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Using minimal human-computer interfaces for studying the interactive development of social awareness.

ABSTRACT: According to the enactive approach to cognitive science, perception is essentially a skillful engagement with the world. Learning how to engage via a human-computer interface (HCI) can therefore be taken as an instance of developing a new mode of experiencing. Similarly, social perception is theorized to be primarily constituted by skillful engagement between people, which implies that it is possible to investigate the origins and development of social awareness using multi-user HCIs. We analyzed the trial-by-trial objective and subjective changes in sociality that took place during a perceptual crossing experiment in which embodied interaction between pairs of adults was mediated over a minimalist haptic HCI. Since that study required participants to implicitly relearn how to mutually engage so as to perceive each other's presence, we hypothesized that there would be indications that the initial developmental stages of social awareness were recapitulated. Preliminary results reveal that, despite the lack of explicit feedback about task performance, there was a trend for the clarity of social awareness to increase over time. We discuss the methodological challenges involved in evaluating whether this trend was characterized by distinct developmental stages of objective behavior and subjective experience.

SUBMITTER: Froese T

PROVIDER: S-EPMC4176033 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Using minimal human-computer interfaces for studying the interactive development of social awareness.

Froese Tom T Iizuka Hiroyuki H Ikegami Takashi T

Frontiers in psychology 20140926

According to the enactive approach to cognitive science, perception is essentially a skillful engagement with the world. Learning how to engage via a human-computer interface (HCI) can therefore be taken as an instance of developing a new mode of experiencing. Similarly, social perception is theorized to be primarily constituted by skillful engagement between people, which implies that it is possible to investigate the origins and development of social awareness using multi-user HCIs. We analyze ...[more]

PMID: 25309490

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Project description:BACKGROUND:Individuals with severe neurological disabilities but preserved cognition, including children, are often precluded from connecting with their environments. Brain computer interfaces (BCI) are a potential solution where advancing technologies create new clinical opportunities. We evaluated clinician awareness as a modifiable barrier to progress and identified eligible populations. METHODS:We executed a national, population-based, cross-sectional survey of physician specialists caring for persons with severe disability. An evidence- and experience-based survey had three themes: clinician BCI knowledge, eligible populations, and potential impact. A BCI knowledge index was created and scored. Canadian adult and pediatric neurologists, physiatrists and a subset of developmental pediatricians were contacted. Secure, web-based software administered the survey via email with online data collection. RESULTS:Of 922 valid emails (664 neurologists, 253 physiatrists), 137 (15%) responded. One third estimated that ≥10% of their patients had severe neurological disability with cognitive capacity. BCI knowledge scores were low with > 40% identifying as less than "vaguely aware" and only 15% as "somewhat familiar" or better. Knowledge did not differ across specialties. Only 6 physicians (4%) had patients using BCI. Communication and wheelchair control rated highest for potentially improving quality of life. Most (81%) felt BCI had high potential to improve quality of life. Estimates suggested that > 13,000 Canadians (36 M population) might benefit from BCI technologies. CONCLUSIONS:Despite high potential and thousands of patients who might benefit, BCI awareness among clinicians caring for disabled persons is poor. Further, functional priorities for BCI applications may differ between medical professionals and potential BCI users, perhaps reflecting that clinicians possess a less accurate understanding of the desires and needs of potential end-users. Improving knowledge and engaging both clinicians and patients could facilitate BCI program development to improve patient outcomes.

Project description:Immersive software tools are virtual environments designed to give their users an augmented view of real-world data and ways of manipulating that data. As virtual environments, every action users make while interacting with these tools can be carefully logged, as can the state of the software and the information it presents to the user, giving these actions context. This data provides a high-resolution lens through which dynamic cognitive and behavioral processes can be viewed. In this report, we describe new methods for the analysis and interpretation of such data, utilizing a novel implementation of the Beta Process Hidden Markov Model (BP-HMM) for analysis of software activity logs. We further report the results of a preliminary study designed to establish the validity of our modeling approach. A group of 20 participants were asked to play a simple computer game, instrumented to log every interaction with the interface. Participants had no previous experience with the game's functionality or rules, so the activity logs collected during their naïve interactions capture patterns of exploratory behavior and skill acquisition as they attempted to learn the rules of the game. Pre- and post-task questionnaires probed for self-reported styles of problem solving, as well as task engagement, difficulty, and workload. We jointly modeled the activity log sequences collected from all participants using the BP-HMM approach, identifying a global library of activity patterns representative of the collective behavior of all the participants. Analyses show systematic relationships between both pre- and post-task questionnaires, self-reported approaches to analytic problem solving, and metrics extracted from the BP-HMM decomposition. Overall, we find that this novel approach to decomposing unstructured behavioral data within software environments provides a sensible means for understanding how users learn to integrate software functionality for strategic task pursuit.

Dataset Information

Using minimal human-computer interfaces for studying the interactive development of social awareness.

Publications

Using minimal human-computer interfaces for studying the interactive development of social awareness.

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