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Training complex skills is typically accomplished by means of a trainer or mediator who tailors instruction to the individual trainee. However, facilitated training is costly and labor intensive, and the use of a mediator is infeasible in remote or extreme environments. Imparting complex skills in applications like long-duration human spaceflight, military field operations, or remote medicine may require automated training algorithms. Virtual reality (VR) is an effective, easily programmable, immersive training medium that has been used widely across fields. However, there remain open questions in the search for the most effective algorithms for guiding automated training progression. This study investigates the effects of responsiveness, personalization, and subtask independence on the efficacy of automated training algorithms in VR for training complex, operationally relevant tasks. Thirty-two subjects (16M/16F, 18–54 years) were trained to pilot and land a spacecraft on Mars within a VR simulation using four different automated training algorithms. Performance was assessed in a physical cockpit mock-up. We found that personalization results in faster skill acquisition on average when compared with a standardized progression built for a median subject (p= 0.0050). The standardized progression may be preferable when consistent results are desired across all subjects. Independence of the difficulty adjustments between subtasks may lead to increased skill acquisition, while lockstep in the progression of each subtask increases self-reported flow experience (p= 0.01), fluency (p= 0.02), and absorption (p= 0.01) on the Flow Short Scale. Data visualization suggests that highly responsive algorithms may lead to faster learning progressions and higher skill acquisition for some subjects. Improving transfer of skills from training to testing may require either high responsiveness or a standardized training progression. Optimizing the design of automated, individually adaptive algorithms around the training needs of a group may be useful to increase skill acquisition for complex operational tasks. 

As several recent National Academies of Sciences reports have highlighted, greater science communication research is needed on 1) communicating chemistry, and 2) building research-practice partnerships to advance communication across science issues. Here we report our insights in both areas, gathered from a multi-year collaboration to advance our understanding of how to communicate about chemistry with the public. Researchers and practitioners from science museums across the U.S. partnered with academic social scientists in science communication to develop and conduct multi-strand data collections on chemistry communication and informal education. Our focus was on increasing interest in, the perceived relevance of, and self-efficacy concerning chemistry through hands-on activities and connecting chemistry to broader themes concerning everyday life and societal impacts. We outline challenges and benefits of the project that future collaborations can gain from and illustrate how our strands of work complemented each other to create a more complete picture of public perceptions of chemistry. 

While craft has had increasing influence on HCI research, HCI researchers tend to engage craft in limited capacities, often focusing on the juxtapositions of "traditional" craft and "innovative" computing. In this paper, we describe the structure and results of a six-week "experimental weaving residency" to show how HCI practitioners, engineers, and craftspeople perform similar work and can productively collaborate to envision new technological interfaces at early stages of development. We address both social and technical challenges of residencies and critically reflect on biases about technical and craft labor that we held prior to the residency. We share our experiences and lessons learned in the hopes of supporting future collaborations with craftspeople and broadening the techniques we use to address design challenges.