May I teach you? Students' behavior when lectured by robotic vs. human teachers

Are Retail Customers Ready for Service Robot Assistants?

The use of service robots is rapidly expanding in many industries, including the retail sector. In some Asian countries retail companies already deploy in-store humanoid robot assistants that interact with customers in a personalized and dynamic way. However, little is known about customers' perceptions of these robot-assisted interactions. Therefore, we compared customers' perceived service quality of a human-robot interaction with a human-human interaction in a retail store, using an experiment with hypothetical scenarios (N = 425). Participants' general attitudes towards robots, their age, gender, and educational level were included as moderators in the analyses (a mixed-design ANOVA model). Results showed that participants valued service quality higher in the human-human interaction scenario. Additionally, findings from the moderation analyses indicated that perceived service quality of the human- robot interaction and the human-human interaction did not statistically significantly differ for participants with relatively high positive attitudes towards robots. Participants with relatively low positive attitudes towards robots, however, held statistically significantly lower perceptions of service quality for the human-robot interaction. Neither age, gender nor educational level statistically significantly influenced participants' perceived service quality scores for both service encounters.

Leaders' innovation expectation and nurses' innovation behaviour in conjunction with artificial intelligence: The chain mediation of job control and creative self-efficacy

AIM

The aim of this work is to investigate the influence of leaders' innovation expectation on nurses' innovation behaviour in conjunction with artificial intelligence, as well as explore the chain mediating effect of job control and creative self-efficacy between leaders' innovation expectation and nurses' innovation behaviour.

BACKGROUND

The nurses' innovation behaviour is crucial in promoting medical artificial intelligence. Thus, clarifying the influencing factors of nurses' innovation behaviour has become a priority.

METHODS

A cross-sectional survey was conducted with 263 Chinese nurses from tertiary hospitals and secondary hospitals in Hefei, Anhui province.

RESULTS

Leaders' innovation expectation was positively related to nurses' innovation behaviour. Creative self-efficacy and job control respectively mediated the relationship between leaders' innovation expectation and nurses' innovation behaviour. Furthermore, creative self-efficacy and job control played a chain mediation role between leaders' innovation expectation and nurses' innovation behaviour.

CONCLUSION

Leaders' innovation expectation helps to enhance nurses' creative self-efficacy and job control, thereby enhancing nurses' enthusiasm for innovation.

IMPLICATIONS FOR NURSING MANAGEMENT

Hospital managers and leaders formulate intervention measures to increase leaders' innovation expectation, nurses' creative self-efficacy and job control, and encourage nurses' innovation behaviour.

Promoting Healthcare Workers' Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human-Computer Trust

Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.

Assessing acceptance of augmented reality in nursing education

The Covid-19 pandemic has negatively affected every aspect of human life. In these challenging times nursing students, facing academic and psychological issues, are advised to use augmented reality applications in the field of health sciences for increasing their motivations and academic performances. The main motive of the study was to examine the acceptance status of nursing students in implementing augmented reality technology in their education and training. The study is a quantitative research study, and it uses the causal-comparative screening method. The data used in the study was collected online from 419 nursing students. The hybrid method was preferred. First, the hypotheses based on the linear relationships were defined between the variables which were then tested by the method of structural equation modeling. Second, the method of artificial neural networks was used to determine the non-linear relationships between the variables. The results show that the nursing students have a high intention of using augmented reality technology as a way of self-learning. It was also found that the most emphasized motive behind this intention is the expectation that using augmented reality technology will increase their academic performance. They also think that AR technology has many potential benefits to offer in the future. It was observed that a considerable number of students already use augmented reality technology for its usefulness and with a hedonic motivation. In conclusion, nursing students have a high acceptance of using augmented reality technology during their education and training process. Since we live in a world where e-learning and self-learning education/training have become widespread, it is estimated that students will demand augmented reality applications as a part of holistic education, and as an alternative to traditional textbooks.

Human-robot interaction methodology: Robot teaching activity

Research on the use of social robots in education is constantly increasing in the growing field of human-robot interaction (HRI). Consequently, it is essential to determine an appropriate methodology to test how these robots can optimally interact with students. This study specifically looks at how we can use existing knowledge from psychology, neuroscience and educational research and apply them with validity and credibility in HRI studies. We are interested in incorporating research methodologies to evaluate the performance of social robots acting as university professors in a real classroom environment. Moreover, we aim to measure three effects, a) students’ knowledge acquisition (quiz after lecture and final exam grades), b) level of enjoyment (Likert scale questionnaire), and c) level of surprize (analysis of facial expressions filmed by cameras). To identify the relationship between students’ knowledge acquisition, enjoyment, and level of surprize, we designed a series of three experiments, testing three variables: 1. one human-tutor lesson, 2. one robot-tutor lesson, 3. two robot-tutor lessons. In this paper we thoroughly explain the methods used to measuring and testing these variables based on modern and reliable sources.•

Application of Psychological Research Methods to Human-Robot Interaction Studies.