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The NetEthics Educational Case Study Collection was developed as part of a project funded by the National Science Foundation (NSF) on "NetEthics: Building Tools & Training to Advance Responsible Conduct in Complex Research Networks Pioneering Novel technologies"(NSF award 2220611). This project has focused on the ethical challenges arising in large, multi-institutional, and frequently multidisciplinary research networks such as NSF-funded Engineering Research Centers (ERCs). This project developed educational case studies that research networks could use and adapt to foster consideration and understanding of key ethical issues arising in these networks. The case study collection aims to strengthen ethical reflection and responsible conduct of research (RCR) in these large and complex research networks. Such networks face unique ethical challenges that are not well addressed by traditional ethics frameworks, which tend to focus on either individual researcher responsibilities or broad societal impacts. The project team developed four educational case studies to support ethics and RCR at the network level. These case studies are fictional but address critical issues in collaborative research networks: (1) data sharing across the network, (2) credit and authorship in multi-team publications, (3) navigating ethics and regulatory frameworks, and (4) fostering effective collaboration within the network. We developed these cases by using analytic and empirical methods to identify key issues in network research. We then piloted a subset of cases in workshops with ERC participants, leading to refinements in all four cases. The cases are designed to be used easily – each case is succinct but can support rich discussion and reflection in a discussion session of an hour or more, either in person or virtually (e.g., through Zoom). These case studies aim to encourage discussion of ethical issues in network research, providing a tool that network participants and leaders can use to advance a culture and climate committed to ethical and responsible research. 

Studies have shown that students often struggle to solve quantitative science problems because they fail to make connections between mathematical equations and associated scientific phenomena. This struggle has been attributed to instructors providing limited sensemaking opportunities that connect science and mathematics sensemaking. Our prior research on college instructors teaching population growth shows that the types of sensemaking elicited varied and were organized in different ways. This case study extends the research by exploring sensemaking opportunities about mathematical equations provided by three instructors teaching Gibbs free energy. This study also examines different levels of connection between sensemaking types within and across the science and mathematics dimensions and analyzes factors (i.e., pedagogical approaches, equation types) that might shape the types of sensemaking that were provided. The Sci-Math Sensemaking Framework was used to identify sensemaking opportunities provided by three instructors during the lessons and a comparative case study approach was employed. Findings showed that while each instructor provided both science and mathematics sensemaking opportunities, they had distinct ways of sequencing their sensemaking even when teaching the same scientific phenomenon using mathematical equations. Mathematics sensemaking was mostly presented separately from science sensemaking, with only a few instances of connected sensemaking occurring in instructors’ lessons, albeit at varying levels. When instructors expose students to connected science and mathematics sensemaking, they model for students how to use resources from two different disciplines to understand scientific concepts or solve quantitative problems. We provide evidence to show that levels of connection between sensemaking types within science and mathematics dimensions reflect distinct approaches to developing more robust scientific explanations or to working with equations. Based on these case studies, we suggest that instructors’ equation choices and pedagogical approaches support specific types of sensemaking and levels of connection between sensemaking opportunities. 

Scientific research increasingly involves large, multidisciplinary teams networked across multiple institutions to develop new technologies. Despite the rise of complex research networks and big team science, there has been little analysis to date of the ethical challenges facing these networks. The extensive literature on the ethical issues confronting individual researchers and small teams (the micro level) and on the larger societal challenges flowing from research and new technology (the macro level) leave a troubling gap in between, at the meso level of the research network involved in big team science. Yet the ability of complex networks to conduct research ethically – which is essential if the results are to be deemed reliable and trustworthy – depends on recognizing the ethical issues that emerge at this intermediate network level, identifying the values that should guide networks in addressing those issues, and equipping research leaders to build a culture supporting the ethical conduct of research across the laboratories and institutions that comprise the network. This paper calls out the problem, analyzing the gap and recommending next steps. 

Abstract To address the lack of a classroom observation protocol aligned with integratedSTEM, the author team developed one to measure the degree of integratedSTEMinstruction implemented in K-12 science and engineering classrooms. This study demonstrates how our instrument can be used to uncover the dimensions of integratedSTEMinstruction practiced in K-12 classrooms and to determine which protocol items are associated with each of these dimensions. This article reports on the results of a principal component analysis (PCA) using 2030 K-12 classroom observation videos.PCArevealed two core dimensions of integratedSTEMeducation.Real-world problem-solvingincludes 21st century skills andSTEMpractices necessary for developing solutions to real-world problems.Nature of IntegratedSTEMincludes items that promote integration between the real-world context, students’ personal experiences,STEMcareers, andSTEMcontent. The authors’ analysis also suggests the possibility of an additional dimension of integratedSTEMinvolving technology practices inSTEM. 

Abstract Given the large variation in conceptualizations and enactment of K − 12 integrated STEM, this paper puts forth a detailed conceptual framework for K − 12 integrated STEM education that can be used by researchers, educators, and curriculum developers as a common vision. Our framework builds upon the extant integrated STEM literature to describe seven central characteristics of integrated STEM: (a) centrality of engineering design, (b) driven by authentic problems, (c) context integration, (d) content integration, (e) STEM practices, (f) twenty-first century skills, and (g) informing students about STEM careers. Our integrated STEM framework is intended to provide more specific guidance to educators and support integrated STEM research, which has been impeded by the lack of a deep conceptualization of the characteristics of integrated STEM. The lack of a detailed integrated STEM framework thus far has prevented the field from systematically collecting data in classrooms to understand the nature and quality of integrated STEM instruction; this delays research related to the impact on student outcomes, including academic achievement and affect. With the framework presented here, we lay the groundwork for researchers to explore the impact of specific aspects of integrated STEM or the overall quality of integrated STEM instruction on student outcomes. 

