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Abstract Student-centered instruction allows students to take ownership over their learning in the classroom. However, these settings do not always promote productive engagement. Using discourse analysis, student engagement can be analyzed based on how they are interacting with each other while completing in-class group activities. Previous analyses of student engagement in science settings have used methods that do not capture the intricacies of student group interactions such as the flow of conversation and nature of student utterances outside of argumentation or reasoning. However, these features are important to accurately assess student engagement. This study proposes a tiered analytical framework and visualization scheme for analyzing group discussion patterns that allow for a detailed analysis of student discourse moves while discussing scientific topics. This framework allows a researcher to see the flow of an entire conversation within a single schematic. The Student Interaction Discourse Moves framework can be used to extend studies using discourse analysis to determine how student groups work through problems.
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This content will become publicly available on June 10, 2026
“We Conquered the Blank Page”: Examining Researcher and Coach Partnerships’ Creation of Shared Objects
This study explored how researcher–coach dyads collaborated to create research-based briefs for classroom use. Data from a two-day workshop and dyads’ final products were analyzed using interaction analysis. The dyad’s work illuminated how products and relationships evolved together, fostering ownership and collaboration. These findings inform future researcher–practitioner partnerships and guide facilitation of effective collaborations by highlighting relationship building, agency, and ownership to shape joint work.
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- PAR ID:
- 10609100
- Publisher / Repository:
- Repository of the International Society of Learning Sciences
- Date Published:
- Page Range / eLocation ID:
- 2747 to 2749
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Gresalfi, M. and (Ed.)A growing subset of the learning sciences centers how relationality supports meaningful sense-making. Some of this work focuses specifically on friendships, a relational form in which participants share a historical, emotional, social, and cultural intersubjectivity. We wish to re-focus this research in the learning sciences by exploring three kinds of friendships within the field (researcher-researcher, researcher-collaborator, and participant-participant) to understand how these relational forms emerged and expanded our thinking and ways of being. We argue politicized trust and ethical vulnerability are important components of learning in friendships. We offer potential implications for the learning sciences to further our goals of developing theoretically validated, politically explicit, ethically laden theories and designs of learning.more » « less
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Abstract BackgroundStudying science identity has been useful for understanding students’ continuation in science-related education and career paths. Yet knowledge and theory related to science identity among students on the path to becoming a professional science researcher, such as students engaged in research at the undergraduate, postbaccalaureate, and graduate level, is still developing. It is not yet clear from existing science identity theory how particular science contexts, such as research training experiences, influence students’ science identities. Here we leverage existing science identity and professional identity theories to investigate how research training shapes science identity. We conducted a qualitative investigation of 30 early career researchers—undergraduates, postbaccalaureates, and doctoral students in a variety of natural science fields—to characterize how they recognized themselves as science researchers. ResultsEarly career researchers (ECRs) recognized themselves as either science students or science researchers, which they distinguished from being a career researcher. ECRs made judgments, which we refer to as “science identity assessments”, in the context of interconnected work-learning and identity-learning cycles. Work-learning cycles referred to ECRs’ conceptions of the work they did in their research training experience. ECRs weighed the extent to which they perceived the work they did in their research training to show authenticity, offer room for autonomy, and afford opportunities for epistemic involvement. Identity-learning cycles encompassed ECRs’ conceptions of science researchers. ECRs considered the roles they fill in their research training experiences and if these roles aligned with their perceptions of the tasks and traits of perceived researchers. ECRs’ identity-learning cycles were further shaped by recognition from others. ECRs spoke of how recognition from others embedded within their research training experiences and from others removed from their research training experiences influenced how they see themselves as science researchers. ConclusionsWe synthesized our findings to form a revised conceptual model of science researcher identity, which offers enhanced theoretical precision to study science identity in the future. We hypothesize relationships among constructs related to science identity and professional identity development that can be tested in further research. Our results also offer practical implications to foster the science researcher identity of ECRs.more » « less
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Abstract As an increasing number of machine learning (ML) products enter the research-to-operations (R2O) pipeline, researchers have anecdotally noted a perceived hesitancy by operational forecasters to adopt this relatively new technology. One explanation often cited in the literature is that this perceived hesitancy derives from the complex and opaque nature of ML methods. Because modern ML models are trained to solve tasks by optimizing a potentially complex combination of mathematical weights, thresholds, and nonlinear cost functions, it can be difficult to determine how these models reach a solution from their given input. However, it remains unclear to what degree a model’s transparency may influence a forecaster’s decision to use that model or if that impact differs between ML and more traditional (i.e., non-ML) methods. To address this question, a survey was offered to forecaster and researcher participants attending the 2021 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiment (SFE) with questions about how participants subjectively perceive and compare machine learning products to more traditionally derived products. Results from this study revealed few differences in how participants evaluated machine learning products compared to other types of guidance. However, comparing the responses between operational forecasters, researchers, and academics exposed notable differences in what factors the three groups considered to be most important for determining the operational success of a new forecast product. These results support the need for increased collaboration between the operational and research communities. Significance StatementParticipants of the 2021 Hazardous Weather Testbed Spring Forecasting Experiment were surveyed to assess how machine learning products are perceived and evaluated in operational settings. The results revealed little difference in how machine learning products are evaluated compared to more traditional methods but emphasized the need for explainable product behavior and comprehensive end-user training.more » « less
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Our understanding of ownership influences how we interact with objects and with each other. Here, we studied people’s intuitions about ownership transfer using a set of simple, parametrically varied events. We found that people ( N = 120 U.S. adults) had similar intuitions about ownership for some events but sharply opposing intuitions for others (Experiment 1). People ( N = 120 U.S. adults) were unaware of these conflicts and overestimated ownership consensus (Experiment 2). Moreover, differences in people’s ownership intuitions predicted their intuitions about the acceptability of using, altering, controlling, and destroying the owned object ( N = 130 U.S. adults; Experiment 3), even when ownership was not explicitly mentioned ( N = 130 U.S. adults; Experiment 4). Subject-level analyses suggest that these disagreements reflect at least two underlying intuitive theories, one in which intentions are central to ownership and another in which physical possession is prioritized.more » « less
