Journal of Research in Science Teaching最新文献

It has been widely accepted in the science education research community that scientific literacy as a concept and phrase was introduced by Paul deHart Hurd in 1958. Recent research into the origins of the phrase, however, has shown this to be incorrect. Its first published use can be traced back, in fact, to 1945, and the phrase was frequently invoked in popular and research publications throughout the 1940s and 1950s. Exploring the historical circumstances of the phrase's introduction into popular discourse, it is argued, reveals that despite the rhetorical power and widespread adoption of the idea, scientific literacy (as others have pointed out) has proven to be little more than an empty slogan that offers no substantive guidance for thinking about the goals of science education. This essay argues that rather than continue to cling to the idea, the field of science education can more productively consider the most relevant and appropriate goals of science teaching by dispensing with the concept altogether.

There is extensive literature focusing on students' misconceptions in various subject domains. Several conceptual change approaches have been trying to understand how conceptual change occurs to help learners handle these misconceptions. This meta-analysis aims to integrate studies investigating the effectiveness of three types of conceptual change strategy: cognitive conflict, cognitive bridging, and ontological category shift in science learning. We conducted a random-effects meta-analysis to calculate an overall effect size in Hedges' g with a sample of 218 primary studies, including 18,051 students. Our analyses resulted in a large overall effect size (g = 1.10, 95% CI [1.01, 1.19], k = 218, p < 0.001). We also performed a robust Bayesian meta-analysis to calculate an adjusted effect size, which specified a large effect (adjusted g = 0.93, 95% CI [0.68, 1.07], k = 218). Results are also consistent across the conceptual change strategies of cognitive conflict (g = 1.10, 95% CI [0.99, 1.21], k = 150, p < 0.001), cognitive bridging (g = 1.06, 95% CI [0.84, 1.28], k = 30, p < 0.001), and ontological category shift (g = 0.88, 95% CI [0.50, 1.26], k = 9, p < 0.001). However, a wide-ranging prediction interval [0.19, 2.38] points out a high level of heterogeneity in the distribution of effect sizes. Thus, we investigated the moderating effects of several variables using simple and multiple meta-regression. The final meta-regression model we created explained 35% of overall heterogeneity. This meta-analysis provides robust evidence that conceptual change strategies significantly enhance students' learning in science.

Social, political, and cultural complexities observed in environmental justice (EJ) communities require new forms of investigation, science teaching, and communication. Defined broadly, participatory approaches can challenge and change inequity and mistrust in science. Here, we describe Project Harvest and the partnership building and co-generation of knowledge alongside four EJ communities in Arizona. From 2017 to 2021, Project Harvest centered learning around these communities and the participant experience drove the data sharing practice. The framework of sense-making is used to analyze how community scientists (CS) are learning within the context of environmental pollution and (in)justice. The environmental health literacy (EHL) framework is applied to document the acquisition of skills that enable protective decision-making and the capacity of CS to move along the EHL continuum. Using data from surveys, focus groups, and semi-structured interviews, we are asking how did: (1) Personal connections and local relevancy fuel sense-making? (2) Data sharing make pollution visible and connect to historical knowledge to either reinforce or modify their existing mental map around pollution? and (3) The co-creation process build data literacy and a relationship science? Results indicate that due to the program framing, CS personally connected with, and made sense of their data based on use and experience. CS synthesized and connected their pollution history and lived experiences with their data and evaluated contaminant transport. CS saw themselves as part of the process, are taking what they learned and the evidence they helped produce to adopt protective environmental health measures and are applying these skills to new contexts. Here, co-created science nurtured a new/renewed relationship with science. This science culture rooted in co-creation, fosters action, trust, and supports ongoing science engagement. The science learning that stems from co-created efforts can set the pace for social transformation and provide the foundation for structural change.

Meaningful participation in science and engineering practices requires that students make their thinking visible to others and build on one another's ideas. But sharing ideas with others in small groups and classrooms carries social risk, particularly for students from nondominant groups and communities. In this paper, we explore how students' perceptions of classrooms shape their contributions to classroom knowledge building in science across a wide range of classrooms. We examine the claim that when students feel a sense of belonging in class, they contribute more and perceive their ideas to be more influential in knowledge building. Data comes from classroom exit tickets (n = 10,194) administered in 146 classrooms as part of a 10-state field test of a new middle-school science curriculum, OpenSciEd, which were analyzed using mixed effects models. We found that students' sense of belonging predicted the degree to which they contributed ideas out loud in class (Odds ratio = 1.57) as well as the degree to which they perceived their contributions as influencing others (Odds ratio = 1.53). These relationships were particularly strong for students who reported a lower a sense of belonging. We also found significant differences by both race and gender in whether students said they contributed and believed their ideas influenced those of others. These findings suggest that a learner's sense of belonging in class and willingness to contribute may be mutually reinforcing, highlighting the need to promote content-specific strategies to foster belonging in ways that support collaborative knowledge building.

