On the Epistemology of Models

Mahr, Bernd; Abel, Günter; Conant, James

doi:10.1515/9783110253573.301

Cited by 26 publications

(20 citation statements)

References 9 publications

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“…Oh & Oh, ). Consequently, we will try to step away from a definition for the term “model” and instead refer to Mahr () who determines interdependent relationships that justify something to be conceived of as a model. In his epistemic pattern of model‐being, a model is (i) distinct from its representation as a model object, (ii) in its function as a representation, a model of something, and (iii), in a methodological view, a model for something (Mahr, ).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Consequently, we will try to step away from a definition for the term “model” and instead refer to Mahr () who determines interdependent relationships that justify something to be conceived of as a model. In his epistemic pattern of model‐being, a model is (i) distinct from its representation as a model object, (ii) in its function as a representation, a model of something, and (iii), in a methodological view, a model for something (Mahr, ). For example, a computer simulation of the Zika‐Virus' spread (the model object) is based on assumptions drawn from recorded data with regard to the rate of infection transmission, thus being a model of the original Zika‐Virus' spread.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Moreover, as a model for predicting, it allows the testing of hypotheses, which are drawn from the model itself about the number of lethal infections or about the potential spatial dispersion of the Zika‐Virus by the Olympic Games. Mahr () points out that models “do not incarnate any form of truth, but rather forms of demonstrability, possibility, and choice” (p. 303). Summarizing purposes attributed to models by science philosophers and science education researchers, Oh and Oh () highlight that “as description, explanation and prediction are primary goals of science, the purposes of modeling in science are to describe, explain and predict particular aspects of the natural world” (pp.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…1114–1115). Despite the many divergent attempts to define models and their use in science, researchers agree that models are the result of a theory‐driven modeling process and are defined only in the context of their use (e.g., Bailer‐Jones, ; Giere, ; Mahr, ).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…The levels were develop based on a literature review (cf. Upmeier zu Belzen & Krüger, ) and theoretical reflections about the term “model” (Mahr, ). Furthermore, the levels were empirically validated in a study with open‐ended tasks by Grünkorn, Upmeier zu Belzen, and Krüger ().…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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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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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

See 3 more Smart Citations

Students' understanding of the nature and purpose of models

Gogolin

Krüger

2018

J Res Sci Teach

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Investigating scientific modeling practices in U.S. and German elementary science classrooms: A comparative, cross‐national video study

2022

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Science education reform efforts have emphasized the incorporation of more authentic and meaningful scientific practices into formal learning environments. With this focus on practices, such as scientific modeling, a powerful tool for sense‐making and reasoning, comes a need to observe and understand if and how it is actually occurring, particularly in elementary science learning environments. To address this need, and moving forward an international, collaborative research effort centered around scientific modeling, we undertook a cross‐national observational study in which we used an observation protocol to characterize scientific modeling practices in elementary classrooms in both the United States and Germany. Drawing on existing video‐based datasets from multiple projects, this study's findings provide empirical evidence for model‐based teaching and learning and explore the relative frequencies of relevant modeling subpractices (i.e., construction, use, evaluation, and revision of scientific models) in regular, day‐to‐day elementary science classrooms. This study also illustrates the differences and similarities between German and American science instruction. In general, students in both countries experience model construction more often than other modeling practices. German teachers more consistently foreground anchoring phenomena and students’ questions/preconceptions as part of the modeling process, thus leading to slightly higher overall modeling scores—despite a complete lack of model evaluation and revision in any of the observed German classrooms. Ultimately, however, young learners in both nations seem to experience alarmingly little opportunities to engage in any of the modeling subpractices. Particularly in terms of modeling as a means to make sense of phenomena, constrained by teachers most commonly using finished representations (i.e., models) of phenomena and processes to teach science/deliver content. Our results indicate the need for a greater focus on all scientific modeling subprocesses, particularly the integration of scientific modeling with already established, more general (e.g., inquiry‐based) strategies for effective science teaching and an emphasis on actualizing modeling as an authentic sense‐making endeavor.

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Development of a questionnaire for assessing Spanish‐speaking students' understanding of the nature of models and their uses in science

Martínez

López

2021

J Res Sci Teach

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The translation and adaptation of an assessment instrument into another language can be problematic, due, among other reasons, to sociocultural differences. This proved to be the case with the Spanish adaptation of the Students' Understanding of Models in Science (SUMS) questionnaire, a Likert‐type scale developed originally in English. In light of this, and with the additional aim of improving upon certain aspects of the original instrument, we report the development of a new questionnaire for assessing Spanish‐speaking students' understanding of the nature of models and their uses in science, providing validity evidence for the internal structure of the construct measured. The tool was developed by considering various dimensions of this concept that have been described in the literature, as well as the results of studies that piloted the SUMS questionnaire. For each dimension we drew up a set of items that could be rated using a Likert‐type scale; half of these items were positively worded with respect to an adequate understanding of models, and half were reverse worded. The adequacy of the proposed items was first assessed by a panel of experts, following which we examined the score structure obtained with the resulting instrument by administering it to a sample of 1272 students aged between 14 and 55 years. After purifying the instrument based on the results of these analyses, we obtained a final version of the questionnaire comprising 20 items distributed equally across four subscales: Beyond exact replicas, Purpose of models, Multiple models, and Changing models. The results obtained through factor analysis and structural equation modeling provide validity evidence for the internal structure of the construct measured. The questionnaire is quick to administer and is applicable to students across a wide range of ages and levels of education, including prospective science teachers.

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On the Epistemology of Models

Cited by 26 publications

References 9 publications

Students' understanding of the nature and purpose of models

Students' understanding of the nature and purpose of models

Investigating scientific modeling practices in U.S. and German elementary science classrooms: A comparative, cross‐national video study

Development of a questionnaire for assessing Spanish‐speaking students' understanding of the nature of models and their uses in science

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