The STEM teacher workforce in the United States has faced a host of pressing challenges, including teacher shortages, pervasive job dissatisfaction, and high turnover, problems largely attributable to working conditions within schools and districts. These problems have been exacerbated in high-needs districts with fewer resources and more students from low-income communities. Since social network research has shown that workplace relationships are vital for retention, this study investigates the demographic and relational antecedents to what we dub ties of retention. We explore how demographic and relational properties affect the likelihood that teachers have “retention-friendly” networks, characterized by connections important for retention. Our analysis of data from a sample of 120 STEM teachers across five geographic regions identifies key demographics (i.e., site, gender, career changer, and prior teaching experience) and relational properties (network size, positive affect, and perceptions of bridging) associated with ties of retention. We discuss the implications of our findings for the STEM teacher workforce and for teacher education programs. 

Abstract Background Teacher communities of practice, identity, and self-efficacy have been proposed to influence positive teacher outcomes in retention, suggesting all three may be related constructs. Qualitative studies of communities of practice can be difficult to empirically link to identity and self-efficacy in larger samples. In this study, we operationalized teacher communities of practice as specific networks related to teaching content and/or pedagogy. This scalable approach allowed us to quantitatively describe communities of practice and explore statistical relationships with other teacher characteristics. We asked whether these community of practice networks were related to identity and self-efficacy, similar to other conceptualizations of communities of practice. Results We analyzed survey data from 165 in-service K-12 teachers prepared in science or mathematics at 5 university sites across the USA. Descriptive statistics and exploratory factor analyses indicated that math teachers consistently reported smaller communities of practice and lower identity and self-efficacy scores. Correlations revealed that communities of practice are more strongly and positively related to identity than self-efficacy. Conclusion We demonstrate that teacher communities of practice can be described as networks. These community of practice networks are correlated with teacher identity and self-efficacy, similar to published qualitative descriptions of communities of practice. Community of practice networks are therefore a useful research tool for evaluating teacher characteristics such as discipline, identity, self-efficacy, and other possible outcomes (e.g., retention). These findings suggest that teacher educators aiming to foster strong teacher identities could develop pre-service experiences within an explicit, energizing community of practice. 

National Science Foundation (NSF) funded Engineering Research Centers (ERC) must complement their technical research with various education and outreach opportunities to: 1) improve and promote engineering education, both within the center and to the local community; 2) encourage and include the underrepresented populations to participate in Engineering activities; and 3) advocate communication and collaboration between industry and academia. ERCs ought to perform an adequate evaluation of their educational and outreach programs to ensure that beneficial goals are met. Each ERC has complete autonomy in conducting and reporting such evaluation. Evaluation tools used by individual ERCs are quite similar, but each ERC has designed their evaluation processes in isolation, including evaluation tools such as survey instruments, interview protocols, focus group protocols, and/or observation protocols. These isolated efforts resulted in redundant resources spent and lacking outcome comparability across ERCs. Leaders from three different ERCs led and initiated a collaborative effort to address the above issue by building a suite of common evaluation instruments that all current and future ERCs can use. This leading group consists of education directors and external evaluators from all three partners ERCs and engineering education researchers, who have worked together for two years. The project intends to address the four ERC program clusters: Broadening Participation in Engineering, Centers and Networks, Engineering Education, and Engineering Workforce Development. The instruments developed will pay attention to culture of inclusion, outreach activities, mentoring experience, and sustained interest in engineering. The project will deliver best practices in education program evaluation, which will not only support existing ERCs, but will also serve as immediate tools for brand new ERCs and similar large-scale research centers. Expanding the research beyond TEEC and sharing the developed instruments with NSF as well as other ERCs will also promote and encourage continual cross-ERC collaboration and research. Further, the joint evaluation will increase the evaluation consistency across all ERC education programs. Embedded instrumental feedback loops will lead to continual improvement to ERC education performance and support the growth of an inclusive and innovative engineering workforce. Four major deliveries are planned. First, develop a common quantitative assessment instrument, named Multi-ERC Instrument Inventory (MERCII). Second, develop a set of qualitative instruments to complement MERCII. Third, create a web-based evaluation platform for MERCII. Fourth, update the NSF ERC education program evaluation best practice manual. These deliveries together will become part of and supplemented by an ERC evaluator toolbox. This project strives to significantly impact how ERCs evaluate their educational and outreach programs. Single ERC based studies lack the sample size to truly test the validity of any evaluation instruments or measures. A common suite of instruments across ERCs would provide an opportunity for a large scale assessment study. The online platform will further provide an easy-to-use tool for all ERCs to facilitate evaluation, share data, and reporting impacts. 

There is currently a severe shortage of teachers in the U.S. workforce. The problem is especially acute among science, technology, engineering, and mathematics (STEM) teachers and exacerbated by high turnover among new teachers—those with less than 5 years of teaching experience. In this article, the authors investigate one piece of the puzzle. The authors model a social cognitive approach to understanding self-efficacy, a key precursor to job performance and retention. Their interactionist approach accounts for both demographic (i.e., gender and age) and relational variables (i.e., social networks). The authors test their ideas on a sample of 159 STEM teachers across five geographic regions in the United States. Their analysis reveals patterned differences in self-efficacy across gender that are contingent on the communities of practice in which the teachers are embedded. Together, their theory and findings highlight the value of taking a holistic, interactionist view in explaining STEM teacher self-efficacy.