The DOI matches its Crossref record.
Integrated STEM Education
Abstract
This chapter provides an overview of what &s;integrated STEM (Science, Technology, Engineering and Mathematics)&s; is-from its forms and characteristics to the practices and pedagogical approaches involved. It describes the forms of STEM integration followed by the hallmark characteristics of integrated STEM learning environment. STEM integration in the classroom generally takes one of three forms: content integration, supporting content integration, or context integration Content integration refers to units and activities that have multiple STEM disciplinary learning objectives. Context integration uses a context from one discipline to situate learning objectives from another discipline. Supporting content integration is common in the classroom, but often not done in a way that furthers the learning of the supporting content. Instructional approaches including problem-based learning and project-based learning, discussed in this chapter, are examples of the types of approaches conducive to teaching integrated STEM in K-12 classrooms. The biology provides important opportunities to discuss other aspects of K-12 engineering standards, for example ethics of cloning and genetic engineering.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Bryan et al. (2015) argued that robots were designed to develop multiple learning goals from STEM knowledge, beginning with an initial learning context.
“Bryan et. al. (2015) argued that robots were designed to develop multiple learning goals from STEM knowledge, beginning with an initial learning context.”
From Trends and research foci of robotics-based STEM education: a systematic review from diverse angles based on the technology-based learning model (2023) · cites this paper as Bryan et al., 2015
Students can develop a deep and transferable understanding of interdisciplinary phenomena and problems through emphasizing the content across disciplines.
“students can develop a deep and transferable understanding of interdisciplinary phenomena and problems through emphasizing the content across disciplines (Bryan etal., 2015).”
From Trends and research foci of robotics-based STEM education: a systematic review from diverse angles based on the technology-based learning model (2023) · cites this paper as Bryan et al., 2015
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 1
- Barell, J. (2006). Problem-based learning: An inquiry approach. Thousand Oaks, CA: Corwin Press.
Cited by
Sorted by citations
Darmawansah, D., Hwang, G.-J., Chen, M.-R. A., & Liang, J.-C. (2023) · International Journal of STEM Education · doi:10.1186/s40594-023-00400-3 · Cited by 147
“Bryan et. al.”
BackgroundA Proposed Taxonomy of Teaching Models in STEM Education: Robotics as an Example
Zhong, B., Liu, X., Xia, L., & Sun, W. (2022) · Sage Open · doi:10.1177/21582440221099525 · Cited by 44
Metadata
- Authors
- Bryan, L. A., Moore, T. J., Johnson, C. C., & Roehrig, G. H.
- Affiliations
- Purdue University West Lafayette (US)
- Venue
- STEM Road Map
- Publisher
- Routledge
- Published
- 2015-07-03
- Pages
- 23-37
- OpenAlex
- W2573402628
- Cited by
- 233
- References
- 0
- Citations by year
- 2026: 12 · 2025: 23 · 2024: 24 · 2023: 34 · 2022: 40 · 2021: 25 · 2020: 24 · 2019: 22 · 2018: 20 · 2017: 4 · 2016: 4
- FWCI
- 44.33
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Education › STEM Education
- Social Sciences › Education › Problem and Project Based Learning
- Keywords
- STEM integration, content integration, contextual integration, problem-based learning, project-based learning, biology education, cloning ethics, genetic engineering
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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