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.

There is growing recognition in the education community that the problem-solving practices that comprise computational thinking (CT) are a fundamental component of both life and work in the twenty-first century. Historically, opportunities to learn CT have been confined to computer science (CS) and elective courses that lack racial, ethnic, and gender diversity. To combat this inequity, a number of scholars have proposed integrating CT practices into core curriculum——especially science, technology, engineering, and math curriculum. Successfully achieving the goal of integrated CT, however, depends on frameworks to guide integration, professional development for teachers, exemplars of successful integrations, and identifications of the barriers teachers encounter. Research pertaining to each of these areas is in its infancy. This study addresses these needs through a collective case study of 10 secondary science teachers' implementations of a novel, process-based, unplugged approach to CT/science integration and the factors that supported or hindered their CT/science integration efforts. The results of this work reveal that: (1) an unplugged and process-based approach to CT/science integration shows promise as a vehicle for infusing CT into diverse science classrooms; (2) educators' teaching context exerts a strong influence on their CT-integration efforts and persistence; and (3) special attention is needed to support teachers in their CT/science integrations including algorithm creation. This study also demonstrates the utility of the Fraillon et al.'s CT framework as a guide for CT/science integration efforts and sheds light on the unique affordances of unplugged strategies for implementing CT-integrated science curricula.

This article explores the meaning of community-driven and owned science in the context of an Inuit-led land-based program, the Young Hunters Program. It is the foundational program of the Arviat Aqqiumavvik Society, situated in Nunavut, Canada, a community-led group dedicated to researching challenges to community wellness and designing and delivering programs to help address those challenges. We show how the program emerged locally and blends Indigenous knowledge systems (IKS) with tools of western science in respectful ways given its core sits within and emerges from what Inuit have always known to be true. We offer a description of six dimensions inherent in Inuit cultural practices and beliefs and foundational to the program activities and show how they open up various learning trajectories and possibilities for the involved young people to engage in community science. We then discuss in what ways the revitalization of IKS and practices led to community science projects that were locally meaningful and empowering with important implications for scientific work that mattered in light of locally experienced and devastating climate change threats. The study speaks to the importance of rebuilding relations and decolonizing knowledge systems and science practices, two key tools to Inuit self-determination and social transformations, and essential to achieving more social justice and equity in and beyond community science.

This article reports on analyses of the instructional practices of six middle- and high-school science teachers in the United States who participated in a research-practice partnership that aims to support reform science education goals at scale. All six teachers were well qualified, experienced, and locally successful—respected by students, parents, colleagues, and administrators—but they differed in their success in supporting students' three-dimensional learning. Our goal is to understand how the teachers' instructional practices contributed to their similarities in achieving local success and to differences in enabling students' learning, and to consider the implications of these findings for research-practice partnerships. Data sources included classroom videos supplemented by interviews with teachers and focus students and examples of student work. We also compared students' learning gains by teacher using pre–post assessments that elicited three-dimensional performances. Analyses of classroom videos showed how all six teachers achieved local success—they led effectively managed classrooms, covered the curriculum by teaching almost all unit activities, and assessed students' work in fair and efficient ways. There were important differences, however, in how teachers engaged students in science practices. Teachers in classrooms where students achieved lower learning gains followed a pattern of practice we describe as activity-based teaching, in which students completed investigations and hands-on activities with few opportunities for sensemaking discussions or three-dimensional science performances. Teachers whose students achieved higher learning gains combined the social stability characteristic of local classroom success with more demanding instructional practices associated with scientific sensemaking and cognitive apprenticeship. We conclude with a discussion of implications for research-practice partnerships, highlighting how partnerships need to support all teachers in achieving both local and standards-based success.

There is a significant amount of research literature on the importance of identifying and building on students' experiences and ideas for making sense of the natural world, especially when engaging in science practices. Simultaneously, approaches to creating justice-oriented science education promote the need to focus on the diverse sense-making repertoires that students, especially those from historically marginalized communities, bring to science classrooms. However, when it comes to emergent bi/multilingual students, science education has favored narrow definitions of what ways of communicating are seen as productive for figuring out natural phenomena, privileging English-based academic vocabulary. In this article, we investigate the myriad conceptual and semiotic resources that third-grade emergent bilingual students developed and used when explaining sound production. Additionally, we explore how students investigated the sounds produced by a string instrument and unpacked the how and whys that give rise to the pitch of the sounds they heard. Our analyses indicate that: (1) students created mechanistic explanations that identified how changes to the salient physical features of strings affected the pitch of the sounds; (2) students created and laminated multiple semiotic resources when sharing their observations and explanations, particularly sound symbolisms; and (3) students navigated both semiotic convergence and divergence as they worked toward conceptual convergence. Based on our findings, we argue that justice-oriented science learning environments must become spaces where emergent bilingual students can build on all their conceptual, semiotic, and cultural resources, without being policed, as they engage science practices.