7,676 research outputs found
Combining computer game-based behavioural experiments with high-density EEG and infrared gaze tracking
Rigorous, quantitative examination of therapeutic techniques anecdotally reported to have been successful in people with autism who lack communicative speech will help guide basic science toward a more complete characterisation of the cognitive profile in this underserved subpopulation, and show the extent to which theories and results developed with the high-functioning subpopulation may apply. This study examines a novel therapy, the "Rapid Prompting Method" (RPM). RPM is a parent-developed communicative and educational therapy for persons with autism who do not speak or who have difficulty using speech communicatively.The technique aims to develop a means of interactive learning by pointing amongst multiple-choice options presented at different locations in space, with the aid of sensory "prompts" which evoke a response without cueing any specific response option. The prompts are meant to draw and to maintain attention to the communicative taskâmaking the communicative and educational content coincident with the most physically salient, attention-capturing stimulus â and to extinguish the sensoryâmotor preoccupations with which the prompts compete.ideo-recorded RPM sessions with nine autistic children ages 8â14years who lacked functional communicative speech were coded for behaviours of interest
What does not happen: quantifying embodied engagement using NIMI and self-adaptors
Previous research into the quantification of embodied intellectual and emotional engagement using non-verbal movement parameters has not yielded consistent results across different studies. Our research introduces NIMI (Non-Instrumental Movement Inhibition) as an alternative parameter. We propose that the absence of certain types of possible movements can be a more holistic proxy for cognitive engagement with media (in seated persons) than searching for the presence of other movements. Rather than analyzing total movement as an indicator of engagement, our research team distinguishes between instrumental movements (i.e. physical movement serving a direct purpose in the given situation) and non-instrumental movements, and investigates them in the context of the narrative rhythm of the stimulus. We demonstrate that NIMI occurs by showing viewersâ movement levels entrained (i.e. synchronised) to the repeating narrative rhythm of a timed computer-presented quiz. Finally, we discuss the role of objective metrics of engagement in future context-aware analysis of human behaviour in audience research, interactive media and responsive system and interface design
Monitoring and improving performance in human-computer interaction
Monitoring an individual's performance in a task, especially in the workplace context, is becoming an increasingly interesting and controversial topic in a time in which workers are expected to produce more, better and faster. The tension caused by this competitiveness, together with the pressure of monitoring, may not work in favour of the organization's objectives. In this paper, we present an innovative approach on the problem of performance management. We build on the fact that computers are nowadays used as major work tools in many workplaces to devise a non-invasive method for distributed performance monitoring based on the observation of the worker's interaction with the computer. We then look at musical selection both as a pleasant and as an effective method for improving performance in the workplace. The proposed approach will allow team coordinators to assess and manage their co-workers' performance continuously and in real-time, using a distributed service-based architecture. Copyright (c) 2015 John Wiley & Sons, Ltd.This work is part-funded by European Regional Development Fund (ERDF) through the COMPETE Programme (operational programme for competitiveness) and by the national funds through the Fundacao para a Ciencia e a Tecnologia (FCT; Portuguese Foundation for Science and Technology) within projects FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012) and project PEst-OE/EEI/UI0752/2014.info:eu-repo/semantics/publishedVersio
Emotional and attitudinal responses to remote versus co-located usability testing
Current usability testing is often conducted via face-to-face interactions. This method can be costly, both in terms of timelines and budget. However, remote usability testing has been shown to be a viable alternative, in that performance scores have been shown to be quite similar to face-to-face methods. Although performance appears similar, remote usability testing may present challenges that threaten the validity and reliability of usability testing results. Rather than focusing on the performance of users in remote versus co-located conditions, the proposed study investigates the emotional and attitudinal responses of users engaged in software usability tests. The purpose of this study was to compare usersâ anxiety and satisfaction with communication in remote and face-to-face usability tests. It was hypothesized that participants in the remote condition would exhibit a lower level of anxiety and be less satisfied with the communication method. Multiple usability tasks were administered and measures were recorded at three time intervals. Responses on the Social Anxiety Thoughts (SAT) questionnaire and the Communication Satisfaction Inventory (CSI) were collected. Although there were no significant differences between the groups in terms of anxiety and communication satisfaction, methodological limitations may have prevented the detection of differences and additional research is required to explore the strengths and weaknesses of remote usability testing
A framework for Adaptive Capability Profiling
This thesis documents research providing improvements in the field of accessibility modelling, which will be of particular interest as computing becomes increasingly ubiquitous. It is argued that a new approach is required that takes into account the dynamic relationship between users, their technology (both hardware and software) and any additional Assistive Technologies (ATs) that may be required. In addition, the approach must find a balance between fidelity and transportability.
A theoretical framework has been developed that is able to represent both users and technology in symmetrical (hierarchical) recursive profiles, using a vocabulary that moves from device-specific to device-agnostic capabilities. The research has resulted in the development of a single unified solution that is able to functionally assess the accessibility of interactions through the use of pattern matching between graph-based profiles. A self-efficacy study was also conducted, which identified the inability of older people to provide the data necessary to drive a system based on the framework. Subsequently, the ethical considerations surrounding the use of automated data collection agents were discussed and a mechanism for representing contextual information was also included. Finally, real user data was collected and processed using a practically implemented prototype to provide an evaluation of
the approach.
The thesis represents a contribution through its ability to both: (1) accommodate the collection of data from a wide variety of sources, and (2) support accessibility assessments at varying levels of abstraction in order to identify if/where assistance may be necessary. The resulting approach has contributed to a work-package of the Sus-IT project, under the New Dynamics of Ageing (NDA) programme of research in the UK. It has also been presented to a W3C Research and Development Working Group symposium on User Modelling for Accessibility (UM4A). Finally, dissemination has been taken forward through its inclusion as an invited paper presented during a subsequent parallel session within the 8th International Conference on Universal Access in Human-Computer Interaction
Prediction of uncertainty events using human-computer interaction
The practice of medicine is characterized by complex situations that evoke uncertainty.
Uncertainty has implications for the quality and costs of health care, thus emphasizing
the importance of identifying its the main causes.
Uncertainty can be manifested through human behaviour. Accordingly, in this dissertation,
a machine learning model that detects events of uncertainty based on mouse
cursor movements was created. To do so, 79 participants answered an online survey while
the mouse data was being tracked. This data was used to extract meaningful features that
allowed model testing and training after a feature selection stage. With the implementation
of a Logistic Regression, and applying a k-fold cross-validation method, the model
achieved an estimated performance of 81%.
It was found that, during moments of uncertainty, the number of horizontal direction
inversions increases and the mouse cursor travels higher distances. Moreover, items that
evoke uncertainty are associated to longer interaction times and a higher number of visits.
Subsequently, the model was applied to a medical decision making task performed
by 8 physicians, in order to understand whether it might be applied in different contexts
or not. The results were consistent with the task design.
To better understand the nature of uncertainty, its relationship with personality was
explored. Regarding the clinical task, it was found a slight tendency of uncertainty to
increase with Neuroticism.
In the future, the created model may be used to help physicians understand their
main difficulties
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