Background: The potential of learning analytics dashboards in virtual reality simulation-based training environments to influence occupational self-efficacy via self-reflection phase processes in the Chemical industry is still not fully understood. Learning analytics dashboards provide feedback on learner performance and offer points of comparison (i.e., comparison with one's own past performance or comparison with peer performance) to help learners make sense of their feedback.Objectives: We present a theoretical framework for describing learning analytics reference frames and investigate the impact of feedback delivered through dashboards with different reference frames on occupational self-efficacy, while controlling for workplace self-reflection.Methods: This experimental study engaged 42 chemical operator employees, aged between 18 and 55 years, each with at least one year of experience. We utilised a two-group design to ask two research question each with three competing hypotheses related to changes in occupational self-efficacy, employing Bayesian informative hypothesis evaluation.Results and Conclusions: Results for the primary research question suggest that dashboards with progress reference frames do not elicit greater change to self-efficacy than those with social reference frames, however, they may elicit equal change. Furthermore, dashboards with social reference frames may elicit greater change to self-efficacy than those with progress reference frames. Exploratory results found that dashboards with progress reference frames may elicit greater positive directional change than those with social reference frames and that they may elicit equal directional change.These findings contribute to the understanding of self-efficacy beliefs within the Chemical industry, with potential impacts on skill development. The research may inform the design of targeted interventions and training programs to influence self-efficacy. From a practical perspective, this research suggests that careful consideration is needed when choosing reference frames in learning analytics dashboards due to their potential consequences on the formation of learner self-efficacy.

This study addresses the critical need for realistic emergency training in industries where non-stationary conditions can quickly escalate into accidents or incidents. Real-life training is often impractical due to safety concerns and cost constraints. Consequently, incorporating immersive technologies into training curricula becomes crucial. This research explores participants' self-reflection on safety readiness during virtual reality (VR) emergency training and investigates the impact of interactive versus passive exposure to emergency situations in VR.Three distinct exposure methods were developed, varying in the degree of participant involvement. Surprisingly, no statistically significant differences were found among the groups, indicating a positive perception of VR emergency training regardless of the exposure method. Participants valued the opportunity to safely make mistakes, witness consequences, and repeat procedures in VR. They believed such training enhanced their real-life emergency responses by fostering calmness, quick thinking, and prudent reactions.However, some participants expressed skepticism, suggesting that VR training might not accurately simulate real-life stress conditions. Future research should explore the impact of photorealistic VR experiences on operators' perceptions and assess the benefits of additional efforts in VR development for emergency training.

BackgroundLearning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self-regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self-reflection phases) and SRL skills. Insight into design preferences for dashboards with different reference frames (i.e., progress, social, internal achievement and external achievement) is important because the effectiveness of feedback can depend upon how a learner perceives it.ObjectiveThis study examines workplace learner preferences for four dashboard designs for each SRL phase and how SRL skills relate to these preferences.MethodsSeventy participants enrolled in a chemical process apprenticeship program took part in the study. Preferences were determined using a method of adaptive comparative judgement and SRL skills were measured using a questionnaire. Preferences were tested on four dashboard designs informed by social and temporal comparison theory and goal setting theory. Multinomial logistic regressions were used to examine the relationship between dashboard preferences and SRL.Results and ConclusionsResults show that the progress reference frame is more preferred before and after task performance, and the social reference frame is less preferred before and after task performance. It was found that the higher the SRL skill score the higher the probability a learner preferred the progress reference frame compared to having no preference before task performance. The results are consistent with other findings, which suggest caution when using social comparison in designing dashboards which provide feedback. What is already known about this topic? Learning analytics dashboards use visualisations to provide feedback on learning tasks to optimise learning. Learners can better understand the meaning of their feedback if it is presented alongside a point of comparison, such as a prior level of performance, the performance level of their peers or how their performance level compares to an achievement goal. Learning analytics dashboards can support learning behaviours before, during, and after learners perform a task. Learners can acquire information to improve their learning via learning analytics dashboards, such as feedback on performance, which illustrates areas of a task learners are stronger and weaker at, which in turn can help inform future training efforts.What this paper adds? Workplace learners typically prefer dashboards which offer visualisations comparing their current performance level with past levels of performance. Comparison with peers is typically the least preferred point of comparison when offered in learning analytics dashboards. No clear preference emerged between reference frames containing assigned or self-set goals in dashboards presented before and after task performance.Implications for practice Designers should take into account learner preferences when designing learning analytics dashboard visualisations. Designers should consider presenting learning analytics dashboards before, during, and after task performance. Designers should gain more insight into how learners process learning analytic dashboards and act upon it.

