REVIEW article

Front. Educ., 11 April 2025

Sec. STEM Education

Volume 10 - 2025 | https://doi.org/10.3389/feduc.2025.1547994

Core concept identification in STEM and related domain education: a scoping review of rationales, methods, and outputs

  • 1. Pharmacy and Pharmaceutical Sciences Education Research Theme, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville Campus, VIC, Australia

  • 2. Department of Pharmaceutical Care and Health Systems, University of Minnesota College of Pharmacy-Twin Cities, Minneapolis, MN, United States

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Abstract

Core concepts—fundamental, enduring, and discipline-specific ideas—are essential for enhancing comprehension and facilitating knowledge acquisition for STEM and health-related learners. Since the 1990s, many articles have been published in STEM and health-related domains explaining the need and/or the value of identifying and utilizing core concepts in education. However, little research has explored the reasons for and methods for identifying the core concepts that may be useful to curriculum designers, course coordinators, instructors and assessment specialists in STEM and health sciences faculties. This scoping review examines the research on core concept identification within the context of STEM and Health-related domains of education with three objectives: (1) to describe the rationale for identifying core concepts; (2) to identify the study designs and research approaches employed; and (3) to present key outputs about core concept identification across domains. Using scoping review methodology aligned with Arksey and O’Malley’s framework, eligible studies addressing core concept identification with a methodological description of how these concepts were identified for formal education in a STEM or health-related domain were identified through Medline ALL and Scopus database, complemented with backward citation of all included full-text references. Thirty research publications were identified, and data was systematically extracted and analyzed according to the review objectives. The review identified seven rationales for core concept identification, the most common being content prioritization, which addresses the need to identify essential teaching content within expanding knowledge bases. Mixed methods were the predominant research approach (n = 20), with various data collection and analysis methods, most of which are aligned with pragmatic philosophical worldviews, strongly emphasizing expert-driven techniques. These findings provide valuable insights for educators and researchers engaging in core concept identification, offering guidance for methodology selection and implementation while highlighting areas requiring further development in the field.

1 Introduction

Core concepts are the big ideas that are essential to the understanding and practice of a discipline, the mastery of these concepts resulting in enduring understanding and the ability to address novel problems across that discipline (McFarland and Michael, 2020). These core concepts help learners develop appropriate structures for understanding and organizing discipline-specific knowledge; retain key concepts long after specific details are forgotten; solve discipline-specific problems, and transfer learning across different areas of a field (Michael et al., 2017). These concepts have underpinned education for decades, particularly in Science, Technology, Engineering, Mathematics (STEM), and health-related fields. Identifying core concepts in education is crucial as they provide a structured framework for organizing knowledge, facilitating deeper understanding, and establishing consistency across disciplines, thereby enhancing the application of learning across various contexts. These big ideas are considered central to a discipline and help in transferring learning beyond rote memorization. The value of core concepts is realized not only in their identification but also in how they are applied and integrated with other active learning strategies.

In STEM education, core concepts have gained prominence for their ability to support the structuring of information into coherent patterns and establish common vocabulary frameworks (Bacon, 1979; D'Avanzo, 2008; Chen et al., 2022). Their implementation streamlines knowledge acquisition by focusing on fundamental ideas rather than overwhelming students with excessive facts, which is particularly important given the rise in disciplinary knowledge explosion (Michael et al., 2017). Research demonstrates that core concepts enhance student learning and comprehension (Wood, 2008; Koba and Tweed, 2009), support curriculum development (Ball, 2023; Barrett et al., 2023), and improve assessment practices (Libarkin and Ward, 2011). When integrated into classroom instruction, these interventions effectively improve students’ “big picture” understanding (Schaefer and Hannah, 2023).For health professionals, core concepts help educators prioritize and benchmark their curriculum, facilitate integration with other disciplines, and improve the application of knowledge to professional contexts like safe prescribing practices (Guilding et al., 2023). They have also been used as a framework to link student learning to program objectives in undergraduate medical education (Averill et al., 2022).

The identification and application of core concepts in education are grounded in several complementary theoretical perspectives. Ausubel’s theory of meaningful learning(Ausubel, 1966; Ausubel, 2012) provides a fundamental foundation, distinguishing between rote and meaningful learning. Learning becomes meaningful when new information integrates into existing cognitive structure, and reorganized or transformed to create desired outcomes or discover relationships. Core concepts, the “big ideas” of a domain serve as cognitive anchors for this integration process. Building on Ausubel’s work, concept mapping(Novak and Cañas, 2008) demonstrates how educators can help students develop mental models and conceptual frameworks to make meaning of new content. This approach supports the paradigm shift from teaching isolated facts to shaping conceptual understanding through Concept-Based Curriculum and Instruction (CBCI), where topics, facts, and skills become tools for understanding deeper conceptual structures (Erickson et al., 2017). Core concepts also facilitate transfer of learning—applying knowledge across contexts—which is central to the Understanding by Design framework (Wiggins and McTighe, 2005) commonly used in curriculum development. These theoretical perspectives converge to establish core concepts as pedagogically powerful tools grounded in principles of human learning, supporting the movement from transmitting isolated facts toward developing conceptual understanding and adaptive expertise.

