Investigating the Relationship between Students’ Views of Scientific Models and Their Development of Models

Cheng, Meng-Fei; Lin, Jang‐Long

doi:10.1080/09500693.2015.1082671

Cited by 51 publications

(43 citation statements)

References 59 publications

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“…However, existing curricula rarely support students in engaging with productive modeling epistemologies. Instead, science curricula often encourage students to perceive models as: literal depictions of a phenomenon, rather than simplified and explanatory representations (Cheng & Lin, ; Lehrer & Schauble, ; Schwarz & White ; Treagust et al, ), case‐specific rather than abstract and generative (Buckingham & Reiser, ; Lehrer, Schauble, & Lucas, ; Schwarz et al., ), based on information from authorities, like textbooks or teachers, rather than on evidence collected and analyzed by the students (Schwarz et al., ), and created as answers for teachers rather than as revisable tools for sense making or communication (Schwarz et al., ; Treagust et al., ). …”

Section: K–12 Modeling Practicesmentioning

confidence: 99%

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Learning progressions in context: Tensions and insights from a semester‐long middle school modeling curriculum

2017

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Schwarz and colleagues have proposed and refined a learning progression for modeling that provides a valuable template for envisioning increasingly sophisticated levels of modeling practice at an aggregate level (Fortus, Shwartz, & Rosenfeld, ; Schwarz et al., ; Schwarz, Reiser, Archer, Kenyon, & Fortus, ). Thinking about learning progressions for modeling, however, involves challenges in coordinating between aggregate arcs in the curriculum and individual student learning trajectories. First, individual student performance is often dependent on students’ epistemic aims and the nature of the conceptual and representational context. Second, approaches for longitudinally supporting students in modeling is a relatively nascent endeavor, although notable exemplars have been developed (e.g., IQWST). Third, research on the highest levels of the proposed progression is often hypothetical, because few students demonstrate high‐level modeling practices in typical classrooms. In response to these challenges, we conducted a semester‐long design‐based study of eighth graders engaging in diagrammatic, physical, and computational modeling. In this paper, we explore conceptual and representational contexts designed to support sophisticated modeling practices and beliefs, analyze the nature of high‐level performances achieved through these contexts, and suggest revisions to the articulation of the Schwarz and colleagues learning progression to increase its utility and generalizability when viewed through a resource‐related lens.

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Section: K–12 Modeling Practicesmentioning

confidence: 99%

“…• literal depictions of a phenomenon, rather than simplified and explanatory representations (Cheng & Lin, 2015;Lehrer & Schauble, 2012;Schwarz & White 2005;Treagust et al, 2002),…”

Section: Introductionmentioning

confidence: 99%

Learning progressions in context: Tensions and insights from a semester‐long middle school modeling curriculum

2017

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“…Some students argue that models are end products of research which show what has been found out already. The perspective may stem from a focus on models as representations which indicate the students' “science learning performance” (Campbell et al, ; Cheng & Lin, ; Gilbert & Justi, ). The students critique that the models presented in the tasks are too simple for research as models for research need to include all the details of the original.…”

Section: Discussionmentioning

confidence: 99%

Students' understanding of the nature and purpose of models

Gogolin

Krüger

2018

J Res Sci Teach

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The process of thinking in and about models as a scientific practice should be integrated into science teaching and learning. Empirical studies show that students see models primarily in their role as media to facilitate content learning while rarely appreciating models as instruments of scientists which allow the deduction and the testing of predictions. In order to foster students' meta-modeling knowledge successfully, specific diagnostic information about students' understanding of models and modeling is needed. The aim of this study is to gather such diagnostic information by investigating students' understanding of the nature and the purpose of models in biology with respect to context-and grade-specific differences. Students' understanding of the nature and the purpose of models was assessed by using forced choice tasks (N students 5 285). In order to gain qualitative insight into possible reasons for context-specific differences, the students were additionally asked to give reason for their decision in the forced choice tasks by answering open-ended justification tasks. The results indicate that the majority of students in all grades see models as idealized representations of an original which have the purpose to show or to describe this original. Students' levels of understanding of the nature and the purpose of models increase only little across grades. Nevertheless, a gradespecific analysis of the consistency of students' understanding across contexts suggests that the students' understanding becomes more consistent in higher grades. Students' justifications helped to identify model contexts which have a high potential to be fruitful when trying to foster students' understanding of the nature and the purpose of models. K E Y W O R D Sbiology education, contexts, diagnosis, models, students' understanding J Res Sci Teach. 2018;1-26.wileyonlinelibrary.com/journal/tea

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“…However, in both undergraduate chemistry and physics contexts there is limited evidence of how traditional or modeling‐focused curricula impact students' epistemic ideas about models and modeling (Justi & Gilbert, ; Nicolau & Constantinou, ). Prior efforts to assess metamodeling knowledge at the high school and undergraduate levels have focused used selected‐response assessments for assessing the efficacy of curricular interventions on students' perceptions of models and modeling (Burgin, Oramous, Kaminski, Stocker, & Moradi, ; Cheng et al, ; Cheng & Lin, ; Everett, Otto, & Luera, ; Gobert et al, ; Levy & Wilensky, ; Liu, ; Park, Liu, Smith, & Waight, ). For example, Treagust, Chittleborough, and Mamiala () developed the Students' Understanding of Models in Science (SUMS) instrument to assess students' perceived metamodeling knowledge.…”

Section: Introductionmentioning

confidence: 99%

“…Since epistemic knowledge contributes to the development of content knowledge (Schuchardt & Schunn, ; Schwarz & White, ), we argue that the science community should develop ways to assess growth in students' epistemic knowledge about models and modeling (Justi & Gilbert, ). While the literature describes some assessment resources (e.g., Treagust et al, ; Treagust, Chittleborough, & Mamiala, ), most of these have been developed and validated with reference to K‐12 students' and pre‐service teachers' understandings (Cheng & Lin, ; Derman & Kayacan, ; Everett et al, ; Gobert et al, ; Liu, ; Park et al, ). Thus, to better develop and refine modeling‐focused instructional resources that support student learning, the science community needs assessment resources that are valid for undergraduate populations as well (Justi & Gilbert, ).…”

Section: Introductionmentioning

confidence: 99%

Mapping undergraduate chemistry students' epistemic ideas about models and modeling

et al. 2019

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Developing and using scientific models is an important scientific practice for science students. Undergraduate chemistry curricula are often centered on established disciplinary models, and assessments typically provide students with opportunities to use these models to predict and explain chemical phenomena. However, traditional curricula generally provide few opportunities for students to consider the epistemic nature of models and the process of modeling. To gain a sense of how introductory chemistry students understand model changeability, model multiplicity, the evaluation of models, and the process of modeling, we use a construct‐mapping approach to characterize the sophistication of students' epistemic knowledge of models and modeling. We present a set of four related construct maps that we developed based on the work of other scholars and empirically validated in an undergraduate introductory chemistry setting. We use the construct maps to identify themes in students' responses to an open‐ended survey instrument, the models in chemistry survey, and discuss the implications for teaching.

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Investigating the Relationship between Students’ Views of Scientific Models and Their Development of Models

Cited by 51 publications

References 59 publications

Learning progressions in context: Tensions and insights from a semester‐long middle school modeling curriculum

Learning progressions in context: Tensions and insights from a semester‐long middle school modeling curriculum

Students' understanding of the nature and purpose of models

Mapping undergraduate chemistry students' epistemic ideas about models and modeling

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