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Abstract. The Vacuum-Assisted Resin Infusion Molding (VARIM) process is widely used in wind turbine blade manufacturing due to its cost-effectiveness and reliability. However, challenges such as prolonged curing cycles and defects caused by non-uniform cure remain persistent. To address these issues, multizone heating systems have been developed to enable independent temperature control across blade sections. Yet, optimizing the temperature profile in each zone is computationally intensive, requiring detailed modelling of curing kinetics and heat transfer mechanisms. To overcome these challenges, in this work, a machine learning (ML) based digital twin of the VARIM process was developed using a time-distributed long short-term memory (LSTM) network trained on data generated by a high-fidelity multiphysics solver. The model achieved a predictive accuracy of 96.7 % in replicating the resin curing behavior. Its time-distributed architecture effectively captures the spatial – temporal dependencies across multiple zones, allowing precise prediction of the degree-of-cure evolution. Paired with a gradient-free optimization algorithm, the digital twin reduced curing time by 12.5 % while improving cure uniformity. This AI-driven framework eliminates costly trial-and-error experimentation, and provides a scalable, adaptive solution for improving both quality and productivity in wind turbine blade manufacturing, with strong potential for extension to other composite manufacturing processes. 

In an age where artificial intelligence (AI) plays an increasingly pivotal role in daily life, it is essential to equip our youngest learners with foundational knowledge of AI. The AI by 8 project aims to empower kindergarten through second grade teachers in rural North Carolina by introducing AI concepts through engaging, unplugged activities integrated into English Language Arts (ELA) instruction. This initiative seeks to address the gap in AI education expertise among early childhood educators and seeks to foster a generation of students who are well-prepared to navigate a technology-driven future. We present in this poster the guiding theoretical framework for our work, outlining the objectives of the research-practice partnership, and our initial efforts at recruiting rural K-2 teachers. 

The Wind River Elementary Computer Science (WRECS) Collaborative is a research-practice partnership (RPP) among three school districts serving Eastern Shoshone and Northern Arapaho communities on the Wind River Reservation, the Wyoming Department of Education (WDE), BootUp Professional Development (BootUp PD), and the American Institutes for Research (AIR). The purpose of the WRECS Collaborative is to develop culturally sustaining elementary computer science (CS) education through integration of CS and Indigenous studies. The Collaborative engaged three cohorts of elementary educators in cycles of professional development, classroom implementation, and group reflection over the 2020-21, 2021-22, and 2022-23 school years. In this experience report, we share a set of reflections and lessons learned as the RPP developed relationships and worked through intersecting priorities, instructional goals, and ways of knowing and learning present within the RPP. 

Teacher shortages in K–12 computer science (CS) education negatively impact students’ access to CS courses, exposure to CS concepts, and interest in CS-related careers. To address CS teacher shortages, this study seeks to understand factors related to expressing a preference to teach CS among prospective teachers. The study team analyzed data from 27,700 prospective teacher applications accepted into the 2016–2020 Teach For America (TFA) corps (cohorts). The TFA corps is an alternative teacher development program that recruits and prepares participants to obtain their teaching certification while they work for at least two years in underserved communities on a temporary teaching license. Study results show that earning at least one postsecondary CS credit and majoring in CS are positively associated with these prospective teachers’ preference to teach CS. Findings indicate that among these accepted TFA applicants, a larger proportion of male applicants and racially minoritized applicants earned a postsecondary CS credit, majored in CS, and preferred to teach CS compared with female applicants and racially non-minoritized applicants. This study lays the foundation for future explorations of whether early exposure to CS could increase prospective teachers’ interest in teaching CS and reduce CS teacher shortages in K-12 settings. Findings from this study can also serve as a precursor to developing policies that result in a CS teacher workforce that is more representative of students enrolled in K-12 public schools. 

