Modeling with Embodiment for Inquiry-Based Science Education

Bibliographic Data

ID22047080
AuthorsJordi Solbes (0000-0002-8220-209X, Universitat de València), Rafael Palomar (Universitat de València), M Francisca Petit (0000-0001-9750-8879, Universitat de València, corresponding author), Paula Tuzón Marco (0000-0003-1344-3751, Universitat de València, corresponding author)
Year2025
Volume15
Issue7
Pages796
Publication date2025-06-20
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci15070796
OpenAlexW4411471268
LanguageEN
References cited33

Modeling is a fundamental scientific procedure for understanding nature, and it is also one of the basic strategies in inquiry-based science education. Among the various tools available for modeling, this article focuses on investigating a particular framework that uses embodiment to understand both macroscopic and microscopic phenomena. Within this approach, students actively engage as agents in the model and together build the final representation. For that, we present a specific methodology (the IBME approach) for inquiry-based modeling with embodiment. We specify the steps of the modeling approach, which were subsequently tested through instructional sequences based on this method with second-year students obtaining a degree in Primary Education at a public university. We analyzed the instructional sequences both quantitatively and descriptively. The quantitative analysis compares the results of an experimental group (n= 86) with a control group (n = 68) that does not work with inquiry-based modeling. Both groups address the same concepts, and at the end, they complete a questionnaire. The descriptive analysis discusses the details of the modeling process and the discussions that take place throughout the teaching sequences; on the other hand, it also summarizes the progress in the modeling process based on three qualitative parameters. The results obtained after implementing these sequences show significant differences compared to the control group. The descriptive analysis illustrates how students are able to reach the final model by inquiry, that is, through the discussion fostered by the modeling process itself, involving models of different levels of complexity

Descriptive statistics · Epistemology · Management science · Mathematics education · Scientific modelling · Computer Science · Engineering · Genetics, Bioinformatics, and Biomedical Research · Innovative Teaching Methods · Mathematics · Psychology · Science Education and Pedagogy · Artificial Intelligence

Tools

Open DOIOpen Access