Prospective elementary teachers’ perceptions of the processes of modeling: A case study

Fazio, Claudio; Paola, Benedetto Di; Guastella, Ivan

doi:10.1103/physrevstper.8.010110

Cited by 15 publications

(18 citation statements)

References 31 publications

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“…In [14] authors discuss a study on the approaches to model the students of the 4-year elementary school teacher program at the University of Palermo, Italy. The answers to a specially designed questionnaire are analyzed on the basis of an a priori analysis made using a general scheme of reference on the epistemology of mathematics and physics.…”

Section: Related Workmentioning

confidence: 99%

Analysis of Bejaia University Computer Science students' marks through the CHIC software and Statistical Implicative Analysis

Khaled

Ghanem

Couturier

2014

2014 4th International Symposium ISKO-Maghreb: Concepts and Tools for Knowledge Management (ISKO-Maghreb)

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Through the study of the Bejaia's University students' marks in Computer Science, we want to show the interest of the Statistical Implicative Analysis (SIA). This method, developed by Régis Gras and his collaborators, is used to discover and analyze the most relevant implications between different studied modules. CHIC (Cohesive Hierarchical Implicative Classification) is a software implementing most of the methods defined under the framework SIA. An analysis of the relations between the modules is given according to students' marks. We comment the results through different years.

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Section: Related Workmentioning

confidence: 99%

Analysis of Bejaia University Computer Science students' marks through the CHIC software and Statistical Implicative Analysis

Khaled

Ghanem

Couturier

2014

2014 4th International Symposium ISKO-Maghreb: Concepts and Tools for Knowledge Management (ISKO-Maghreb)

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“…And, according to Megowan-Romanowicz [9], over 3,000 teachers have participated in training for Modeling Instruction. Taken together, this literature [9,[46][47][48][49][50][51][52][53][54][55] paints a picture of both need and promise for model-centered teacher professional development.…”

Section: B Instructors' Understanding and Use Of Modelingmentioning

confidence: 99%

“…Last, in contrast to one of the trends in K-12 science education research [46][47][48][49][50][51], our study was not designed to probe instructors' metamodeling knowledge. Rather, it was designed to determine whether and how instructors value or implement various modeling subtasks in their classrooms.…”

Section: A Limitationsmentioning

confidence: 99%

Characterizing lab instructors’ self-reported learning goals to inform development of an experimental modeling skills assessment

Dounas-Frazer

Rios

Pollard

et al. 2018

Phys. Rev. Phys. Educ. Res.

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The ability to develop, use, and refine models of experimental systems is a nationally recognized learning outcome for undergraduate physics lab courses. However, no assessments of students' model-based reasoning exist for upper-division labs. This study is the first step toward development of modeling assessments for optics and electronics labs. We interviewed 35 lab instructors about the ways they incorporate modeling in their courses, and we used their self-reported learning goals and activity designs to identify test contexts and objectives that are likely relevant across many institutional settings. The study design was informed by the Modeling Framework for Experimental Physics, which conceptualizes modeling as consisting of multiple subtasks: making measurements, constructing system models, comparing data to predictions, proposing causes for discrepancies, and enacting revisions to models or apparatus. We found that each modeling subtask was identified by multiple instructors as an important learning outcome for their course. Based on these results, we argue that test objectives should include probing students' competence with most modeling subtasks, and test items should be designed to elicit students' justifications for choosing particular modeling pathways. In addition to discussing these and other implications for assessment, we also identify future areas of research related to the role of modeling in optics and electronics labs. *

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“…The questionnaire is made up of four open-ended questions, which focus on the understanding of the modeling concept (see Appendix 1). They are part of a more complex questionnaire, which has already been validated and used in previous research (Fazio & Spagnolo, 2008;Fazio et al, 2012). We chose to analyze a questionnaire with a low number of questions in order to easily describe the process of clustering data interpretation in terms of the answering strategies related to the questions.…”

Section: Context and Research Questionsmentioning

confidence: 99%

“…Fazio et al (2012Fazio et al ( , 2013 analyze students' responses to specially designed questionnaires using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of relevant physics content. Through cluster analysis methods groups of students showing remarkable similarity in the reasoning categories are identified and the consistency of their deployed mental models is validated by comparison with researcher-built ideal profiles of student behavior known from previous research.…”

Section: Introductionmentioning

confidence: 99%

A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

Battaglia

Paola

Fazio

2017

EURASIA J MATH SCI T

Self Cite

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Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. In this paper two different Cluster Analysis methods are described and the variables and parameters involved are discussed in order to clarify the information that they can supply. The clustering results obtained by using the two methods are compared and showed a good coherence between them. The results are interpreted and compared with the literature. More detail about the relationship between different student conceptions of modeling in physics was obtained.

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Prospective elementary teachers’ perceptions of the processes of modeling: A case study

Cited by 15 publications

References 31 publications

Analysis of Bejaia University Computer Science students' marks through the CHIC software and Statistical Implicative Analysis

Analysis of Bejaia University Computer Science students' marks through the CHIC software and Statistical Implicative Analysis

Characterizing lab instructors’ self-reported learning goals to inform development of an experimental modeling skills assessment

A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

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