley ◽  
Tim Altom
Keyword(s):  
Mobile Computing ◽  
Full Advantage ◽  
Mental Models ◽  
Mobile Device ◽  
Design Theory ◽  
Cognitive Models ◽  
Device Design ◽  
Mobile Media ◽  
New Device

As designers of mobile/media-rich devices continue to incorporate more features/functionality, the evolution of interfaces will become more complex. Meanwhile, users cognitive models must be aligned with new device capabilities and corresponding physical affordances. In this paper, the authors argue that based on HCI design theory, users approach objects by building mental models starting with physical appearance. Findings suggest that users who embrace a device’s multifunctionality are prevented from taking full advantage of an array of features due to an apparent cognitive constraint caused by a lack of physical controls. The authors submit that this problem stems from established mental models and past associated behaviors of both mobile and non-mobile interactive devices. In conclusion, users expressed a preference for immediate access and use of certain physical device controls within a multi-tasking environment, suggesting that as mobile computing becomes more prevalent, physical affordances in multifunctional devices may remain or increase in importance.

The Role of Physical Affordances in Multifunctional Mobile Device Design

2012 ◽  
pp. 306-324
Author(s):  
Sorin Adam Matei ◽  
Anthony Faiola ◽  
David J. Wheatley ◽  
Tim Altom
Keyword(s):  
Mobile Computing ◽  
Full Advantage ◽  
Mental Models ◽  
Mobile Device ◽  
Design Theory ◽  
Cognitive Models ◽  
Device Design ◽  
Mobile Media ◽  
New Device

As designers of mobile/media-rich devices continue to incorporate more features/functionality, the evolution of interfaces will become more complex. Meanwhile, users cognitive models must be aligned with new device capabilities and corresponding physical affordances. In this paper, the authors argue that based on HCI design theory, users approach objects by building mental models starting with physical appearance. Findings suggest that users who embrace a device’s multifunctionality are prevented from taking full advantage of an array of features due to an apparent cognitive constraint caused by a lack of physical controls. The authors submit that this problem stems from established mental models and past associated behaviors of both mobile and non-mobile interactive devices. In conclusion, users expressed a preference for immediate access and use of certain physical device controls within a multi-tasking environment, suggesting that as mobile computing becomes more prevalent, physical affordances in multifunctional devices may remain or increase in importance.

scholarly journals 4488 Neural Network of the Cognitive Model of Reading

2020 ◽  
Vol 4 (s1) ◽  
pp. 140-141
Author(s):  
Joseph Posner ◽  
Vivian Dickens ◽  
Andrew DeMarco ◽  
Sarah Snider ◽  
Peter Turkeltaub ◽  
...  
Keyword(s):  
Neural Networks ◽  
Functional Connectivity ◽  
Cognitive Processing ◽  
Word Reading ◽  
Cognitive Model ◽  
Network Connectivity ◽  
Cognitive Models ◽  
Neuronal Interactions ◽  
Language Areas ◽  
The Brain

OBJECTIVES/GOALS: A particularly debilitating consequence of stroke is alexia, an acquired impairment in reading. Cognitive models aim to characterize how information is processed based on behavioral data. If we can concurrently characterize how neural networks process that information, we can enhance the models to reflect the neuronal interactions that drive them. METHODS/STUDY POPULATION: There will be 10 unimpaired adult readers. Two functional localizer tasks, deigned to consistently activate robust language areas, identify the regions of interest that process the cognitive reading functions (orthography, phonology, semantics). Another task, designed for this experiment, analyses the reading-related functional-connectivity between these areas by presenting words classified along the attributes of frequency, concreteness, and regularity, which utilize specific cognitive routes, and a visual control. Connectivity is analyzed during word reading overall vs. a control condition to determine overall reading-related connectivity, and while reading words that have high vs. low attribute values, to determine if cognitive processing routes bias the neural reading network connectivity. RESULTS/ANTICIPATED RESULTS: The localizer analysis is expected to result in the activation of canonical reading areas. The degree of functional connectivity observed between these regions is expected to depend on the degree to which each cognitive route is utilized to read a given word. After orthographic, phonologic, and semantic areas have been identified, the connectivity analysis should show that there is high correlation between all three types of areas during reading compared to the control condition. Then the frequency, regularity, and concreteness of the words being read should alter the reliance on the pathways between these area types. This would support the hypothesized pattern of connectivity as predicted by the cognitive reading routes. Otherwise, it will show how the neural reading network differs from the cognitive model. DISCUSSION/SIGNIFICANCE OF IMPACT: The results will determine the relationship between the cognitive reading model and the neural reading network. Cognitive models show what processes occur in the brain, but neural networks show how these processes occur. By relating these components, we obtain a more complete view of reading in the brain, which can inform future alexia treatments.

scholarly journals Metaphors and the Degree of Conventionality in Translation of Prose Fiction: A Fraction of the Whole in Focus

Hikma ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 153-176
Author(s):  
Akbar Hesabi ◽  
Mobina Bakhshi ◽  
Pouria Sadrnia
Keyword(s):  
Cognitive Processing ◽  
Processing Time ◽  
Cognitive Models ◽  
The Other ◽  
Prose Fiction ◽  
Ordinary People ◽  
Identification Procedure ◽  
Conceptual Metaphors ◽  
Everyday Language ◽  
Persian Translation

