Title: Rethinking the classroom science investigation
Abstract There is now a significant research literature devoted to reconceptualizing scientific activities, such as modeling, explanation, and argumentation, to realize a vision of science‐as‐practice in classrooms. As yet, however, not all scientific practices have received equal attention.Planning and Carrying out Investigationsis one of the eight scientific practices identified in the Next Generation Science Standards, and there is a long line of research from both psychological and science education traditions that addresses topics about investigation, such as the generation and interpretation of evidence. However, investigation has not been subject to concerted reconceptualization within recent research and instructional design efforts focused on science‐as‐practice. In this article, we propose a framework that centers the investigation as a key locus for constructing alignments among phenomena, data, and explanatory models and makes visible the work that scientists engage in as they develop and stabilize alignments. We argue that these alignments are currently under‐theorized and under‐utilized in instructional environments. We explore four opportunities that we argue are both accessible to students from a young age and can support conceptual innovation. These are (a) developing empirical systems, (b) getting a grip on empirical systems, (c) determining, defining and operationalizing data as “evidence,” and (d) making sense of what the results of empirical systems do and do not help us understand. more »« less
Sutherland, Will; Neang, Andrew; Lee, Charlotte P
(, University of Hawaii Press)
Bui, Tung X
(Ed.)
Studies of research software development have focused on how to promote or encourage the adoption of software engineering practices, but we do not have a good empirical understanding of strategies that researchers have already begun to take in order to integrate those practices into research work in sustainable ways. We conduct a comparative case study of two research groups in different fields, and characterize two approaches that they have taken to get research software engineering work done: practice integration and differentiating expertise. From these findings we argue that examining outcomes of change in research software development practice is critical for understanding sustainability and the ramifications of such changes for scientific work.
Jaber, Lama_Z; Dini, Vesal; Hammer, David
(, Journal of Research in Science Teaching)
Abstract While research shows that responsive teaching fosters students' disciplinary learning and equitable opportunities for participation, there is yet much to know about how teachers come to be responsive to their students' experiences in the science classroom. In this work, we set out to examine whether and how engaging teachersas learnersin doing science may support responsive instructional practices. We draw on data from a year‐long blended‐online science professional development (PD) program that began with an emphasis on teachers' doing science and progressed to supporting their attention to their students' doing science. By analyzing videos from teachers' classrooms collected throughout the PD, we found that teachers became more stable in attending and responding to their students' thinking. In this article, we present evidence from teachers' reflections that this stability was supported by the teachers' intellectual and emotional experiences as learners. Specifically, we argue that engaging in extended scientific inquiry provided a basis for the teachers havingepistemic empathyfor their students—their tuning into and appreciating their students'intellectualandemotionalexperiences in science, which in turn supported teachers' responsiveness in the classroom.
Fujimura, Joan H; Holmes, Christopher J.
(, Sociological forum)
Scientific knowledge has been under attack recently, especially during and from the Trump administration. This article discusses the value of research in social studies of science in relation to scientific practice and post‐truth attacks on science. This literature analyzes the expert work and social values that enter into the production of evidence, the development and testing of methods, and the construction of theoretical and epistemological frames for connecting evidence, methods, and methodologies. Although researchers in this area argue that there are politics in science, this article demonstrates that their analyses of the processes of adjudicating evidence and epistemologies contribute to science. In contrast, post‐truth attacks on scientific expertise exemplify a particular kind of politics aimed at supporting a particular group's political and economic interests.
This paper examines how practicing teachers approach and evaluate students’ critical thinking processes in science, using the implementation of an online, inquiry-based investigation in middle school classrooms as the context for teachers’ observations. Feedback and ratings from three samples of science teachers were analysed to determine how they valued and evaluated component processes of students’ critical thinking and how such processes were related to their instructional approaches and student outcomes. Drawing from an integrated view of teacher practice, results suggested that practicing science teachers readily observed and valued critical thinking processes that aligned to goal intentions focused on domain content and successful student thinking. These processes often manifested as components of effective scientific reasoning—for example, gathering evidence, analysing data, evaluating ideas, and developing strong arguments. However, teachers also expressed avoidance intentions related to student confusion and uncertainty before and after inquiry-based investigations designed for critical thinking. These findings highlight a potential disconnect between the benefits of productive student struggle for critical thinking as endorsed in the research on learning and science education and the meaning that teachers ascribe to such struggle as they seek to align their instructional practices to classroom challenges.
