The last trend in technology is the upcoming Metaverse [1]. Metaverse represents a combination of virtual and augmented technology. With this technology, users will be able to immerse into a fully digital environment by obtaining a virtual identity through a digital avatar and acting as this was the real world. They can meet other users, shop, buy real estate, visit bars and restaurants, even flirt. Metaverse can be applied in several aspects of life such as (among others): Economy (Metaverse is entering into the cryptocurrency field), finance [2], social life, working environment, healthcare, real estate [3], and education [4]. In the last 2 and a half years, during the COVID-19 pandemic, universities made immediate use of e-learning technologies, providing students with access to online learning content and platforms. Previous considerations on how to better integrate the technology to universities or how the institutions can be better prepared in terms of infrastructures were vanished almost immediately due to the necessity of immediate actions towards the need for social distance and global health [5]. The present study proposes a framework for university students’ metaverse technologies in education acceptance and intention to use. The study is based on the Technology Acceptance Model (TAM) [6, 7]. The objectives of the study are to analyze the relationship of students’ intention to use metaverse in education technologies (hereafter named MetaEducation) in correlation with selected constructs of TAM such as: Attitude (ATT), Perceived Usefulness (PU), Perceived Ease of Use (PE), Self-efficacy (SE) of the metaverse technologies in education, and Subjective Norm (SN). The present study develops a structural model of MetaEducation acceptance. This model will be useful to universities’ managers, policymakers and professors to better incorporate the upcoming metaverse technology. The present study tests (if supported) the correlations among the aforementioned constructs. Preliminary results show a hesitance to use MetaEducation technologies from university students. Self-efficacy and Subjective Norm affect Attitude and Perceived Usefulness positively, but on the other side, there is no strong correlation between Perceived Ease of Use and Attitude or Perceived Usefulness and Attitude. Authors believe that the weak ties among the studies constructs have to do with the lack of knowledge of what really MetaEducation really is, and which are its advantages of use.
LINK
Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.
LINK
The present study proposes a framework for university students’ metaverse technologies in education acceptance and intention to use. The study is based on the Technology Acceptance Model (TAM). Data used are coming from two universities and are compared to each other. 311 university students from The Netherlands and 292 from Greece participated, gathering 513 valid answers to analyze (285 from The Netherlands and 228 from Greece). The objectives of the study are to analyze the relationship between students’ intention to use metaverse in education technologies (hereafter named MetaEducation) in correlation with selected constructs of TAM such as Attitude (ATT), Perceived Usefulness (PU), Perceived Ease of Use (PE), Self-efficacy (SE) of the metaverse technologies in education, and Subjective Norm (SN). Furthermore, we want to research any cultural differences between the two populations based on their answers. Therefore, we propose two different structural models from the SEM analysis, once for each country. For both proposed models, different and individual analysis is conducted. We decided not to combine the datasets, since the samples present several cultural differences. The proposed models will be useful to universities’ managers, policymakers, and professors to better incorporate the upcoming metaverse technology. The present study tests the correlations among the aforementioned constructs. Preliminary results show a hesitance to use MetaEducation technologies from university students from both countries. Self-efficacy and Subjective Norms affect Attitude and Perceived Usefulness positively, but on the other side, there is no strong correlation between Perceived Ease of Use and Attitude or Perceived Usefulness and Attitude. Authors believe that the weak ties among the study constructs have to do with the lack of knowledge of what really MetaEducation really is, and which are its advantages of use.
LINK
The temporal dimension of acceptance is under-researched in technology acceptance research. Yet, people’s perceptions on technology use may change over time when gaining user experiences. Our 6-month home study deploying an interactive robot provides insight into the long-term use of use interactive technology in a domestic environment. We present a phased framework for the acceptance of interactive technology in domestic environments. Based on 97 interviews obtained from 21 participants living in different household types, the results provide an initial validation of our phased framework for long-term acceptance showing that acceptance phases are linked to certain user experiences which evolve over time when people gain experience with the technology. Involving end users in the early stages of development helps researchers understand the cultural and social contexts of acceptance and enables developers to apply this gained knowledge into their future designs.
DOCUMENT
The effectiveness of smart home technology in home care situations depends on the acceptance and use of the technology by both users and end-users. In the Netherlands many projects have started to introduce smart home technology and telecare in the homes of elderly people, but only some have been successful. In this paper, features for success and failure in the deployment of new (ICT) technology in home care are used to revise the technology acceptance model (TAM) into a model that explains the use of smart home and telecare technology by older adults. In the revised model we make the variable 'usefulness' more specific, by describing the benefits of the technology that are expected to positively affect technology usage. Additionally, we state that several moderator variables - that are expected to influence this effect - should be added to the model in order to explain why people eventually do (not) use smart home technology, despite the benefits and the intention to use. We categorize these variables, that represent the problems found in previous studies, in 'accessibility', 'facilitating conditions' and 'personal variables'.