This study uses log-file data to investigates how chemical process plant employees interact and engage with two distinct learning analytics dashboard designs, which are implemented in a virtual reality simulation-based training environment. The learning analytics dashboard designs differ by reference frame: the progress reference frame, offers historical performance data as a point of comparison and the social reference frame offers aggregated average peer group performance data as a point of comparison. Results show that participants who receive a progress reference frame are likely to spend less time reviewing their dashboard than those who receive a social reference. However, those who receive a progress reference frame are more likely to spend more time reviewing detailed task feedback and engaging with the learning analytics dashboard.

Immersive technologies aim to improve crucial process and safety training by increasing motivation, engagement and skills development. A Systematic Literature Review (SLR) was performed to identify immersive technologies applications that have been published in the past twenty years and aimed to enhance the training and learning of operators in the process industry, with special emphasis on the chemical industry. A set of 44 articles was obtained following the PRISMA framework with backward and forward snowballing. They were examined based on type of training, industry and technology. Only very few studies (10 out of 44) reported a comparison of immersive and traditional training. Six performance indicators (time; number of: mistakes, hints and instruction repetitions; events and equipment identification) were named to evaluate the immersive experience. To allow for a consistent analysis of the quality of immersive training in future studies, an effectiveness-efficiency model from the trainee viewpoint is proposed. (C) 2022 Published by Elsevier Ltd.

Although modern consumer level head-mounted-displays of today provide high-quality room scale tracking, and thus support a high level of immersion and presence, there are application contexts in which constraining oneself to seated set-ups is necessary. Classroom sized training groups are one highly relevant example. However, what is lost when constraining cybernauts to a stationary seated physical space? What is the impact on immersion, presence, cybersickness and what implications does this have on training success? Can a careful design for seated virtual reality (VR) amend some of these aspects? In this line of research, the study provides data on a comparison between standing and seated long (50–60 min) procedural VR training sessions of chemical operators in a realistic and lengthy chemical procedure (combination of digital and physical actions) inside a large 3-floor virtual chemical plant. Besides, a VR training framework based on Maslow's hierarchy of needs (MHN) is also proposed to systematically analyze the needs in VR environments. In the first of a series of studies, the physiological and safety needs of MHN are evaluated among seated and standing groups in the form of cybersickness, usability and user experience. The results (n=32, real personnel of a chemical plant) show no statistically significant differences among seated and standing groups. There were low levels of cybersickness along with good scores of usability and user experience for both conditions. From these results, it can be implied that the seated condition does not impose significant problems that might hinder its application in classroom training. A follow-up study with a larger sample will provide a more detailed analysis on differences in experienced presence and learning success.

Operator training in the chemical industry is important because of the potentially hazardous nature of procedures and the way operators' mistakes can have serious consequences on process operation and safety. Currently, operator training is facing some challenges, such as high costs, safety limitations and time constraints. Also, there have been some indications of a lack of engagement of employees during mandatory training. Immersive technologies can provide solutions to these challenges. Specifically, virtual reality (VR) has the potential to improve the way chemical operators experience training sessions, increasing motivation, virtually exposing operators to unsafe situations, and reducing classroom training time. In this paper, we present research being conducted to develop a virtual reality training solution as part of the EU Horizon 2020 CHARMING Project, a project focusing on the education of current and future chemical industry stakeholders. This paper includes the design principles for a virtual reality training environment including the features that enhance the effectiveness of virtual reality training such as game-based learning elements, learning analytics, and assessment methods. This work can assist those interested in exploring the potential of virtual reality training environments in the chemical industry from a multidisciplinary perspective.

The Integrated Gasification Combined Cycle (IGCC) possesses a number of advantages over traditional power generation plants, including increased efficiency, flex-fuel, and carbon capture. A lesser-known advantage of the IGCC system is the ability to coordinate with the smart grid. The idea is that process modifications can enable dispatch capabilities in the sense of shifting power production away from periods of low electricity price to periods of high price and thus generate greater revenue. The work begins with a demonstration of Economic Model Predictive Control (EMPC) as a strategy to determine the dispatch policy by directly pursuing the objective of maximizing plant revenue. However, the numeric nature of EMPC creates an inherent limitation when it comes to process design. Thus, Economic Linear Optimal Control (ELOC) is proposed as a surrogate for EMPC in the formulation of the integrated design and control problem for IGCC power plants with smart grid coordination.