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Remote Education Tutors (RETs) are central to the delivery of distance schooling in Australia and are accountable for the face-to face supervision and educational support of students. They act as the government mandated adult supervisors of Australian primary and secondary school students enrolled in distance education, including geographically isolated learners. This paper draws on statistical data from a national survey ( N  = 575) that was designed to map the perceptions of Australian RETs. These data confirmed that RETs act as a conduit between the distance schooling teacher and student, and that their role requires complex capabilities to be performed within a structured framework. Time restrictions with competing demands present a constant challenge to the RETs’ work satisfaction. Constraining this occupation is the reality that there is no formal qualification available for RETs. Without specific credentialling, it appears that the RETs’ (in)visible role risks being overlooked as a substantive educational occupation.

Due to the COVID-19 pandemic, there has been a shift from in-person to remote education, with most students taking classes via video meetings. This change inhibits active class participation from students. In particular, video education has limitations in replacing practical classes, which require both theoretical and empirical knowledge. In this study, we propose a system that incorporates virtual reality and metaverse methods into the classroom to compensate for the shortcomings of the existing remote models of practical education. Based on the proposed system, we developed an aircraft maintenance simulation and conducted an experiment comparing our system to a video training method. To measure educational effectiveness, knowledge acquisition, and retention tests were conducted and presence was investigated via survey responses. The results of the experiment show that the group using the proposed system scored higher than the video training group on both knowledge tests. As the responses given to the presence questionnaire confirmed a sense of spatial presence felt by the participants, the usability of the proposed system was judged to be appropriate.

“This work offers us the rare opportunity to step inside innovative uses of technologies, mergers of global technologies into local knowledge, and community advocacy of local history and ideology…The young people who move through these pages are motivated and proud of having had the opportunities that make possible their linking together of historical knowledge and contemporary means of communication and performance. The means illustrated here have enabled them to develop skills that will help them move into the future as adults engaged with the health and life of their own communities, connected to their language and culture as their way of being in the world of the local so as to know the world of the global.” Professor Shirley Brice Heath Stanford University, USA

Learning related emotions (LREs) are determinant for students’ achievement both in face-to-face and online education. Research has also shown that LREs tend to affect technology acceptance which in turn affects learning outcomes as well. Today though, the negative psychological impact of the COVID-19 crisis and the sudden transmission to obligatory remote education might yield different functions of emotions and acceptance on learning outcomes. In this context, the current study seeks to model the relations between students’ negative emotions, acceptance of (emergency) remote education, and self-perceived knowledge improvement. The suggested model was examined and validated on 116 university students that attended fully remote courses in Greece during the COVID-19 crisis. The results suggested that negative emotions of boredom and cognitive load are significant predictors of students’ acceptance of remote learning components: i) online attending a lecture, ii) online communicating with professor, and iii) online collaborating with peers. Anxiety directly affected perceived knowledge improvement, boredom, and cognitive load; Boredom was also affected by cognitive load. In addition, acceptance of remote learning components indirectly affected perceived knowledge improvement mediated by learnability. Boredom was the strongest predictor of online attending a lecture and online collaborating with peers, while online communication with professor was the strongest predictor of learnability. The contribution of this study and the structural findings are further discussed in the paper.

The outbreak of the coronavirus pandemic was declared a public health emergency of international concern. In South Africa (SA), institutions had to adopt emergency remote education, thus resulting in significant challenges for both students and lecturers. This article investigated students’ views and perceptions towards emergency remote education. The Diffusion of Innovations (DoI) model was used as a lens to understand students’ views regarding emergency remote education. The researchers applied a qualitative research approach within the interpretivist paradigm since it offered an opportunity to explore and understand participants’ lived experiences. Purposive sampling was used. The participants included nine undergraduate students from a public university in Gauteng province. Findings highlighted students’ ambivalent views towards online teaching and learning. Some participants support emergency remote education, while some believed that they did not acquire the depth and scope of the content of the module in comparison to contact lectures. Participants indicated that it was challenging to follow lecturers due to unstable network connectivity. They highlighted socio-economic conditions, lack of resources and an unconducive learning environment affected their education. For effective online teaching and learning, appropriate planning and infrastructure were recommended to be available and accessible to all students.

