Introducing a Framework for Modeling Competence

Belzen, Annette Upmeier zu; Driel, Jan van; Krüger, Dirk

doi:10.1007/978-3-030-30255-9_1

Cited by 35 publications

(59 citation statements)

References 36 publications

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“…Del mismo modo, es fundamental la elaboración se secuencias de enseñanza que impliquen los procesos usuales de la modelización: explicar, predecir, argumentar, comunicar, analogar, etc. (Develaki, 2007;Upmeier zu Belzen, Driel, & Krüger, 2019). Esto último está en línea con la idea de que la modelización no es una competencia en sí misma, sino una suma de competencias que sería deseable fomentar en el estudiantado (Adúriz-Bravo, 2018).…”

Section: La Ciencia Escolarunclassified

Aproximaciones entre filosofía de la ciencia y didáctica de las ciencias: filosofía de la ciencia escolar y enseñanza en el nivel científico

Ariza

2021

Acta Sci. Human Soc. Sci.

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En este trabajo se revisan dos de las estrechas relaciones que pueden establecerse entre la filosofía de la ciencia y la didáctica de las ciencias experimentales. Para ello se analiza, por un lado, la manera en la cual haciendo uso de herramientas metateóricas (provenientes principalmente de la filosofía de la ciencia) se puede comprender y fundamentar el proceso de construcción de modelos científicos escolares, aquellos constituyentes de la llamada ‘ciencia escolar’; y, por otro lado, se revisa el cómo los procesos de enseñanza se desarrollan no sólo en los niveles de enseñanza de las ciencias usualmente reconocidos (primaria, secundaria o universitaria), sino también en los procesos de cambio científico. De esta manera, en la primera parte del trabajo se postula un posible campo de reflexiones epistemológicas específicas que toman como objeto de estudio a la construcción de modelos científicos escolares, las cuales podrían sugerir un campo especial de trabajo dentro de la filosofía de la ciencia: ‘la filosofía de la ciencia escolar’. Y, en la segunda parte, se sostiene la existencia de un ‘nivel de enseñanza científica’ centrado en la dinámica de comparación de teorías rivales, referida a los procesos de enseñanza (y no mera comunicación) que llevan a cabo los/as científicos/as en los llamados ‘periodos de crisis y revolución’.

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Section: La Ciencia Escolarunclassified

Aproximaciones entre filosofía de la ciencia y didáctica de las ciencias: filosofía de la ciencia escolar y enseñanza en el nivel científico

Ariza

2021

Acta Sci. Human Soc. Sci.

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“…As such, modeling is a prominent style of scientific reasoning that also is understood as a skill that needs to be practiced [4] and is related to competences [5] (p. 43). Thus, the framework for modeling competence was developed [6,7], respecting particularly procedural and epistemic perspectives of reasoning [8].…”

Section: Introductionmentioning

confidence: 99%

“…In biology education, the framework for modeling competence (FMC) [6] has been developed and empirically validated [15,16]. The FMC structures modeling competence into aspects and levels [17] and addresses at the same time the perspectives of model construction and model application.…”

Section: Introductionmentioning

confidence: 99%

Modeling as Scientific Reasoning—The Role of Abductive Reasoning for Modeling Competence

2021

Self Cite

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While the hypothetico-deductive approach, which includes inductive and deductive reasoning, is largely recognized in scientific reasoning, there is not much focus on abductive reasoning. Abductive reasoning describes the theory-based attempt of explaining a phenomenon by a cause. By integrating abductive reasoning into a framework for modeling competence, we strengthen the idea of modeling being a key practice of science. The framework for modeling competence theoretically describes competence levels structuring the modeling process into model construction and model application. The aim of this theoretical paper is to extend the framework for modeling competence by including abductive reasoning, with impact on the whole modeling process. Abductive reasoning can be understood as knowledge expanding in the process of model construction. In combination with deductive reasoning in model application, such inferences might enrich modeling processes. Abductive reasoning to explain a phenomenon from the best fitting guess is important for model construction and may foster the deduction of hypotheses from the model and further testing them empirically. Recent studies and examples of learners’ performance in modeling processes support abductive reasoning being a part of modeling competence within scientific reasoning. The extended framework can be used for teaching and learning to foster scientific reasoning competences within modeling processes.

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“…This implies not only learning about the models that feature in school science curricula but also the ability to work with, develop, and revise these models, and to discuss and express an opinion about them, understanding their nature, purpose, and limitations (Aragón et al, 2014). In the words of Upmeier zu Belzen, van Driel, and Krüger (2019), “…modeling competence includes the ability to gain insightful knowledge with models, to be able to judge models with regard to their purpose, and to reflect on the process of gaining knowledge through models and modeling…” (p. 12). Hence, it is a multidimensional construct, a key component of which is what is referred to as meta‐modeling knowledge (Krell & Krüger, 2017; Nicolaou & Constantinou, 2014).…”

Section: Introductionmentioning

confidence: 99%

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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Introducing a Framework for Modeling Competence

Cited by 35 publications

References 36 publications

Aproximaciones entre filosofía de la ciencia y didáctica de las ciencias: filosofía de la ciencia escolar y enseñanza en el nivel científico

Aproximaciones entre filosofía de la ciencia y didáctica de las ciencias: filosofía de la ciencia escolar y enseñanza en el nivel científico

Modeling as Scientific Reasoning—The Role of Abductive Reasoning for Modeling Competence

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

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