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During design, different forms of reasoning shape the designers’ decision-making. As a result, the ability to fluently transition across various forms of reasoning is essential. The purpose of this study is two-fold: first is to introduce and explain the concept of Semantic Fluency in Design Reasoning, as the ability to transition across multiple forms of reasoning fluently. To identify these transitions, this study used the Design Reasoning Quadrants framework, which represents four quadrants: experiential observations (reasoning based on observations and experiences), trade-offs (reasoning recognizing multiple competing design requirements), first-principles (reasoning requiring disciplinary understandings), and complex abstractions (reasoning in envisioning new situations). The second purpose of this study is to illustrate semantic fluency in a design review conversation. We selected and presented three different forms of transitions identified through our analysis of conversations between students and design reviewers. Our analysis revealed evidence of semantic fluency in young designers. Mike, one of the students, demonstrated fluency across three quadrants (experiential observations, trade-offs, and first-principles). Lisa and David demonstrated two-quadrant transitions. Lisa had fluency from experiential observations to trade-offs, and David transitioned from experiential observations to first-principles. We recommend the intentional use of design reviews to elicit student reasoning in design and adoptmore »questioning strategies to promote fluency across different forms of design reasoning.« less

https://www.nsta.org/connected-science-learning/connected-science-learning-march-april-2022/data-driven-science-vlogging

During the COVID-19 pandemic, many students lost opportunities to explore science in labs due to school closures. Remote labs provide a possible solution to mitigate this loss. However, most remote labs to date are based on a somehow centralized model in which experts design and conduct certain types of experiments in well-equipped facilities, with a few options of manipulation provided to remote users. In this paper, we propose a distributed framework, dubbed remote labs 2.0, that offers the flexibility needed to build an open platform to support educators to create, operate, and share their own remote labs. Similar to the transformation of the Web from 1.0 to 2.0, remote labs 2.0 can greatly enrich experimental science on the Internet by allowing users to choose and contribute their subjects and topics. As a reference implementation, we developed a platform branded as Telelab. In collaboration with a high school chemistry teacher, we conducted remote chemical reaction experiments on the Telelab platform with two online classes. Pre/post-test results showed that these high school students attained significant gains (t(26)=8.76, p<0.00001) in evidence-based reasoning abilities. Student surveys revealed three key affordances of Telelab: live experiments, scientific instruments, and social interactions. All 31 respondents were engagedmore »by one or more of these affordances. Students behaviors were characterized by analyzing their interaction data logged by the platform. These findings suggest that appropriate applications of remote labs 2.0 in distance education can, to some extent, reproduce critical effects of their local counterparts on promoting science learning.« less

Digital sensors allow people to collect a large quantity of data in chemistry experiments. Using infrared thermography as an example, we show that this kind of data, in conjunction with videos that stream the chemical phenomena under observation from a vantage point, can be used to construct digital twins of experiments to support science education on the cloud in a visual and interactive fashion. Through digital twins, a significant part of laboratory experiences such as observation, analysis, and discussion can be delivered on a large scale. Thus, the technology can potentially broaden participation in experimental chemistry, especially for students and teachers in underserved communities who may lack the expertise, equipment, and supplies needed to conduct certain experiments. With a cloud platform that enables anyone to store, process, and disseminate experimental data via digital twins, our work also serves as an example to illuminate how the movement of open science, which is largely driven by data sharing, may be powered by technology to amplify its impacts on chemistry education.

Abstract This position paper is motivated by recent educational reform efforts that urge the integration of engineering in science education. We argue that it is plausible and beneficial to integrate engineering into formal K-12 science education. We illustrate how current literature, though often implicitly, discusses this integration from a pedagogical, epistemological, or methodological argumentative stance. From a pedagogical perspective, a historically dominant argument emphasizes how engineering helps make abstract science concepts more concrete. The epistemological argument is centered on how engineering is inherently interdisciplinary and hence its integrative role in support of scientific literacy and more broadly STEM literacy is natural. From a methodological perspective, arguments focus on the engineering design process, which is compatible with scientific inquiry and adaptable to answering different types of engineering questions. We call for the necessity of spelling out these arguments and call for common language as science and engineering educators form a research-base on the integration of science and engineering. We specifically provide and discuss specific terminology associated with four different models, each effectively used to integrate engineering into school science. We caution educators against a possible direction towards a convergence approach for a specific type of integrating engineering and science. Diversity inmore »teaching models, more accurately represents the nature of engineering but also allows adaptations based on available school resources. Future synthesis can then examine student learning outcomes associated with different teaching models.« less