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This exploratory study compares how young people (ages 15-16) learn circuitry concepts and layout design principles important to electrical engineering using one of two educational circuitry toolkits: paper circuits and traditional solderless breadboards. Paper-based prototyping kits are representative of a trend that incorporates new materials and approaches to integrating arts into traditional STEM disciplines. Extending prior research on how non-traditional toolkits enhance learning of electrical engineering outcomes, including basic circuitry concepts (i.e., current flow, polarity, and connections), this study examines the material affordances and design choices of the kits that contribute to youth's understanding of more advanced circuitry layout design principles, including space allocation, placement of electronic components, and routing. Results indicate that paper circuits better afford the learning of layout design principles for printed circuit boards (PCBs) with large effect sizes. This study illuminates how the materials of educational toolkits uniquely solicit body- and material-syntonic patterns of activity, and thus differentially engage learners' powerful ideas around circuitry and design principles. This investigation encourages careful consideration of the material affordances of some toolkits over others for learning purposes.

Industrial process heat decarbonization through electrification could contribute significantly to climate change mitigation efforts. In the US industry, thermal processes accounted for more than two-thirds of the total final energy demand in 2021. Cross-cutting electrification technologies like industrial heat pumps are suitable for the process heat supply to several industrial unit operations in a sustainable way while also improving overall energy efficiency. This study employs a bottom-up approach to investigate the techno-enviro-economic potentials of deploying high-temperature and steam-generating heat pumps in US textile, pulp and paper, and automotive sectors in different timeframes. The results show that the annual technical potential energy and CO2 savings by electrifying heat supply are 310 PJ (or 36% of the projected energy demand) and 28 MtCO2 (or 71% of the projected CO2 emissions) in 2050 respectively, however, these incur additional costs in each sector (ranging between 5 and 18 $/GJ). The required heating capacity of industrial heat pumps is estimated at 15 GW, which translates roughly into a market of over 6000 heat pump units and an investment volume of $7 billion in the studied processes. Although there may be individual cost-effective opportunities for electrifying heat supply in specific industrial sites, the overall costs are estimated to be high in the three industrial sectors due to the large disparity between electricity and natural gas prices and low heat source temperatures. To overcome the identified techno-economic barriers, comprehensive action plans for different stakeholders are also given. This study provides novel insights that should inform policymakers’ and executives’ decisions about the electrification of the current and future US industrial heat supply in relevant industrial sectors.

The development of highly specific biomimetic recognition material is a challenge for rapid detection of harmful residues in foodstuff. In this study, a paper-based boronate affinity metal-organic framework/molecularly imprinted polymer microfluidic chip (FZS-BA@MIP) was constructed based on the in situ construction strategy, which was also designed as a highly specific biomimetic recognition module. Here, the homogeneous zeolitic imidazole framework-8 (ZIF-8) membrane served as a great scaffold and enrichment layer. Besides, the recognition layer of MIP was prepared based on a highly oriented boronate affinity surface imprinting strategy. With the aid of the liquid flow channel, the highly specific enrichment and visual detection for antibiotic residues like kanamycin in actual products were achieved on the paper chip module of an integrated lateral flow platform. The whole analysis process could be accomplished within 30 min. In brief, this study offered a new integrated biomimetic recognition platform for visually detecting harmful veterinary residues containing cis-diols, which demonstrated promising commercial value in point-of-care testing of foodborne hazardous compounds.

Background: To accurately measure students' science, technology, engineering and mathematics (STEM) career interest, researchers must get inside the 'black box' to understand students' conceptualizations of STEM careers., Aims: The aim of Study 1 was to explore whether students' conceptualizations of STEM included medical careers. The aim of Study 2 was to explore whether predictors of STEM career interest (e.g., gender and motivation) varied by STEM definition (inclusion/exclusion of medical careers)., Samples: In Study 1, the sample was US college students (N = 125) who were mostly White (80%). In Study 2, the sample was US 10th-grade high school students (N = 455) who were mostly Black (79%)., Methods: In Study 1, students completed an online questionnaire. In Study 2, students completed various measures of math achievement, motivation (science and math expectancies of success, interest and importance value) and career interest with an importance., Results: In Study 1, medical careers were less often classified as STEM careers than traditional STEM careers, but more often classified as STEM than non-STEM careers. In Study 2, science importance value was the only motivational predictor of students' STEM+Medicine career interest, and no motivation constructs predicted traditional STEM career interest. Boys expressed greater interest in traditional STEM careers, while girls expressed greater interest in STEM+Medicine careers., Conclusions: Students' conceptualizations of STEM are not binary. Thus, we recommend researchers are explicit about their definition of STEM with study participants, in their coding and in their publications., (© 2023 British Psychological Society.)

The integration of online platforms in (bio)chemical engineering education has increasingly become a matter of fact at all educational levels. Examples such as virtual laboratories in tertiary education have shown their benefits, such as the decreased cost and resources needed as well as providing a safer environment for practical experimentation. However, students or stakeholders are not usually involved in developing the virtual laboratory, even if, when given the opportunity, they can provide valuable feedback for improvement and acquire ownership over the platform. Hence, when proposing a novel educational process virtual laboratory that targets teaching bioprocess modeling to undergraduate students, the best approach is to involve the students in the development as its future users. To this end, in this work, four co-participatory design experiences are presented that show the journey from a paper prototype to an online educational virtual laboratory (www.biovl.com). Qualitative and quantitative data have been collected in two different universities through surveys, semi-structured interviews, and informal conversations among the students and the developer. The students’ perspectives were found to provide valuable feedback about the platform’s content, usability, and functionality. For example, interest in adding bioprocess-related coding activities, or suggesting to change the platform name, were opinions collected and carefully considered. These suggestions can be easily integrated since the software is at the early stages of the virtual laboratory prototype. Although the usability and functionality features of the platform are under continuous advancement, this work’s findings show that the students are interested in contributing to the virtual laboratory’s development. Therefore, it opens the door to modifications and improvements, which are strongly based on the users’/students’ perceptions and perspectives as the virtual laboratory’s co-designers. Although the primary target of the BioVL prototype is to teach bioprocessing modelling, several advanced tools such as virtual and augmented reality (VR and AR) are being considered to be included at a future stage. Furthermore, the educational strategy proposed in this work can be replicated by those who want to develop other virtual laboratories.