International Journal of Advances in Applied Computational Intelligence
Journal DOI
2833-5600ISSN (Online)
This inclination is caused by the fact that the topic of technology incorporation has not received enough attention. The use of information and communication technology (ICT) like Google Glass has allowed instructors and students to engage in a technology-based educational setting because of the subsequent dramatic transformation. Yet, just a small number of schools and universities have started using Google Glass in their classrooms. This research aims to look at Google Glass adoption in the UAE. We reasoned those educating instructors and students about Google Glass's effective capabilities would help them make up their minds about adopting the device in classrooms. The layout of a framework that connects TAM with other influential factors is discussed in this study. To improve the interaction between instructors and learners in the classroom, this research explored the incorporation of the technology acceptance model (TAM) with the widely acknowledged potent features of the gadget, such as the teaching and learning mediator, "Motivation," and trust and information privacy. 750 questionnaires from various universities were acquired in total. According to the student's survey data gathered, the research model was studied using partial least squares-structural equation modeling (PLS-SEM) and machine learning models. The findings showed a significant association between motivation, trust, and privacy, as well as perceived usefulness and perceived ease of use of Google Glass. Moreover, the adoption of Google Glass was substantially correlated with perceived usefulness and perceived ease of use. The perceived ease of use, trust, and privacy are all important factors in the adoption of Google Glass. These results' practical implications for subsequent research were also discussed.
Read MoreDoi: https://doi.org/10.54216/IJAACI.010101
Vol. 1 Issue. 1 PP. 08-22, (2022)
Studies on the acceptance of social media apps are being conducted at an increasing rate. The factors influencing its popularity for learning reasons are still not well understood, though. The goal of this study is to create a conceptual model that extends the Technology Adoption Model (TAM) to account for perceived playfulness to gauge students' acceptance of social media in learning. A total of 623 authenticated questionnaire surveys were obtained from students enrolled at a reputed university in the United Arab Emirates (UAE). Tools such as partial least squares-structural equation modeling (PLS-SEM) and machine learning approaches were obtained to examine the collected data. According to the research findings, significant parameters of students' intention to use social media networks for education include perceived playfulness, perceived usefulness, and perceived ease of use.
Read MoreDoi: https://doi.org/10.54216/IJAACI.010102
Vol. 1 Issue. 1 PP. 23-33, (2022)
The outbreak of COVID-19 led to the foundation of modern techniques of learning which involves metaverse. Specifically in the medical field, where cross-border medical training became out of question. Opportunities for medical students to practice were greatly reduced as there was very less physical interaction with patients due to the COVID-19 pandemic. However, metaverse proved to be of great help for medical staff to gain education virtually who came to the UAE to acquire proficient skills related to medical technology. New digital approaches based on metaverse technology are evolving in the UAE medical groups to address restrictions arising by using current teleconferencing platforms like Zoom in providing effective medical training. The goal of this research is to find out the effect of using the metaverse system for medical training in the UAE and students’ perceptions of it. The adoption features of trialability, observability, perceived pleasure, perceived ubiquity, perceived worth, personal innovativeness, and Technology Acceptance Model (TAM) components are all included in the conceptual model. The study’s novelty comes from its conceptual model, which links both personal and technology-based elements. Furthermore, the present work will employ a novel approach of hybrid analysis to perform machine-learning (ML) based structural equation modeling analysis (SEM). In addition, this study is assisted by importance-performance map analysis (IPMA) to evaluate the performance and importance of presumed factors. As this work is one of the rare attempts to utilize machine learning algorithms in predicting the intention to use metaverse systems, the methodological aspect of the study is also of great use. The adoption of a complementary multi-analytical approach is thought to provide a novel contribution to the information systems (IS) field. This study is also significant in assisting medical authorities to judge the importance of each factor and guiding them to opt for relevant strategies and techniques depending on the significance of the factors.
Read MoreDoi: https://doi.org/10.54216/IJAACI.010103
Vol. 1 Issue. 1 PP. 34-44, (2022)
Knowledge sharing between employees in positions at different levels in the organization chart is always a big challenge. It is important to study the main factors that affects employees’ knowledge. A number of literature reviews that sheds the light on knowledge management (KM) was conducted, which focuse on the employee knowledge sharing motivations. However, analyzing the knowledge sharing among employees is still questioned and requires further examination. The main objective of this systematic review is to analyze the state-of-the-are KM studies that involved the factors that affect employees’ intention to share their tacit knowledge. In this systematic review, we explored the tacit knowledge sharing and reviewed 115 recent papers. After filtering and reviewing we extracted many factors, then we categorize them into twelve categories: (ordered by most frequent studied), namely: trusting environment, culture, organization encouragement, rewards, Information system, intrinsic motivations, equal opportunities, job security, the community of practice, time pressure, knowledge confidence and accuracy, and years of experience. This systematic review is important to organizations which seek to share, preserve tacit knowledge and experiences, and gain competitive edge.
Read MoreDoi: https://doi.org/10.54216/IJAACI.010104
Vol. 1 Issue. 1 PP. 45-68, (2022)
Among studies on natural language generation (NLG), computational creativity, and human-computer interaction; there is a vision of witnessing these tools collaborating with humans in generating and authoring creative content. This study aims to systematically review published studies discussing creative writing and story generation during the period of 2016-2021. This work seeks to identify the primary research methods used in NLG and creative writing studies, to locate how these studies are distributed geographically, and finally, to classify the subfields or common keywords primarily used in NLG involving creative writing. The findings suggest that experiment studies and problem-solving were the most common research methods in NLG and creative writing. Major identified themes in the reviewed articles include story generation, language models, and co-creativity, along with some gaps in foreign language translation and humour generation studies. The majority of the studies suggest that NLG tasks had a positive impact on creative writing. Common tasks related to NLG and creative writing are typically using keywords such as story generation, co-creativity, co-writing, user interface and writing tools. In future work, we aim to explore more GPT-3 capabilities in creative writing, in addition to creative writing applications in foreign language translation tasks.
Read MoreDoi: https://doi.org/10.54216/IJAACI.010105
Vol. 1 Issue. 1 PP. 69-90, (2022)