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In the United States, the Next Generation Science Standards advocate for the integration of computational thinking (CT) as a science and engineering practice. Additionally, there is agreement among some educational researchers that increasing opportunities for engaging in computational thinking can lend authenticity to classroom activities. This can be done through introducing CT principles, such as algorithms, abstractions, and automations, or through examining the tools used to conduct modern science, emphasizing CT in problem solving. This cross-case analysis of nine high school biology teachers in the mid-Atlantic region of the United States documents how they integrated CT into their curricula following a year-long professional development (PD). The focus of the PD emphasized data practices in the science teachers' lessons, using Weintrop et al.'s definition of data practices. These are: (a) creation (generating data), (b) collection (gathering data), (c) manipulation (cleaning and organizing data), (d) visualization (graphically representing data), and (e) analysis (interpreting data). Additionally, within each data practice, teachers were asked to integrate at least one of five CT practices: (a) decomposition (breaking a complex problem into smaller parts), (b) pattern-recognition (identifying recurring similarities in data practices), (c) algorithms (the creation and use of formulas to predict an output given a specific input), (d) abstraction (eliminating detail in order to generalize or see the "big picture"), and (e) automation (using computational tools to carry out specific procedures). Although the biology teachers integrated all CT practices across their lessons, they found it easier to integrate decomposition and pattern recognition while finding it more difficult to integrate abstraction, algorithmic thinking, and automation. Implications for designing professional development experiences are discussed.

There is substantial research in science education about students', teachers', and scientists' views of nature of science (NOS). Many studies have used NOS frameworks that focus on particular ideas such as tentativeness of scientific knowledge and cultural embeddedness of science. In this paper, we investigate NOS from the perspective of the Family Resemblance Approach (FRA) which considers clusters of ideas about science in terms of categories that offer a comprehensive analytical lens to studying NOS views. The empirical study re-analyzes NOS views obtained from 7 and 8th grade students, science teachers, and scientists using the FRA lens. Statements from all three groups were obtained using a free-write questionnaire on nature of knowledge and nature of knowing. The statements were reclassified using the FRA framework. Epistemic network analysis (ENA) was applied to the statements produced by each group of participants, and the resulting network models were interpreted and compared. The results show that student and teacher network models possessed no central idea, and more tangible ideas about science were frequently connected. Scientist network models showed more connections across their statements which indicate a higher degree of agreement and coherence among a variety of ideas compared to student and teacher network models. The paper discusses the findings as well as the methodological contributions, and concludes with implications for future research.

A key process in the discipline of science is argumentation, which has recently been receiving more attention in K-12 classrooms. The purpose of this multiple case study was to concurrently examine self-regulated learning processes (SRL) and learning outcomes of three teachers in a professional development (PD) on argumentation in science to assess the relationship between types of learning processes employed by teachers and corresponding learning outcomes. Three teacher cases were selected based on variations in their self-efficacy for the PD, the type of schools in which they taught, and their experiences with argumentation in science. Teachers who were able to use SRL strategies had deeper learning outcomes and created lesson plans that engaged students in higher levels of argumentation. It was found that the SRL microanalysis was useful in eliciting learning processes for learners and provided opportunities for learners to be more aware of their SRL practices. Implications for this study include ways to measure learning processes and learning outcomes concurrently to provide more effective PD instruction.

In an effort to deepen learning in K-12 science classrooms, there has been a national movement to integrate computational thinking (CT). The purpose of this phenomenographic study was to understand teachers' perceptions of the function and usefulness of a task analysis and a decision tree tool designed to help them with integration. Teachers participated in a long-term professional development to improve their knowledge and application of CT and then developed lesson plans integrating CT into science investigations. To assist in the integration, teachers used the two unique tools. No one lesson plan or content area addressed all of the CT practices, but all CT practices were addressed in lessons across all four science areas. All 19 teachers found that the task analysis tool helped them to shift their lessons to a student-centered focus and helped them pinpoint data practices so they could systematically integrate CT practices. However, they expressed confusion over the amount of detail to document on the tool. Similarly, teachers found both benefits and barriers to the decision tree tool. Teachers found the decision tree tool to be useful in predicting the ways students may misunderstand a data practice and in reflecting on the level of accomplishment of students. However, teachers were sometimes uncertain with how to efficiently document complex student behaviors when engaged with data practices and CT. Implications for the use of the two lesson planning tools is discussed.

In an attempt to broaden participation in STEM, a new type of high school is emerging, high schools which include a focus on engineering, have few or no academic admission criteria, and actively involve students of all levels of ability, known as Inclusive STEM High Schools (ISHSs). One aspect of successful ISHSs includes the intentional and explicit integration of engineering learning opportunities into coursework. The purpose of this paper is to report results of a systematic cross-case analysis exploring the extent of engineering learning opportunities in five exemplar ISHSs. The results are framed by the "Engineering in K-12 Education" report from which seven different topics were derived to appropriately represent the field of engineering in schools: design, identifying constraints, modeling and analysis, engineering habits of mind, systems thinking, modeling, identifying constraints, communication, and optimization. The cross-case analysis was conducted by aggregating the information gathered through surveys, interviews, focus groups, classroom observations, and document analysis, noting similarities and differences across schools and mechanisms for the course foci. It was found in the participating ISHSs that engineering is not merely an elective; all students must take at least one engineering course to graduate, although the states in which the schools are located did not require engineering for a diploma. The most prominent topics from the recommended list found at the schools were design, engineering habits of mind, and communication, while the least prominent were modeling, analysis, and identifying constraints. Based on the results of this study, the engineering education community is encouraged to continue making engineering concepts and skills accessible to K-12 educators, who may not have prior formal training in the field of engineering or engineering education.

