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Which Knowledge Do Pre-Service Teachers Need to Meaningfully Engage in Modeling?

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Title: Which Knowledge Do Pre-Service Teachers Need to Meaningfully Engage in Modeling?
Language: English
Authors: Paul Engelschalt (ORCID 0000-0003-2638-7381), Erik Maslyak, David Fortus (ORCID 0000-0002-6157-4505), Dirk Krüger (ORCID 0000-0003-0999-4382), Annette Upmeier zu Belzen (ORCID 0000-0002-1465-7519)
Source: Journal of Research in Science Teaching. 2026 63(4-5):352-371.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 20
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Knowledge Base for Teaching, Preservice Teachers, Models, Science Instruction, Science Process Skills, Cognitive Processes
DOI: 10.1002/tea.70047
ISSN: 0022-4308
1098-2736
Abstract: Modeling involves a set of scientific practices that pre-service science teachers struggle with. These practices involve constructing, predicting, testing, and revising models. Engaging meaningfully in modeling practices leads modelers to gain new insights about phenomena. Research suggests that this requires domain-general metamodeling knowledge and domain-specific content knowledge. However, research has not yet systematically investigated the role of metamodeling and content knowledge in the modeling practices, particularly regarding which practices benefit from either knowledge facet or their interplay. Addressing this gap, we interviewed 17 pre-service science teachers selected from a larger quantitative study based on their performance in metamodeling knowledge and modeling practice assessments. We showed participants their answers to the modeling practice assessments and asked them to recall their thinking. We analyzed their thinking processes, focusing on metamodeling and content knowledge application. By comparing high- and low-modeling-practice performers, we aimed to examine the role of these knowledge facets in modeling practices. Our study extends modeling literature with two main findings: First, both metamodeling and content knowledge supported the participants in engaging in modeling practices, but each practice had specific knowledge requirements. For instance, constructing models was driven by content knowledge, while an interplay between metamodeling and content knowledge supported revising models. Second, the metamodeling knowledge that participants demonstrated in the previous metamodeling knowledge assessment was not related to the metaknowledge they applied during modeling practices. This is best evidenced in testing models, for which participants frequently recalled metaknowledge they had not demonstrated in the previous metamodeling knowledge assessment. Our findings suggest that teaching modeling practices separately is probably beneficial, as this approach enables science educators to better scaffold practice-specific knowledge requirements. For future research, our results question the meaningfulness of metamodeling knowledge assessments, as the knowledge demonstrated in such assessments does not indicate the knowledge learners actually apply when engaging in modeling practices.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1504473
Database: ERIC
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  Data: Which Knowledge Do Pre-Service Teachers Need to Meaningfully Engage in Modeling?
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  Data: <searchLink fieldCode="AR" term="%22Paul+Engelschalt%22">Paul Engelschalt</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2638-7381">0000-0003-2638-7381</externalLink>)<br /><searchLink fieldCode="AR" term="%22Erik+Maslyak%22">Erik Maslyak</searchLink><br /><searchLink fieldCode="AR" term="%22David+Fortus%22">David Fortus</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6157-4505">0000-0002-6157-4505</externalLink>)<br /><searchLink fieldCode="AR" term="%22Dirk+Krüger%22">Dirk Krüger</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0999-4382">0000-0003-0999-4382</externalLink>)<br /><searchLink fieldCode="AR" term="%22Annette+Upmeier+zu+Belzen%22">Annette Upmeier zu Belzen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1465-7519">0000-0002-1465-7519</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Research+in+Science+Teaching%22"><i>Journal of Research in Science Teaching</i></searchLink>. 2026 63(4-5):352-371.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: Modeling involves a set of scientific practices that pre-service science teachers struggle with. These practices involve constructing, predicting, testing, and revising models. Engaging meaningfully in modeling practices leads modelers to gain new insights about phenomena. Research suggests that this requires domain-general metamodeling knowledge and domain-specific content knowledge. However, research has not yet systematically investigated the role of metamodeling and content knowledge in the modeling practices, particularly regarding which practices benefit from either knowledge facet or their interplay. Addressing this gap, we interviewed 17 pre-service science teachers selected from a larger quantitative study based on their performance in metamodeling knowledge and modeling practice assessments. We showed participants their answers to the modeling practice assessments and asked them to recall their thinking. We analyzed their thinking processes, focusing on metamodeling and content knowledge application. By comparing high- and low-modeling-practice performers, we aimed to examine the role of these knowledge facets in modeling practices. Our study extends modeling literature with two main findings: First, both metamodeling and content knowledge supported the participants in engaging in modeling practices, but each practice had specific knowledge requirements. For instance, constructing models was driven by content knowledge, while an interplay between metamodeling and content knowledge supported revising models. Second, the metamodeling knowledge that participants demonstrated in the previous metamodeling knowledge assessment was not related to the metaknowledge they applied during modeling practices. This is best evidenced in testing models, for which participants frequently recalled metaknowledge they had not demonstrated in the previous metamodeling knowledge assessment. Our findings suggest that teaching modeling practices separately is probably beneficial, as this approach enables science educators to better scaffold practice-specific knowledge requirements. For future research, our results question the meaningfulness of metamodeling knowledge assessments, as the knowledge demonstrated in such assessments does not indicate the knowledge learners actually apply when engaging in modeling practices.
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