The idea of metaphor classification is regarded as how felicitously they are entrenched in everyday language spoken by ordinary people. Metaphor conventionality can be regarded as a scale whose opposite ends constitute conventional and creative metaphors. Logic indicates that the majority of linguistic metaphors are well-worn and conventional rather than novel, since an excess of novel metaphors may remarkably bring about “communicative surprise” (Rabadán Álvarez, 1991) thus increase cognitive processing time and even hinder perceiving. Metaphorical creativity, as the other extreme of the scale of conventionality, can be looked at as the use of conceptual metaphors and/ or their linguistic manifestations that are creative or novel. This study seeks to scrutinize the scale of conventionality in the Persian translation of A Fraction of the Whole. MIP known as Metaphor Identification Procedure put forward by the Pragglejaz Group (2007) was employed in the study to identify metaphors. The findings reveal that, sometimes, the metaphors used in L1 are novel or creative, but the translator draws upon conventional or entrenched ones in L2, or vice versa. The aim is to show the translator's choice of metaphor in terms of a conventionality scale using some previous cognitive models in this regard.

The S-SH Confusion Test and the Effects of Frequency Lowering

2019 ◽  
Vol 62 (5) ◽  
pp. 1486-1505
Author(s):  
Joshua M. Alexander
Keyword(s):  
Cognitive Processing ◽  
Hearing Aids ◽  
Response Times ◽  
Nonlinear Frequency ◽  
Low Frequencies ◽  
Frequency Compression ◽  
Negative Side ◽  
Minimal Word ◽  
Low Pass ◽  
Negative Side Effects

PurposeFrequency lowering in hearing aids can cause listeners to perceive [s] as [ʃ]. The S-SH Confusion Test, which consists of 66 minimal word pairs spoken by 6 female talkers, was designed to help clinicians and researchers document these negative side effects. This study's purpose was to use this new test to evaluate the hypothesis that these confusions will increase to the extent that low frequencies are altered.MethodTwenty-one listeners with normal hearing were each tested on 7 conditions. Three were control conditions that were low-pass filtered at 3.3, 5.0, and 9.1 kHz. Four conditions were processed with nonlinear frequency compression (NFC): 2 had a 3.3-kHz maximum audible output frequency (MAOF), with a start frequency (SF) of 1.6 or 2.2 kHz; 2 had a 5.0-kHz MAOF, with an SF of 1.6 or 4.0 kHz. Listeners' responses were analyzed using concepts from signal detection theory. Response times were also collected as a measure of cognitive processing.ResultsOverall, [s] for [ʃ] confusions were minimal. As predicted, [ʃ] for [s] confusions increased for NFC conditions with a lower versus higher MAOF and with a lower versus higher SF. Response times for trials with correct [s] responses were shortest for the 9.1-kHz control and increased for the 5.0- and 3.3-kHz controls. NFC response times were also significantly longer as MAOF and SF decreased. The NFC condition with the highest MAOF and SF had statistically shorter response times than its control condition, indicating that, under some circumstances, NFC may ease cognitive processing.ConclusionsLarge differences in the S-SH Confusion Test across frequency-lowering conditions show that it can be used to document a major negative side effect associated with frequency lowering. Smaller but significant differences in response times for correct [s] trials indicate that NFC can help or hinder cognitive processing, depending on its settings.

Cognitive Processing of Miscommunication in Interactive Listening: An Evaluation of Listener Indecision and Cognitive Effort

2021 ◽  
pp. 1-17
Author(s):  
Jennifer M. Roche ◽  
Arkady Zgonnikov ◽  
Laura M. Morett
Keyword(s):  
Decision Making ◽  
Cognitive Processing ◽  
Language Processing ◽  
Cognitive Effort ◽  
Mouse Tracking ◽  
Computer Mouse ◽  
Decision Making Processes ◽  
Computer Mouse Tracking ◽  
Listening Task ◽  
Processing Effort

Purpose The purpose of the current study was to evaluate the social and cognitive underpinnings of miscommunication during an interactive listening task. Method An eye and computer mouse–tracking visual-world paradigm was used to investigate how a listener's cognitive effort (local and global) and decision-making processes were affected by a speaker's use of ambiguity that led to a miscommunication. Results Experiments 1 and 2 found that an environmental cue that made a miscommunication more or less salient impacted listener language processing effort (eye-tracking). Experiment 2 also indicated that listeners may develop different processing heuristics dependent upon the speaker's use of ambiguity that led to a miscommunication, exerting a significant impact on cognition and decision making. We also found that perspective-taking effort and decision-making complexity metrics (computer mouse tracking) predict language processing effort, indicating that instances of miscommunication produced cognitive consequences of indecision, thinking, and cognitive pull. Conclusion Together, these results indicate that listeners behave both reciprocally and adaptively when miscommunications occur, but the way they respond is largely dependent upon the type of ambiguity and how often it is produced by the speaker.

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