DOCUMENT
Advanced technology is a primary solution for the shortage of care professionals and increasing demand for care, and thus acceptance of such technology is paramount. This study investigates factors that increase use of advanced technology during elderly care, focusing on current use of advanced technology, factors that influence its use, and care professionals’ experiences with the use. This study uses a mixed-method design. Logfiles were used (longitudinal design) to determine current use of advanced technology, questionnaires assessed which factors increase such use, and in-depth interviews were administered to retrieve care professionals’ experiences. Findings suggest that 73% of care professionals use advanced technology, such as camera monitoring, and consult clients’ records electronically. Six of nine hypotheses tested in this study were supported, with correlations strongest between performance expectancy and attitudes toward use, attitudes toward use and satisfaction, and effort expectancy and performance expectancy. Suggested improvements for advanced technology include expanding client information, adding report functionality, solving log-in problems, and increasing speed. Moreover, the quickest way to increase acceptance is by improving performance expectancy. Care professionals scored performance expectancy of advanced technology lowest, though it had the strongest effect on attitudes toward the technology.
DOCUMENT
Purpose: To provide an overview of factors influencing the acceptance of electronic tech-nologies that support aging in place by community-dwelling older adults. Since technologyacceptance factors fluctuate over time, a distinction was made between factors in the pre-implementation stage and factors in the post-implementation stage. Methods: A systematic review of mixed studies. Seven major scientific databases (includingMEDLINE, Scopus and CINAHL) were searched. Inclusion criteria were as follows: (1) originaland peer-reviewed research, (2) qualitative, quantitative or mixed methods research, (3)research in which participants are community-dwelling older adults aged 60 years or older,and (4) research aimed at investigating factors that influence the intention to use or theactual use of electronic technology for aging in place. Three researchers each read the articlesand extracted factors. Results: Sixteen out of 2841 articles were included. Most articles investigated acceptance oftechnology that enhances safety or provides social interaction. The majority of data wasbased on qualitative research investigating factors in the pre-implementation stage. Accep-tance in this stage is influenced by 27 factors, divided into six themes: concerns regardingtechnology (e.g., high cost, privacy implications and usability factors); expected benefits oftechnology (e.g., increased safety and perceived usefulness); need for technology (e.g., per-ceived need and subjective health status); alternatives to technology (e.g., help by family orspouse), social influence (e.g., influence of family, friends and professional caregivers); andcharacteristics of older adults (e.g., desire to age in place). When comparing these results to qualitative results on post-implementation acceptance, our analysis showed that some factors are persistent while new factors also emerge. Quantitative results showed that a small number of variables have a significant influence in the pre-implementation stage. Fourteen out of the sixteen included articles did not use an existing technology acceptance framework or model. Conclusions: Acceptance of technology in the pre-implementation stage is influenced by multiple factors. However, post-implementation research on technology acceptance by community-dwelling older adults is scarce and most of the factors in this review have not been tested by using quantitative methods. Further research is needed to determine if and how the factors in this review are interrelated, and how they relate to existing models of technology acceptance.
LINK
Despite its potential, the acceptance of technology to support the ability to live independently in one’s own home, also called aging in place, is not optimal. Family members may play a key role in technology acceptance by older adults; however, it is not well understood why and how they exert influence. Based on open interviews with 53 community-dwelling older adults, this paper describes the influence of family members, including spouses, on the use of various types of consumer electronics by older adults as was reported by themselves. Such a broad focus enables understanding the use of technology as was reported by older adults, instead of its intended use. Our study reveals that the influence of each family member has its own characteristics. The influence of technology acceptance is a natural and coincidental part of the interaction with spouses and grandchildren in which entertainment and pleasure are prominent. This is also partly true for the influence of children, but their influence also is intentional and driven by concerns. Our study indicates the importance of including all family members when implementing technology in the lives of older adults. Besides information for children about the use(fullness) of devices, it is worthwhile to give grandchildren an important role, because older adults easily adopt their enthusiasm and it might eventually lighten the burden on children.
LINK
Keywords: technology adoption; telecare systems; user acceptance; quality of experience
DOCUMENT
Metaverse, a burgeoning technological trend that combines virtual and augmented reality, provides users with a fully digital environment where they can assume a virtual identity through a digital avatar and interact with others as they were in the real world. Its applications span diverse domains such as economy (with its entry into the cryptocurrency field), finance, social life, working environment, healthcare, real estate, and education. During the COVID-19 and post-COVID-19 era, universities have rapidly adopted e-learning technologies to provide students with online access to learning content and platforms, rendering previous considerations on integrating such technologies or preparing institutional infrastructures virtually obsolete. In light of this context, the present study proposes a framework for analyzing university students' acceptance and intention to use metaverse technologies in education, drawing upon the Technology Acceptance Model (TAM). The study aims to investigate the relationship between students' intention to use metaverse technologies in education, hereafter referred to as MetaEducation, and selected TAM constructs, including Attitude, Perceived Usefulness, Perceived Ease of Use, Self-efficacy of metaverse technologies in education, and Subjective Norm. Notably, Self-efficacy and Subjective Norm have a positive influence on Attitude and Perceived Usefulness, whereas Perceived Ease of Use does not exhibit a strong correlation with Attitude or Perceived Usefulness. The authors postulate that the weak associations between the study's constructs may be attributed to limited knowledge regarding MetaEducation and its potential benefits. Further investigation and analysis of the study's proposed model are warranted to comprehensively understand the complex dynamics involved in the acceptance and utilization of MetaEducation technologies in the realm of higher education
LINK
