Encyclopedia of Human Computer Interaction

Ghaoui, Claude

doi:10.4018/978-1-59140-562-7

Cited by 103 publications

(8 citation statements)

References 5 publications

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“…Bråten et al, 2010;Pornpitakpan, 2004;Rouet et al, 2020;Werner da Rosa & Otero, 2018). In this context, trustworthiness refers to the extent to which a source is perceived to be willing to provide accurate and unbiased information, and expertise to the extent to which a source is perceived to be able, and thus competent, to provide accurate and valid information (Danielson, 2006;Sperber et al, 2010). That is, readers may perceive an expert in a field as more trustworthy if the expert works for a university rather than for a company, and therefore conceive the former source as more credible.…”

Section: Introductionmentioning

confidence: 99%

How laypersons consider differences in sources’ trustworthiness and expertise in their regulation and resolution of scientific conflicts

Gottschling

Kammerer

Thomm

et al. 2020

International Journal of Science Education, Part B

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When reading scientific information on the Internet laypersons frequently encounter conflicting claims. However, they usually lack the ability to resolve these scientific conflicts based on their own prior knowledge. This study aims to investigate how differences in the trustworthiness and/or expertise of the sources putting forward the conflicting claims affect laypersons' explanation and resolution of the scientific conflict. We sequentially presented 144 participants with two conflicting scientific claims regarding the safety of nanoparticles in sunscreen and manipulated whether the scientists putting forward the claims differed in their trustworthiness and/or expertise. After having read the claims on a computer in a self-paced manner, participants rated their subjective explanations for the conflicting claims, assessed their personal claim agreement, and completed a source memory task. We examined how differences in source trustworthiness and source expertise affected these measures. Results showed that trustworthiness differences resulted in higher attribution of the conflict to motivational explanations, and expertise differences in higher attribution of the conflict to competence explanations, than without respective differences. Furthermore, main effects of trustworthiness differences and of expertise differences on readers' claim agreement were shown, with participants agreeing more with claims from sources of higher trustworthiness or expertise.

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Section: Introductionmentioning

confidence: 99%

How laypersons consider differences in sources’ trustworthiness and expertise in their regulation and resolution of scientific conflicts

Gottschling

Kammerer

Thomm

et al. 2020

International Journal of Science Education, Part B

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“…The fixation count is the number of discrete points in a visual field, where participant fixates or focuses their attention. The number of fixations is indicative of the importance or "noticeability" of objects/ areas to a user [38].…”

Section: Fixation Count (Fc)mentioning

confidence: 99%

“…= Where = the number of fixations in AOI = Total number of fixations in AOG The fixation rate is indicative of search efficiency, with smaller ratio suggesting that participants spend more effort in finding the pertinent objects, thereby indicating lower search efficiency [38].…”

Section: Fixation Rate (Fr)mentioning

confidence: 99%

Automating Analysis of Construction Workers' Viewing Patterns for Personalized Safety Training and Management

Jeelani¹,

Han²,

Albert³

2018

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Unrecognized hazards increase the likelihood of workplace fatalities and injuries substantially. However, recent research has demonstrated that a large proportion of hazards remain unrecognized in dynamic construction environments. Recent studies have suggested a strong correlation between viewing patterns of workers and their hazard recognition performance. Hence, it is important to study and analyze the viewing patterns of workers to gain a better understanding of their hazard recognition performance. The objective of this exploratory research is to explore hazard recognition as a visual search process to identifying various visual search factors that affect the process of hazard recognition. Further, the study also proposes a framework to develop a vision based tool capable of recording and analyzing viewing patterns of construction workers and generate feedback for personalized training and proactive safety management.

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“…For instance, researchers have investigated fixations in eye movement to measure the degree of engagement to improve naturalness in human-agent communication according to the participant's level of engagement [20]. Other research has identified several features of eye-movements: fixations per area of interest (the number of fixations on a particular area); fixation duration; gaze/fixation clusters [16,22]. In my research, I will use these features to measure childrenâĂŹs engagement with digital narratives.…”

Section: Eye-tracking Measuresmentioning

confidence: 99%

“…Using eye-tracking [22] and facial expression [2] analysis, we can collect some data without disrupting participants' attention from the narrative.…”

Section: Automated Measuresmentioning

confidence: 99%

Evaluating engagement in digital narratives from facial data

Huan

2017

Proceedings of the 19th ACM International Conference on Multimodal Interaction

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Engagement researchers indicate that the engagement level of people in a narrative has an influence on people's subsequent storyrelated attitudes and beliefs [6], which helps psychologists understand people's social behaviours and personal experience. With the arrival of multimedia, the digital narrative combines multimedia features (e.g. varying images, music and voiceover) with traditional storytelling. Research on digital narratives has been widely used in helping students gain problem-solving and presentation skills [4] as well as supporting child psychologists investigating children's social understanding such as family/peer relationships [18] through completing their digital narratives. However, there is little study on the effect of multimedia features in digital narratives on the engagement level of people.This research focuses on measuring the levels of engagement of people in digital narratives and specifically on understanding the media effect of digital narratives on people's engagement levels. Measurement tools are developed and validated through analyses of facial data from different age groups (children and young adults) in watching stories with different media features of digital narratives. Data sources used in this research include a questionnaire with Smileyometer scale [10] and the observation of each participant's facial behaviours.

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Encyclopedia of Human Computer Interaction

Cited by 103 publications

References 5 publications

How laypersons consider differences in sources’ trustworthiness and expertise in their regulation and resolution of scientific conflicts

How laypersons consider differences in sources’ trustworthiness and expertise in their regulation and resolution of scientific conflicts

Automating Analysis of Construction Workers' Viewing Patterns for Personalized Safety Training and Management

Evaluating engagement in digital narratives from facial data

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