Three Northern Arapaho and Eastern Shoshone–serving districts formed a researcher–practitioner partnership with the Wyoming Department of Education, the American Institutes for Research®, and BootUp Professional Development to advance the computer science (CS) education of their elementary students in ways that strengthen their Indigenous identities and knowledges. In this paper, we share experiences from 2019 to 2022 with our curriculum development, professional development (PD), and classroom implementation. The researcher–practitioner partnership developed student and teacher materials to support elementary CS lessons aligned to Wyoming’s CS standards and “Indian Education for All” social studies standards. Indigenous community members served as experts to codesign culturally relevant resources. Teachers explored the curriculum resources during three 4-hour virtual and in-person PD sessions. The sessions were designed to position the teachers as designers of CS projects they eventually implemented in their classrooms. Projects completed by students included simulated interviews with Indigenous heroes and animations of students introducing themselves in their Native languages. Teachers described several positive effects of the Scratch lessons on students, including high engagement, increased confidence, and successful application of several CS concepts. The teachers also provided enthusiastic positive reviews of the ways the CS lessons allowed students to explore their Indigenous identities while preparing to productively use technology in their futures. The Wind River Elementary CS Collaborative is one model for how a researcher–practitioner partnership can utilize diverse forms of expertise, ways of knowing, and Indigenous language to engage in curriculum design, PD, and classroom implementation that supports culturally sustaining CS pedagogies in Indigenous communities. 

Prekindergarten to 12th-grade teachers of computer science (CS) face many challenges, including isolation, limited CS professional development resources, and low levels of CS teaching self-efficacy that could be mitigated through communities of practice (CoPs). This study used survey data from 420 PK–12 CS teacher members of a virtual CoP, CS for All Teachers, to examine the needs of these teachers and how CS teaching self-efficacy, community engagement, and sharing behaviors vary by teachers’ instructional experiences and school levels taught. Results show that CS teachers primarily join the CoP to gain high-quality pedagogical, assessment, and instructional resources. The study also found that teachers with more CS teaching experience have higher levels of self-efficacy and are more likely to share resources than teachers with less CS teaching experience. Moreover, teachers who instruct students at higher grade levels (middle and high school) have higher levels of CS teaching self-efficacy than do teachers who instruct lower grade levels (elementary school). These results suggest that CoPs can help CS teachers expand their professional networks, gain more professional development resources, and increase CS teaching self-efficacy by creating personalized experiences that consider teaching experience and grade levels taught when guiding teachers to relevant content. This study lays the foundation for future explorations of how CS education–focused CoPs could support the expansion of CS education in PK–12 schools. 

In fall 2019, the National Science Foundation awarded Southern Oregon University a two-year Computer Science for All Researcher Practitioner Partnership grant focused on integrating computational thinking (CT) into the K'5 instruction of general elementary and elementary bilingual teachers. This experience report highlights the process of transitioning one essential component of the project an elementary teacher summer institute (SI) from in-person to online due to COVID-19. This report covers the approach the team took to designing the SI to work virtually, the challenges encountered, the experiences of the 15 teachers involved through observations and surveys, and the opportunities for refinement. This report will be of potential interest for other computer science (CS) education researchers who also may be working with elementary teachers to incorporate CS and CT activities into their instruction. 

Abstract The Conoderinae (Coleoptera: Curculionidae) are one of the most distinctive Neotropical weevil groups in behaviour and appearance, attracting numerous hypotheses regarding the evolution and function of widespread apparent mimetic convergence. Conoderines have a poorly documented natural history, and a large fraction of the diversity of the group remains undescribed, presenting challenges to their study. In this analysis, 128 species of conoderine weevils previously or herein hypothesized to belong to three mimicry complexes are analysed in the first quantitative test of conoderine mimicry. Fifteen continuous and categorical characters describing the size, shape and coloration of these weevils were analysed using non-metric multidimensional scaling while statistically testing the resulting clusters in ordination space. Three similar, putatively mimetic complexes are recognized: (1) the ‘red-eyed fly’ complex of weevils, which are hypothesized to be evasively mimetic on various species of red-eyed flies; (2) the ‘striped/spotted’ complex, composed of weevils with a brightly coloured pronotum and red to white elytral stripes or spots; and (3) the ‘shiny blue’ complex of species with iridescent blue to blue–green pronotal scales. Each of these groups covers a wide geographical distribution and has evolved independently in multiple genera, although the red-eyed fly complex appears to be both the most species rich and widely distributed phylogenetically. Groupings were found to be statistically significant, although variation within each group suggests that the similarity in appearance of species in each group could be attributable to independent convergence on different, but phenotypically similar, models. Several avenues for future research on conoderine mimicry are discussed.