Basic life support (BLS) education is essential for improving bystander cardiopulmonary resuscitation (CPR) rates, but the imparting of such education faces obstacles during the outbreak of emerging infectious diseases, such as COVID-19. When face-to-face teaching is limited, distance learning-blended learning (BL) or an online-only model-is encouraged. However, evidence regarding the effect of online-only CPR training is scarce, and comparative studies on classroom-based BL (CBL) are lacking. While other strategies have recommended self-directed learning and deliberate practice to enhance CPR education, no previous studies have incorporated all of these instructional methods into a BLS course. This study aimed to demonstrate a novel BLS training model-remote practice BL (RBL)-and compare its educational outcomes with those of the conventional CBL model. A static-group comparison study was conducted. It included RBL and CBL courses that shared the same paradigm, comprising online lectures, a deliberate practice session with Little Anne quality CPR (QCPR) manikin feedback, and a final assessment session. In the main intervention, the RBL group was required to perform distant self-directed deliberate practice and complete the final assessment via an online video conference. Manikin-rated CPR scores were measured as the primary outcome; the number of retakes of the final examination was the secondary outcome. A total of 52 and 104 participants from the RBL and CBL groups, respectively, were eligible for data analysis. A comparison of the 2 groups revealed that there were more women in the RBL group than the CBL group (36/52, 69.2% vs 51/104, 49%, respectively; P=.02). After adjustment, there were no significant differences in scores for QCPR release (96.9 vs 96.4, respectively; P=.61), QCPR depth (99.2 vs 99.5, respectively; P=.27), or QCPR rate (94.9 vs 95.5, respectively; P=.83). The RBL group spent more days practicing before the final assessment (12.4 vs 8.9 days, respectively; P<.001) and also had a higher number of retakes (1.4 vs 1.1 times, respectively; P<.001). We developed a remote practice BL-based method for online-only distant BLS CPR training. In terms of CPR performance, using remote self-directed deliberate practice was not inferior to the conventional classroom-based instructor-led method, although it tended to take more time to achieve the same effect. Not applicable.

To contain the COVID-19 pandemic, governments all over the world implemented strong lockdown measures to a large part of the population, including the closing of educational centres. Teachers were urged to transform their teaching methodology, moving from a face-to-face model to an emergency remote education (ERE) model, characterised by the use of technologies to continue with lectures and maintain the physical distance with the students. The aim of the present study was to analyse the existence of socio-digital inequalities and the educational challenges posed by the development of an ERE model, hence, contributing to the literature by proposing a systematic and holistic approach on this phenomenon. Based on the characteristics of the research problem and the objectives set, a qualitative methodology was applied. On the one hand, a semi-structured interview was conducted with 136 active teachers as the main data gathering technique. On the other hand, grounded theory was key in interpreting the results, with the aim of generating the theory in a systematic and holistic manner. It can be asserted that ERE was very useful during the lockdown of schools, and its potential to transform education was demonstrated. However, it was also shown that the development of an ERE model can cause socio-digital inequalities among students, due to the lack of access to digital devices and Internet connection, mainly due to factors, such as the socio-educational level of the family and the rural or urban context of the centre.

IntroductionSurrey and Borders NHS Foundation Trust’s AVATr (Augmented Virtual-reality Avatar in Training) is a unique ground-breaking Virtual Patient simulation system, which uses the Xenodu platform to train learners in essential clinical and complex communication skills. Over 30 patient scenarios have been developed after identifying learner-specific development needs, including exploration of overt psychosis, assessment of capacity, sharing bad news, and neglect in care home residents.During the session, the trainee is projected on to a large screen, using a camera and video special effects, which results in a life-like interaction with the Virtual Patient. Trainees can view themselves interacting with the Virtual Patient in real-time, from a unique ’out-of-body’ perspective, immersed in a customdesigned interactive virtual environment. This is different to a first-person perspective used in virtual or augmented-reality systems in several clinical specialties. During the COVID-19 pandemic, we evolved the AVATr model to remote or hybrid sessions, where simulations were digitally enhanced, and have been run through Microsoft Teams. The simulation facilitator is connected to a multi-user video call, enabling the Virtual Patient to be projected as an attendee using Microsoft Teams.ObjectivesTo evaluate the feedback from Doctors in training taking part on the education sessions.MethodsWe collected qualitiative and quanttaive infromation from participants after the teaching session.ResultsWe received strongly positive reults in all parameters measured. the presenters will show a detailed breakdoen in the session.ConclusionsThe digitalised delivery of the virtual patient simulation, has been pivotal in limiting interruptions to communication skills training in mental health.DisclosureThe NHS trust has co produced the simulation platform with a private software firm Xenadu Virtual Environments

The evolution of digital education necessitates robust computational frameworks to address the complexities inherent in remote learning environments. Traditional scheduling mechanisms often fall short in accommodating the dynamic nature of learner engagement and the asynchronous delivery of content. To bridge this gap, we introduce a novel computational model that leverages reinforcement learning to optimize content delivery schedules. Central to our approach is the Attentive Stochastic Transition Estimation Network (ASTEN), which models the probabilistic transitions of learner states, accounting for factors such as attention variability and feedback delays. Complementing ASTEN is the Selective Informative Delivery Strategy (SIDS), a decision-theoretic framework that determines optimal content emission based on real-time uncertainty assessments and pedagogical utility. Our approach captures nuanced behavioral trends, such as sporadic learner interaction, temporal learning decay, and individualized attention cycles, thereby enabling a more responsive and tailored instructional strategy. By explicitly integrating cognitive and behavioral signals within the scheduling framework, our model facilitates the delivery of content that aligns with each learner’s evolving state. Empirical evaluations demonstrate that our integrated model significantly enhances learning outcomes by adapting to individual learner trajectories and mitigating the challenges posed by sparse feedback. This research contributes to the theoretical foundations of computational learning models and offers practical insights for the development of adaptive educational technologies, particularly in environments where traditional one-size-fits-all approaches prove inadequate.