Scientific understandings revealed by students' computer models of a stream: A Trickle or a Flood? (original) (raw)
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This study uses interview data involving a variety of modeling contexts to investigate eighth grade students' beliefs about the nature and purpose of scientific models. The participants have been exposed to modeling curricula for the past three years, allowing us to ask questions in a variety of familiar modeling contexts as well as in a novel context introduced during the interview. Results indicate that, overall, students' responses are more consistent when reasoning about familiar modeling contexts than novel contexts, although some students do give very consistent responses across all contexts. All students were able to talk about previous models they had worked with and articulate similarities across them. Students are most likely to talk about models as showing processes and explanations, and some also mentioned models as generalizing to new cases when this was a salient feature of the context.
Cognitive processes enacted by learners during co-construction of scientific models
Proceedings of the 3rd International Constructionism Conference 19-23 August 2014, Vienna, Austria
This study documents our effort to analyze students' cognitive processes during modeling-based learning. A modeling-based teaching intervention was developed and implemented during a summer science class at the University of Cyprus (n=17). Students worked in small groups to develop successive models of simple systems in the topic of heat and temperature using DynaLearn as a modeling tool. Students' conversations were videotaped and transcribed using the software Transana. Additionally, students' work and conversations were analyzed with a combination of two techniques; a video analysis framework which considers classwork at three different scales (macro-, meso-, microscale) and a coding scheme for students' cognitive process during modeling. This paper presents the work of two groups of students. Results indicate differences and similarities in the actual work and the cognitive processes of the two groups at the three scales of analysis. We discuss those differences and similarities as well as their significance for science education.
2009
Modeling is a core practice in science and a central part of scientific literacy. We present theoretical and empirical motivation for a learning progression for scientific modeling that aims to make the practice accessible and meaningful for learners. We define scientific modeling as including the elements of the practice (constructing, using, evaluating, and revising scientific models) and the metaknowledge that guides and motivates the practice (e.g., understanding the nature and purpose of models). Our learning progression for scientific modeling includes two dimensions that combine metaknowledge and elements of practice—scientific models as tools for predicting and explaining, and models change as understanding improves. We describe levels of progress along these two dimensions of our progression and illustrate them with classroom examples from 5th and 6th graders engaged in modeling. Our illustrations indicate that both groups of learners productively engaged in constructing and revising increasingly accurate models that included powerful explanatory mechanisms, and applied these models to make predictions for closely related phenomena. Furthermore, we show how students engaged in modeling practices move along levels of this progression. In particular, students moved from illustrative to explanatory models, and developed increasingly sophisticated views of the explanatory nature of models, shifting from models as correct or incorrect to models as encompassing explanations for multiple aspects of a target phenomenon. They also developed more nuanced reasons to revise models. Finally, we present challenges for learners in modeling practices—such as understanding how constructing a model can aid their own sensemaking, and seeing model building as a way to generate new knowledge rather than represent what they have already learned.
The Effect of Classroom Practice on Students Understanding of Models
umich.edu
Science instruction focused around modeling can help learners develop deep understanding of subject matter and the nature of science. Despite its importance, students typically do not develop an understanding of modeling, and many teachers lack strategies for supporting their students in the practice. This research examines a teacher and her students' developing an understanding of models and modeling by taking part in an 8-weeks 6 th grade chemistry unit that focuses on the particle nature of matter, models and modeling. The unit was developed as part of IQWST: a middle school inquirybased curriculum development project. The curriculum closely integrates content learning goals with scientific practices. Modeling learning goals as well as meta-knowledge of models and modeling were highly specified. To assess the effect of teacher practice and the change in students' meta-knowledge of models and modeling, various types of data were collected: Pre and post students and teacher interviews, videotapes of lessons, students artifacts, and open-ended pre-post assessment items that involved the use of models. Preliminary findings suggests that students improve their modeling practices and understanding of the meta-knowledge associated with the practice. Links can be drawn between students' improvement and instruction. Some changes in the teachers' perception of modeling as a classroom practice are also observed. that focuses on the particle nature of matter, models and modeling. The curriculum closely integrates content learning goals, with scientific practices. Modeling learning goals as well as meta-knowledge of models and modeling were highly specified. We were mostly interested in finding links between specific classroom practices and students' improvement in the practice and in understanding modeling meta-knowledge (MMK). We were also interested in learning about the teachers' conceptions of modeling, as revealed in pre post interviews and in her actual teaching.
An epistemological approach to modeling: Cases studies and implications for science teaching
Science Education, 2008
Models and modeling are a major issue in science studies and in science education. In addressing such an issue, we first propose an epistemological discussion based on the works of Cartwright (1983, 1999), Fleck (1935/1979), and Hacking (1983). This leads us to emphasize the transitions between the abstract and the concrete in the modeling process, by using the notions of nomogical machine (Cartwright, 1999), language game (Wittgenstein, 1953/1997), and thought style (Fleck, 1935/1979). Then, in the light of our epistemological approach, we study four cases coming from the implementations of research-based design activities (SESAMES, 2007). These four case studies illustrate how students are engaged in constructing relations between the abstract and the concrete through modeling activities, by elaborating at the same time specific language games and appropriate thought styles. Finally, we draw some implications for science teaching. It is suggested that considering didactic nomological machines as embedding knowledge on the one hand, and classes as thought collectives, on the other hand, may relevantly contribute to science education and science education research.
Construction and Abstraction: Contrasting Methods of Supporting Model Building in Learning Science
Interactive Learning Systems can offer students a range of representations, tools, environments and assistance to construct a model which reflects their understanding of a situation which exists in the real world. They can also offer a range of possibilities for learners to improve their communicative competence and articulate their understandings to themselves, to others or to the system itself. However, the relationship between interactivity, learning and communication is complex and can involve humans, artefacts or a combination of both. Theories based on the promotion of productive interactivity between humans in order to engender individual learning development, such as that of Vygotsky can be found at the heart of much work on the design of Interactive Learning Environments (ILEs) (Guzdial et al.example). But what do we mean by Interactive and what is the relationship between Interactivity and