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Using Computer Simulations for Promoting Model-based Reasoning

Published on Nov 1, 2017in Science Education2.90
· DOI :10.1007/s11191-017-9944-9
Maria Develaki3
Estimated H-index: 3
(NCSE: National Center for Science Education)
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Abstract
Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students’ ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students’ model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.
  • References (93)
  • Citations (3)
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References93
Newest
Published on Jan 1, 2017in Science Education2.90
Per Morten Kind9
Estimated H-index: 9
(Durham University),
Jonathan Osborne48
Estimated H-index: 48
(Stanford University)
In this paper, we contend that what to teach about scientific reasoning has been bedeviled by a lack of clarity about the construct. Drawing on the insights emerging from a cognitive history of science, we argue for a conception of scientific reasoning based on six “styles of scientific reasoning.” Each “style” requires its own specific ontological and procedural entities, and invokes its own epistemic values and constructs. Consequently, learning science requires the development of not just con...
Published on Oct 1, 2016in Science Education2.90
Yefrin Ariza1
Estimated H-index: 1
(UBA: University of Buenos Aires),
Pablo Lorenzano6
Estimated H-index: 6
(CONICET: National Scientific and Technical Research Council),
Agustín Adúriz-Bravo11
Estimated H-index: 11
(UBA: University of Buenos Aires)
There is nowadays consensus in the community of didactics of science (i.e. science education understood as an academic discipline) regarding the need to include the philosophy of science in didactical research, science teacher education, curriculum design, and the practice of science education in all educational levels. Some authors have identified an ever-increasing use of the concept of ‘theoretical model’, stemming from the so-called semantic view of scientific theories. However, it can be re...
Published on Aug 1, 2016in Interchange
Maria Develaki1
Estimated H-index: 1
Models and modeling are core elements of scientific methods and consequently also are of key importance for the conception and teaching of scientific methodology. The epistemology of models and its transfer and adaption to nature of science education are not, however, simple themes. We present some conceptual units in which school science models are used for exemplifying aspects and issues that we consider crucial for an understanding of models and modelling, such as: the perspectival and concep...
Published on Jan 1, 2016
John K. Gilbert41
Estimated H-index: 41
,
Rosária Justi20
Estimated H-index: 20
Published on Oct 1, 2015in Science Education2.90
Laura Zangori9
Estimated H-index: 9
(MU: University of Missouri),
Cory T. Forbes14
Estimated H-index: 14
(NU: University of Nebraska–Lincoln),
Christina V. Schwarz12
Estimated H-index: 12
(MSU: Michigan State University)
Opportunities to generate model-based explanations are crucial for elementary students, yet are rarely foregrounded in elementary science learning environments despite evidence that early learners can reason from models when provided with scaffolding. We used a quasi-experimental research design to investigate the comparative impact of a scaffold test condition consisting of embedded physical scaffolds within a curricular modeling task on third-grade (age 8–9) students’ formulation of model-base...
Published on Apr 8, 2014in Journal of Science Teacher Education
Joseph Krajcik63
Estimated H-index: 63
(MSU: Michigan State University),
Susan Codere1
Estimated H-index: 1
(Michigan Department of Education)
+ 2 AuthorsKongju Mun3
Estimated H-index: 3
(MSU: Michigan State University)
The National Research Council’s Framework for K-12 Science Education and the Next Generation Science Standards (NGSS Lead States in Next Generation Science Standards: For states, by states. The National Academies Press, Washington, 2013) move teaching away from covering many isolated facts to a focus on a smaller number of disciplinary core ideas (DCIs) and crosscutting concepts that can be used to explain phenomena and solve problems by engaging in science and engineering practices. The NGSS pr...
Published on Jul 1, 2013in Science Education2.90
Agustín Adúriz-Bravo11
Estimated H-index: 11
(UBA: University of Buenos Aires)
In this paper I inspect a ‘semantic’ view of scientific models taken from contemporary philosophy of science—I draw upon the so-called ‘semanticist family’, which frontally challenges the received, syntactic conception of scientific theories. I argue that a semantic view may be of use both for science education in the classrooms of all educational levels, and for research and innovation within the discipline of didactics of science. I explore and characterise a model-based account of the nature ...
Published on Jun 1, 2013in Science Education2.90
Suvi Tala5
Estimated H-index: 5
(UH: University of Helsinki)
The content of the expertise which young natural scientists try to gain by doing science in research groups is a relatively little-explored subject. What makes learning in such settings challenging is that a central part of the expertise is tacit. This study employs empirical methods together with a contextualized approach and interdisciplinary cooperation in order to reveal practicing nanomodellers’ (N = 10) perspectives on their knowledge-building expertise, and on young scientists’ expertise ...
Published on Apr 19, 2013in Science41.04
Ton de Jong37
Estimated H-index: 37
(UT: University of Twente),
Marcia C. Linn60
Estimated H-index: 60
(University of California, Berkeley),
Zacharias C. Zacharia22
Estimated H-index: 22
(UCY: University of Cyprus)
The world needs young people who are skillful in and enthusiastic about science and who view science as their future career field. Ensuring that we will have such young people requires initiatives that engage students in interesting and motivating science experiences. Today, students can investigate scientific phenomena using the tools, data collection techniques, models, and theories of science in physical laboratories that support interactions with the material world or in virtual laboratories...
Published on Apr 8, 2013
Helen R. Quinn28
Estimated H-index: 28
,
Heidi A. Schweingruber12
Estimated H-index: 12
,
Thomas Keller1
Estimated H-index: 1
Cited By3
Newest
Published on Jul 22, 2019in International Journal of Science Education1.25
Gretchen P. King (NU: University of Nebraska–Lincoln), Heather E. Bergan-Roller2
Estimated H-index: 2
(NIU: Northern Illinois University)
+ 2 AuthorsJoseph T. Dauer11
Estimated H-index: 11
(NU: University of Nebraska–Lincoln)
Published on Mar 8, 2019in Journal of Science Education and Technology1.78
Maria Develaki3
Estimated H-index: 3
(NCSE: National Center for Science Education)
While computer simulations are a key element in understanding and doing science today, their nature and implications for science education have not been adequately explored in the relevant literature. In this article, (1) we provide an analysis of the methodology and epistemology of computer simulations, aiming to contribute to a sound and comprehensive account of the nature of computer simulations in science education, and (2) examine certain implications for science education, particularly in ...
Published on Jan 1, 2019in Isa Transactions4.34
Yuan Guo (Jiangsu University), Wei Chen (Jiangsu University)+ 1 AuthorsYu-Qin Guo (Jiangsu University)
Abstract With the arrival of big data era, the integration of Case-Based Reasoning (CBR) and Bayesian Network (BN) has become increasingly a promising technology in implementing the intelligence of engineering application. To further improve the efficiency of the integrated system and make it adapt to the large number of parameter under big data, Within-Cross (WC) algorithm is proposed in this paper to assigned big data to each slave node of Hadoop platform for parallel data processing. The WC a...
Published on Jan 1, 2019
Sonu Jose1
Estimated H-index: 1
,
Siming Liu4
Estimated H-index: 4
+ 1 AuthorsSergiu M. Dascalu12
Estimated H-index: 12
View next paperSupporting Elementary Teachers’ Planning and Assessing of Mathematical Reasoning