Zhai, Xiaoming; Nehm, Ross H.
(, Journal of Research in Science Teaching)
Abstract In response to Li, Reigh, He, and Miller's commentary,Can we and should we use artificial intelligence for formative assessment in science, we argue that artificial intelligence (AI) is already being widely employed in formative assessment across various educational contexts. While agreeing with Li et al.'s call for further studies on equity issues related to AI, we emphasize the need for science educators to adapt to the AI revolution that has outpaced the research community. We challenge the somewhat restrictive view of formative assessment presented by Li et al., highlighting the significant contributions of AI in providing formative feedback to students, assisting teachers in assessment practices, and aiding in instructional decisions. We contend that AI‐generated scores should not be equated with the entirety of formative assessment practice; no single assessment tool can capture all aspects of student thinking and backgrounds. We address concerns raised by Li et al. regarding AI bias and emphasize the importance of empirical testing and evidence‐based arguments in referring to bias. We assert that AI‐based formative assessment does not necessarily lead to inequity and can, in fact, contribute to more equitable educational experiences. Furthermore, we discuss how AI can facilitate the diversification of representational modalities in assessment practices and highlight the potential benefits of AI in saving teachers’ time and providing them with valuable assessment information. We call for a shift in perspective, from viewing AI as a problem to be solved to recognizing its potential as a collaborative tool in education. We emphasize the need for future research to focus on the effective integration of AI in classrooms, teacher education, and the development of AI systems that can adapt to diverse teaching and learning contexts. We conclude by underlining the importance of addressing AI bias, understanding its implications, and developing guidelines for best practices in AI‐based formative assessment.
Manz, Eve, Lehrer, Richard, and Schauble, Leona. Rethinking the classroom science investigation. Journal of Research in Science Teaching 57.7 Web. doi:10.1002/tea.21625.
Manz, Eve, Lehrer, Richard, and Schauble, Leona.
"Rethinking the classroom science investigation". Journal of Research in Science Teaching 57 (7). Country unknown/Code not available: Wiley Blackwell (John Wiley & Sons). https://doi.org/10.1002/tea.21625.https://par.nsf.gov/biblio/10456978.
@article{osti_10456978,
place = {Country unknown/Code not available},
title = {Rethinking the classroom science investigation},
url = {https://par.nsf.gov/biblio/10456978},
DOI = {10.1002/tea.21625},
abstractNote = {Abstract There is now a significant research literature devoted to reconceptualizing scientific activities, such as modeling, explanation, and argumentation, to realize a vision of science‐as‐practice in classrooms. As yet, however, not all scientific practices have received equal attention.Planning and Carrying out Investigationsis one of the eight scientific practices identified in the Next Generation Science Standards, and there is a long line of research from both psychological and science education traditions that addresses topics about investigation, such as the generation and interpretation of evidence. However, investigation has not been subject to concerted reconceptualization within recent research and instructional design efforts focused on science‐as‐practice. In this article, we propose a framework that centers the investigation as a key locus for constructing alignments among phenomena, data, and explanatory models and makes visible the work that scientists engage in as they develop and stabilize alignments. We argue that these alignments are currently under‐theorized and under‐utilized in instructional environments. We explore four opportunities that we argue are both accessible to students from a young age and can support conceptual innovation. These are (a) developing empirical systems, (b) getting a grip on empirical systems, (c) determining, defining and operationalizing data as “evidence,” and (d) making sense of what the results of empirical systems do and do not help us understand.},
journal = {Journal of Research in Science Teaching},
volume = {57},
number = {7},
publisher = {Wiley Blackwell (John Wiley & Sons)},
author = {Manz, Eve and Lehrer, Richard and Schauble, Leona},
}
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