Emotional expressions facilitate human–human trust when using automation in high-risk situations

Feng, Jing; Sanchez, Joseph; Sall, Robert; Lyons, Joseph B.; Nam, Chang S.

doi:10.1080/08995605.2019.1630227

Cited by 5 publications

(2 citation statements)

References 64 publications

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“…Many studies have shown that despite differences in skin color, language, and social status, the basic patterns of facial expression and facial muscle movement in humans are generally consistent (de la Rosa et al, 2018). Relevant research shows that actual language accounts for only 35%, whereas non-verbal signals account for 65% of the impact of human expressions (Feng et al, 2019). Therefore, facial expressions are an important link for students to express their emotions.…”

Section: Introductionmentioning

confidence: 99%

New Breakthroughs and Innovation Modes in English Education in Post-pandemic Era

Shen

Guo

2022

Front. Psychol.

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The outbreak of COVID-19 has brought drastic changes to English teaching as it has shifted from the offline mode before the pandemic to the online mode during the pandemic. However, in the post-pandemic era, there are still many problems in the effective implementation of the process of English teaching, leading to the inability of achieving better results in the quality and efficiency of English teaching and effective cultivation of students’ practical application ability. In recent years, English speaking has attracted the attention of experts and scholars. Therefore, this study constructs an interactive English-speaking practice scene based on a virtual character. A dual-modality emotion recognition method is proposed that mainly recognizes and analyzes facial expressions and physiological signals of students and the virtual character in each scene. Thereafter, the system adjusts the difficulty of the conversation according to the current state of students, toward making the conversation more conducive to the students’ understanding and gradually improving their English-speaking ability. The simulation compares nine facial expressions based on the eNTERFACE05 and CAS-PEAL datasets, which shows that the emotion recognition method proposed in this manuscript can effectively recognize students’ emotions in interactive English-speaking practice and reduce the recognition time to a great extent. The recognition accuracy of the nine facial expressions was close to 90% for the dual-modality emotion recognition method in the eNTERFACE05 dataset, and the recognition accuracy of the dual-modality emotion recognition method was significantly improved with an average improvement of approximately 5%.

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Section: Introductionmentioning

confidence: 99%

New Breakthroughs and Innovation Modes in English Education in Post-pandemic Era

Shen

Guo

2022

Front. Psychol.

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“…The current study aimed to develop a Chinese version of the TPAS. The TPAS is one of the most widely used scales of measurements in human-automation interaction scenarios and has been proven with excellent psychometric properties in the Western culture (Gulati et al, 2019 ; Hussein et al, 2020a , b ; Wei et al, 2020 ), making the TPAS well acknowledged by the majority of researchers ( Manchon et al, 2021 ; Feng et al, 2019 ). The TPAS adopted methods of word elicitation, questionnaire, and paired comparison to generate items, allowing researchers to directly assess trust between humans and automation.…”

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confidence: 99%

Psychometric properties of the Chinese version of the trust between People and Automation Scale (TPAS) in Chinese adults

Cai

Sun

et al. 2022

Psicol. Refl. Crít.

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Trust in automation plays a leading role in human-automation interaction. As there lack of scales measuring trust in automation in China, the purpose of this study was to adapt the trust between People and Automation Scale (TPAS) into Chinese and to demonstrate its psychometric properties among Chinese adults. A total of 310 Chinese adults were randomly selected as sample 1, and 508 Chinese adults as sample 2. Results of the item analysis revealed that each item had a good quality, and the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) suggested that the two-factor model with 12 items was the best fitting model. In addition, the TPAS was positively correlated with Interpersonal Trust Scale (ITS), proving good evidence based on relations to other variables to support the TPAS. In sum, the study suggested that the Chinese version of the TPAS could be used as an effective tool to assess trust in automation in the Chinese context.

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The Effect of past Algorithmic Performance and Decision Significance on Algorithmic Advice Acceptance

Saragih

Morrison

2021

International Journal of Human–Computer Interaction

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Emotional expressions facilitate human–human trust when using automation in high-risk situations

Cited by 5 publications

References 64 publications

New Breakthroughs and Innovation Modes in English Education in Post-pandemic Era

New Breakthroughs and Innovation Modes in English Education in Post-pandemic Era

Psychometric properties of the Chinese version of the trust between People and Automation Scale (TPAS) in Chinese adults

The Effect of past Algorithmic Performance and Decision Significance on Algorithmic Advice Acceptance

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