Epistemic forms and Epistemic Games: Structures and Strategies to Guide Inquiry

Collins, Allan; Ferguson, William D.

doi:10.1207/s15326985ep2801_3

Cited by 265 publications

(212 citation statements)

References 11 publications

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“…From our data, it seems that the bifocal framework afforded a new type of interaction: Students employed the real experiment as their macro-level representation ''anchor,'' while keeping the computational algorithm as their micro-level anchor. We argue that this recursive process not only enriched students' inquiry process, but it provided a new type of epistemic game (Collins and Ferguson 1993) through which students could accelerate and deepen their sense about bacteria growth. b.…”

Section: Discussionmentioning

confidence: 99%

Using the Bifocal Modeling Framework to Resolve “Discrepant Events” Between Physical Experiments and Virtual Models in Biology

2016

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In this paper, we investigate an approach to supporting students' learning in science through a combination of physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework, which we call ''bifocal modeling,'' to link student-designed experiments and computer models in real time. In this study, a group of high school students designed computer models of bacterial growth with reference to a simultaneous physical experiment they were conducting, and were able to validate the correctness of their model against the results of their experiment. Our findings suggest that as the students compared their virtual models with physical experiments, they encountered ''discrepant events'' that contradicted their existing conceptions and elicited a state of cognitive disequilibrium. This experience of conflict encouraged students to further examine their ideas and to seek more accurate explanations of the observed natural phenomena, improving the design of their computer models. IntroductionThe nature and role of school science laboratories have been subject to widespread controversy in the research community (NRC 1996), especially regarding the benefits of physical, virtual, and combined laboratories (Olympiou and Zacharia 2012;Triona and Klahr 2003;Zacharia 2007). The popularity of simulation environments such as PhET (Perkins et al. 2006) has led policy-makers and scholars to question the real value of physical laboratories-especially in the face of the associated costs and logistics. A wave of research studies within the past 10 years has explored: (a) What are the advantages of physical laboratories relative to virtual laboratories and manipulatives, (b) whether the latter can replace the former (Triona and Klahr 2003), and (c) in what ways virtual models can simulate complex phenomena and permit student experimentation in domains that might otherwise be costly, impractical, or dangerous (Finkelstein et al. 2005;Jaakkola and Nurmi 2008;Jaakkola et al. 2011;Klahr et al. 2007; Perkins et al. 2006;Resnick and Wilensky 1998).The literature comparing hands-on or physical models (PM) with virtual models (VM) for science learning has sought to establish rules for choosing one modality over the other or for ordering them as distinct phases in a sequential process (de Jong et al. 2013). Zacharia and Anderson (2003) found that combining physical and virtual models increased teachers' learning of content knowledge in physics. Zacharia and Constantinou (2008) virtual laboratories led to greater conceptual understandings than did either type singly. For example, Liu (2006) compared groups of female high school students utilizing computer simulations and/or hands-on laboratory activities in chemistry. Controlling for time-on-task, the combination of both PM and VM was more effective than either option alone. But interesting interactions between content learning and epistemology were observed for this composite approach: There was a correlation between students' understanding o...

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Section: Discussionmentioning

confidence: 99%

Using the Bifocal Modeling Framework to Resolve “Discrepant Events” Between Physical Experiments and Virtual Models in Biology

2016

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“…The idea of epistemic games (e-games) was first introduced as a set of rules and strategies that guide inquiry, focusing on expert scientific inquiry across disciplines [1]. Tuminaro and Redish [2,3] subsequently generalized e-games to be descriptive rather than normative, and generalized the theory to include introductory physics students as well as experts.…”

Section: Introductionmentioning

confidence: 99%

Epistemic game for answer making in learning about hydrostatics

Chen

Irving

Sayre

2013

Phys. Rev. ST Phys. Educ. Res.

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Previous research into problem solving in physics resulted in researchers introducing six epistemic games to describe the organizational structures of locally coherent resources. We present a new epistemic game-the ''answer-making epistemic game''-which was identified in this paper through the analysis of interviews carried out to validate a survey focusing on students' understanding of Archimedes' principle and Pascal's law. In the game, the ultimate goal is a solution to a problem posed by the survey. Students may remember or intuit an answer, then use conceptual and/or mathematical reasoning to justify it. Alternately, they may use conceptual and/or mathematical reasoning to generate an answer. We demonstrate how students generate their solutions using these two different paths and discuss some implications for instruction.

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“…Spreadsheets, outliners, graphers, and other such tools provide representational guidance that help learners see certain patterns, express certain abstractions in concrete form, and discover new relationships. Representational tools can be designed based on cognitive analysis to address particular learning objectives [Koedinger, 1991;Reiser et al, 1991] and can function as "epistemic forms" [Collins & Ferguson, 1993] that afford desirable knowledge-building interactions. Yet representational tools provide only a subtle kind of guidance.…”

Section: Components For Intelligent Learning Environmentsmentioning

confidence: 99%

Component-Based Construction of a Science Learning Space

Koedinger

Suthers

Forbus

1998

Intelligent Tutoring Systems

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Abstract. We present a vision for learning environments, called Science Learning Spaces, that are rich in engaging content and activities, provide constructive experiences in scientific process skills, and are as instructionally effective as a personal tutor. A Science Learning Space combines three independent software systems: 1) lab/field simulations in which experiments are run and data is collected, 2) modeling/construction tools in which data representations are created, analyzed and presented, and 3) tutor agents that provide just-in-time assistance in higher order skills like experimental strategy, representational tool choice, conjecturing, and argument. We believe that achieving this ambitious vision will require collaborative efforts facilitated by a component-based software architecture. We have created a feasibility demonstration that serves as an example and a call for further work toward achieving this vision. In our demonstration, we combined 1) the Active Illustrations lab simulation environment, 2) the Belvedere argumentation environment, and 3) a modeltracing Experimentation Tutor Agent. We illustrate student interaction in this Learning Space and discuss the requirements, advantages, and challenges in creating one.

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Epistemic forms and Epistemic Games: Structures and Strategies to Guide Inquiry

Cited by 265 publications

References 11 publications

Using the Bifocal Modeling Framework to Resolve “Discrepant Events” Between Physical Experiments and Virtual Models in Biology

Using the Bifocal Modeling Framework to Resolve “Discrepant Events” Between Physical Experiments and Virtual Models in Biology

Epistemic game for answer making in learning about hydrostatics

Component-Based Construction of a Science Learning Space

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