A Student-Dominant View of the Readiness to use Metaverse in Education: The TRI-F Framework

This paper reports on students' readiness for using Metaverse for education in a university in a developing country facing infrastructure and poverty challenges. Covid-19 forced many universities to adopt a hybrid approach to teaching and supervision. While online meeting technologies have become commonplace, there is a lack of the connectedness of face-to-face meetings, for which Metaverse is promoted as a solution. We pose the question as to the level of readiness of students to use Metaverse technologies. Thematic analysis of students' self-reflections on their experience of supervision in a 2D virtual world revealed the usefulness of the technology readiness index model, from which an extension to the model was proposed to include facilitators for the application of the technology that may mediate the motivators and inhibitors when assessing readiness to use Metaverse in education settings

An integrated model for examining teachers' intentions to use augmented reality in science courses

Many studies show that augmented reality (AR) provides multiple benefits to science education, including learning gains, motivation to learn, and collaborative learning. However, while using AR largely depends on the teachers' willingness, existing literature lacks studies that identify teachers' intentions to use this technology. This study proposes a model to predict science teachers' intentions to use AR in their classes. Our model merges the Theory of Planned Behavior and the Unified Theory of Acceptance and Use of Technology 2. It includes nine hypotheses that were tested with 451 science teachers from different cities in Turkey. The results indicate that our model identifies the factors affecting teachers' intentions to use AR with a stronger explanatory power than the referenced theories. Besides, all hypotheses within the proposed model were statistically supported in determining antecedents of science teachers' intentions. Finally, the study contributes to the theory and practice by focusing on the psychological aspects required for explaining science teachers' intentions to use AR

Fearing the Robot Apocalypse: Correlates of AI Anxiety

This study examines the relationship between individuals’ be-liefs about AI (Artificial Intelligence) and levels of anxiety with respect to their technology readiness level. In this cross-sectional study, we surveyed 65 stu-dents at a southwestern US college. Using partial least squares analysis, we found that technology readiness contributors were significantly and positively related to only one AI anxiety factor: socio-technical illiteracy. In contrast, all four links between technology readiness inhibitors and AI anxiety factors were significant with medium effect sizes. Technology readiness inhibitors are posi-tively related to learning, fears of job replacement, socio-technical illiteracy, and particular AI configurations. Thus, we conclude that AI anxiety runs through a spectrum. It is influenced by real, practical consequences of immedi-ate effects of increased automatization but also by popular representations and discussions of the negative consequences of artificial general intelligence and killer robots and addressing technology readiness is unlikely to mitigate effects of AI anxiety

Factors Influencing Small Construction Businesses from Implementing Information Security: A Case Study

This qualitative study described the influence of small businesses’ failure to properly implement information security technologies resulting in the loss of sensitive and proprietary business information. A collective case study approach was used to determine the most effective way to gain a holistic picture of how small construction businesses make security technology implementation decisions to support their workforce. The theory guiding this study was the Unified Theory of Acceptance and Use of Technology (UTAUT) model which is related to the Theory of Planned Behavior and the Technology Acceptance Model which helped explain the intentions of individuals to use information systems. Security policies and threats (insider and cyber) were also looked at during this study. Data collection methods included questionnaires, interviews, document reviews, journaling, and webpage scans to provide insight into security information technology use. The results of this study indicated small construction businesses rely heavily on third-party information technology venders to perform security functions. This security model has led to several of the businesses experiencing cyber security incidents and the businesses being more reactive in responding to cyber-attacks. Deficiencies with planning for system implementations also impacted how employees thought and used the businesses’ security information systems. The study’s results indicated employee’s behavior intention and use behavior was highly impacted by the age moderator with older employees more likely to display a lower behavior intention and use behavior for using systems

An exploration of decision making oscillations in dynamic and undynamic environments

The rapidly changing nature of information and use of information systems within organisations has seen the emergence of a gradual mistrust of human decision-making approaches. This is evident today with both researchers and practitioners advocating for an increased use of data-driven decision making. Although the advantages of using a data-driven approach have been well-documented, there has been scant research on the interplay between a data-driven approach and more human-centric decision making from an information systems perspective. To that end, this research study seeks to explore oscillations in decision-making approaches while having access to information systems in dynamic and undynamic environments. Data was gathered across four case study locations, in two distinct environments. The first of these was classified as a dynamic environment and two case studies were investigated involving aircraft pilots and an air traffic controller. The second was classified as an undynamic environment, with two further case studies investigated involving a pharmacist and national grid controller. The output of this study makes a number of contributions to IS theory and practise. Firstly, this study extends cognitive continuum theory to the information systems domain. In doing so, this study validates that decision makers will oscillate between an intuitive, system-aided judgement, and data-driven approach to decision making. Secondly, two distinct mechanisms are identified and once activated these mechanisms will oscillate a decision makers decision-making approach. These mechanisms are referred to as the personal sensitivity to a negative outcome mechanism and the process loafing mechanism. Thirdly, this research has validated that the environment a decision maker operates is a factor in the decision-making approach used. However, it was also found that the personal sensitivity to a negative outcome mechanism will override the environment a decision maker is in once activated. Fourthly, this study highlights the need for organisations to consider decision making approaches when implementing new policies, procedures, and information systems