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Flexible manufacturing systems, such as Additive Manufacturing, Robotics and Computer Numerical Control (CNC) machines, can be readily deployed and operated in standard warehouse infrastructure providing the opportunity for the on-demand production of a wide variety of goods closer to their point of consumption. This has the potential to shift long-distance logistics towards raw material transport (which can be packed more tightly) and maximise the potential of zero-emission ‘last mile’ logistics. This paper reports a study to demonstrate the merits of Global Local (Glocal) supply chains in terms of the potential reductions in Greenhouse Gas Emissions (GHG). The study used the United Kingdom (UK) and its seven largest cities as the areas of supply and demand with material entering through Dover. The Monte-Carlo simulation showed that distributed production significantly outperforms single location manufacturing and product importing by up to 2-3x.

Artificial Intelligence (AI) is transforming how society works, from real-time classification mechanisms and enhanced patient diagnoses to large language models that can assist workers in real-time. With the increasing interest of the industry in digitising manufacturing, the role of AI will become even more important in promoting meaningful interactions among various stakeholders. This paper appraises AI manufacturing research from the lens of machine/process, human and system interaction. The results show that much of the literature has supported intra-machine/process and system-level interactions. Human-machine and machine-machine are less well-researched, and these require further investigation if society wishes to move to fully integrated Manufacturing Metaverse.

An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results produced using these methods often fail to link to theoretical concepts from the learning sciences, making them difficult for educators to trust, interpret and act upon. At the same time, many of our educational theories are difficult to formalise into testable models that link to educational data. New methodologies are required to formalise the bridge between big data and educational theory. This paper demonstrates how causal modelling can help to close this gap. It introduces the apparatus of causal modelling, and shows how it can be applied to well-known problems in LA to yield new insights. We conclude with a consideration of what causal modelling adds to the theory-versus-data debate in education, and extend an invitation to other investigators to join this exciting programme of research.

Discussion forums are often touted as maximising student participation and learning but concerns around engagement counter any perceived benefits. Often participation is the measure of engagement, and students who do not post are deemed unengaged. To further examine engagement and forums as learning communities, we used analytic data from 270 students enrolled in two online psychology subjects using social network analysis and interviewed 22 students. Both subjects' forums had greater egalitarian triads, indicative of reciprocal relationships. Furthermore, both active posters and lurkers had a mix of grade bands indicating that some lurkers still achieved academically. Lurking was a key qualitative theme along with checking for assessment information and intimidation. For both subjects, students were engaged with the forums, and differences in connectivity were consistent with the different subject content. However, forum activity indicated that these forums were more like subscription services than communities of practice. We propose that forums can be transformed into dynamic teaching spaces through understanding the multidimensionality of engagement, setting the expectation and tone of the forum as a safe place, and enhancing the platforms so visible indicators show that posts have been read or consumed. We further propose that students who engage but do not post be called "quiet participants." Implications for practice or policy: (1) Educators and researchers can improve the understanding of engagement with discussion forums by acknowledging the distinction between participation and engagement; (2) Online providers can assist in transforming these online platforms into dynamic teaching tools through enhancements that indicate a post has been read; and (3) Educators can increase engagement by setting the tone and expectations for the forum. Replacing the negative term "lurker" with quiet participants better reflects the activity of these students.

There is growing demand for online learning activities that offer flexibility for students to study anywhere, anytime, as online students fit study around work and family commitments. We designed a series of online activities and evaluated how, where, and with what devices students used the activities, as well as their levels of engagement and deep learning with the activities. A mixed-methods design was used to explore students' interactions with the online activities. This method integrated learning analytics data with responses from 63 survey, nine interview, and 16 focus group participants. We found that students used a combination of mobile devices to access the online learning activities across a variety of locations during opportunistic study sessions in order to fit study into their daily routines. The online activities were perceived positively, facilitating affective, cognitive, and behavioural engagement as well as stimulating deep learning. Activities that were authentic, promoted problem-solving, applied theory to real-life scenarios, and increased students' feelings of being supported were perceived as most beneficial to learning. These findings have implications for the future design of online activities, where activities need to accommodate students' need for flexibility as students' study habits become more mobile.

Novice design students struggle to engage with early stage design visualization tools such as sketching and prototyping. Instead students have a preference for designing with digital tools such as CAD modelling, motivated by inhibitions around sketching skill, which in turn leads to fixation and sunk cost effects. These behaviors present a barrier to engaging in typical practices of expert designers, namely idea fluency described as generating a wide range of ideas quickly and avoiding favoring one single idea. Noting the recent success of LEGO Serious Play in engaging non-designers in design activities in business and innovation contexts, we explore whether using LEGO as a visualization tool can trigger a behavior change in student designers towards idea fluency. This paper presents a study comparing student attitudes and design behavior when designing with LEGO, in comparison to sketching and cardboard modelling. Findings illustrate how LEGO's comparative low fidelity leads to students to be more willing to change and modify initial ideas, reduces inhibitions related to visual quality, and reinterpret and iterate designs. Based on these findings we illustrate how designing with LEGO can mitigate issues of inhibition, fixation, and sunk cost design behaviors concluding that LEGO can trigger behavior change toward idea fluency. As such we see compelling evidence to integrate LEGO as an educational design activity for novice designers used early in the design process to illustrate and trigger idea fluency.

Reducing stigma is a key benefit to intergenerational programs. However, little is known about the availability and suitability of measures that capture dementia-related attitudes in adolescents, thus limiting interpretations of the efficacy of such programs. The aim of this scoping review was to provide an overview of outcome measures used to capture dementia-related attitudes in adolescents. Scoping review methodology was used to systematically identify relevant articles. Key search terms included dementia, attitudes, and adolescents. Fourteen studies met the inclusion criteria, of which 13 unique measures were identified. However, there are gaps in psychometric properties and a lack of underlying theoretical frameworks. [ABSTRACT FROM AUTHOR]

This paper demonstrates the unpredictability of outcomes that result from compounding variabilities when using generative design (GD) coupled with additive manufacturing (AM). AM technologies offer the greatest design freedom and hence are most able to leverage the full capability of generative design (GD) tools and thus maximize potential improvements, such as weight, waste and cost reduction, strength, and part consolidation. Implicit in all studies reported in the literature is the fundamental assumption that the use of GD, irrespective of user experience or approach followed, yields high-performing and/or comparable design outputs. This work demonstrates the contrary and shows that achieving high performance with GD tools requires careful consideration of study setup and initial conditions. It is further shown that, when coupled with the inherent variability of AM parts, the potential variation in the performance of the design output can be significant, with poorer designs achieving only a fraction of that of higher-performing designs. This investigation shows how AM by Material Extrusion (MEX), which is used to manufacture components with polylactic acid (PLA), varies through different design pathways, bridging MEX and GD. Through a practical study across nine independently generated designs, the breadth of performance—due to initial GD conditions and MEX part strength unpredictability—is shown to reach 592%. This result suggest that current GD tools, including their underlying workflows and algorithms, are not sufficiently understood for users to be able to generate consistent solutions for an input case. Further, the study purports that training and consideration on GD setup are necessary to apply GD toolsets to achieve high-performing designs, particularly when applied in the context of MEX. [ABSTRACT FROM AUTHOR]