In-depth understanding of nature of science (NOS) moves beyond knowledge of discrete NOS aspects to consider connections among NOS aspects. This study presents three teacher cases pre to post a nature of science graduate course to explore the potential of an innovative analytic approach that focuses on the connections individual learners make among NOS aspects, using individual epistemic network analysis (iENA). Participants' pre- and post-course Views of Nature of Science (VNOS) responses were analyzed using both traditional ratings of individual aspects as naïve, transitional, or informed. Then, the responses were coded for NOS connections, which were then modeled using iENA. Compared to traditional VNOS ratings of separate NOS aspects, iENA-based network models added association levels and clustering of NOS aspects. This clarified differences among the participants. Participants' post-course models showed more and more highly associated NOS aspects and increased clustering of NOS aspects, indicating more in-depth and integrated understandings. Additional improvements were recognized beyond those identified through traditional VNOS analysis for one participant who began the course with mostly informed understandings. Consideration of connections may be crucial to guide more effective interventions.

This instrumental case study of Manor New Tech High (MNTH) provides insight and understanding of a trend in U.S. education to create new STEM schools and increase the achievement of students underrepresented in STEM. MNTH was an inclusive, STEM-focused high school, in Manor, Texas. The creation of the school was stimulated by a statewide Texas STEM education policy initiative, seed money from private foundations, and local community support. MNTH was chosen for this study because of its diverse student population and reputation as a successful, innovative STEM school. The case provides an in-depth look at the school's design, implementation, and outcome dimensions, in context. Ten candidate critical components framed the study and illuminate opportunity structures for MNTH students as they learned STEM and built social capital. MNTH implemented a project-based learning instructional environment, ubiquitous integration of technology, and a strong STEM curriculum. Teachers collaborated to create innovative curriculum and instruction, led by an energetic, well-connected principal. A robust network of student supports helped to ensure that students attained the skills and confidence in STEM and for college admission. The positive school culture promoted a sense of family, and the STEM focus enabled acquisition of 21st century skills.

The development of inclusive STEM high schools that have no academic admission requirements has been a national goal in the United States. However, there is no umbrella organization that gives guidance for structuring such schools. The purpose of this study was to develop and validate a self-assessment using critical components of successful inclusive STEM high schools for school personnel and educational researchers who wish to better understand their STEM programs and identify areas of strength. A multi-phase methodology was employed. In the first step, eight in-depth case studies were generated, and common themes were identified. In the second step, inventory items were iteratively generated and tested for reliability and validity, using a sample of 78 teachers and researchers in five schools. In the third step, the inventory was field-tested in a single school. The OSPRI inventory demonstrates strong content validity and reliability. Teachers and researchers generally responded similarly, although some differences emerged that are indicative of their respective experiences and perspectives. School stakeholders and educational researchers can use this inventory, in whole or in part, to better understand their STEM programs and establish a future agenda that best capitalizes on their strengths.

Increasingly, STEM focused high schools are used prepare students for college STEM majors and launch them into STEM careers. Yet a new focus on STEM education at the elementary levels suggests that the importance of STEM education is much broader than a preparation for workforce needs in high school or college. This paper describes a case study designed to articulate the mission and design of an effective and nationally recognized STEM-focused elementary school. As described through the six most impactful components of STEM-focused elementary school design at Walter Bracken STEAM Academy, the case study emphasizes the school's strong and inclusive school leadership, with staff organized into grade level groups empowered to innovate and honing their teaching practices. External partnerships are leveraged to broaden student learning opportunities. Students at Bracken engage in active learning opportunities and multidisciplinary lessons where STEM is used as a way of thinking and as a way to coherently combine content into active learning opportunities that are engaging for learners. By organizing the structural components of an exemplary STEM-focused elementary school, we hope to deliver actionable reforms for elementary schools wanting to increase their STEM-focused offerings.

An understanding of how science is enacted and how scientific knowledge is generated, or the nature of science (NOS), is a major goal of science education. NOS views have almost exclusively been assessed using the Views of Nature of Science (VNOS) suite of instruments, which consists of open-ended questions. The purpose of this study was to investigate the utility of performing an Epistemic Network Analysis (ENA) from VNOS-B responses, using the group as the unit of analysis. Traditional scoring of the VNOS responses demonstrated that overall, participants shifted from emerging to more sophisticated views across all elements. An ENA provided a quick visualization of how participants connected NOS ideas. With regard to accuracy of participants' NOS understandings as a group, findings from traditional VNOS analysis and ENA converged on two main points, improvement of overall quality of knowledge and the identification of missing elements of NOS from responses. Some changes in participants' NOS understanding were identifiable in results from only the ENA. For example, prior to instruction, ENA showed three naive ideas about empiricism. After instruction, no naive statements remained in the responses about the empirical nature of science. ENA extends the traditional VNOS analysis by enabling the pinpointing of particular ideas that are meaningful to the group, indicating clusters of ideas that are related, and illustrating the way informed, transitional and naïve ideas intermingle.