In light of this, educational researchers in various fields have sought to identify and characterize the core concepts within their domains. Many STEM domains—contextualized here as disciplines or fields of knowledge — have identified, selected, and applied these concepts to their educational practice (Gray et al., 2019). However, despite these efforts, few publications describe the methods for identifying these core concepts, and no comprehensive resource exists to guide researchers in this process. Such guidance could save researchers time and effort, potentially enhancing the process, quality, and application of core concepts in education. This is particularly important because developing these core concepts has been reported to be intellectually demanding and time-consuming for educators, who have numerous competing professional endeavors (Mitchell et al., 2017).

A knowledge synthesis of how and why core concepts are identified would be helpful for educators including program directors, curriculum committees, course coordinators, faculty, instructors and assessment specialists embarking on this process. Several scholars who have launched into core concept identification for their domain provide rich and relevant literature reviews in their publications, albeit always focused on the specifics of their domain (McFarland and Michael, 2020; White et al., 2021; Chen et al., 2022). A mini-review further advances the STEM education literature by comparing how physiology and neuroscience developed their core concepts, revealing that effective concept identification must consider disciplinary context, implementation challenges, and educational goals while also providing a framework for other STEM fields to develop their core concepts through documented lessons and identified research needs (Schaefer and Michael, 2024). While these reviews offer valuable insights, they do not fully illustrate the broader context of core concept identification within STEM and health-related fields. This scoping review article aims to understand core concept identification, focusing on the rationale, methodologies, and key outcomes across STEM and health-related domains.

2 Methods

2.1 Methodological justification

The frameworks proposed by Munn and colleagues that provides guidance for authors when choosing between a systematic or scoping review approach (Munn et al., 2018) and Arksey and O′Malley’s methodological framework for scoping studies were selected as they align with our research needs by focusing on identifying available evidence, clarifying key concepts, examining research methods, and analyzing knowledge gaps---objectives that are central to our review. The framework (Arksey and O'Malley, 2005) comprises six stages: (1) identifying the research question, (2) identifying relevant studies, (3) applying predetermined criteria to select studies, (4) charting relevant data, and (5) collating, summarizing, and reporting the results. We excluded the optional consultation exercise since it was irrelevant to our review.

In line with the first stage of the framework, the primary research question was framed using the PICo (Phenomena of Interest, Context) framework (

McArthur et al., 2015

): “What methodological approaches have previous studies used to identify core concepts [Phenomenon of Interest] within STEM and health-related educational fields [Context]?” To address this question, our research objectives are:

  • To identify the rationale for core concept identification, focusing on the reasons or factors driving the process.

  • To identify the research design used for core concept identification, including the specific methods employed.

  • To present key outputs about core concept identification across structured domains, including the number, examples, and reported intentions of the core concepts identified.

2.2 Protocol and reporting

This scoping review protocol was guided by the methodological framework developed by Arksey and O’Malley, revised by all research team members, and registered prospectively on Open Science Framework (Etukakpan et al., 2024). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) was used to guide reporting (Tricco et al., 2018).

2.3 Eligibility criteria

The specific eligibility criteria used to guide the identification and selection of sources of evidence are summarized in Table 1. Studies were included if they aligned with the operational definition of core concepts (i.e., fundamental, enduring, useful, and discipline-specific ideas that underpin a field of knowledge). We focused on studies within STEM and health-related domains that pertained to formal education, defined as institutionalized, intentional and planned through public or recognized private bodies (Schneider, 2013), including primary, secondary, and post-secondary education. To ensure comprehensive coverage of relevant literature, only studies published in English were considered, and no date restrictions were applied.

Table 1

CriterionIncludedExcluded
Phenomenon of interestStudies that
Align with the operational definition of core concepts
AND
Provide a methodological description of how the core concepts were identified
Studies that
Do not align with our operational definition
AND / OR
Do not have a methodological description of how the core concepts were identified
ContextFormal education
AND
STEM/health-related field
Non-formal education
AND/OR
Non-STEM/health-related field
Publication TypePeer-reviewed publications, including original research and conference proceedings.Publications lacking methodological descriptions, such as opinion pieces, commentaries, and articles focused on the authors’ personal views, were excluded.

Inclusion and exclusion criteria.

2.4 Information sources

Prior to database selection, we conducted a preliminary assessment using a predetermined gold-set of articles(Quirk et al., 2024; Nosratzadeh et al., 2025) that met our inclusion criteria as a means to test the search strategy’s sensitivity (ability to identify relevant studies) and specificity (ability to exclude irrelevant studies; Hub, 2025). This step helped identify the most appropriate databases for our review. Relevant studies were identified using two primary electronic databases: Medline(R) ALL via Ovid and Scopus. These databases were chosen because they provided the highest yield of articles from our gold set of articles, demonstrating optimal coverage of our target literature.

2.5 Search strategy

The search strategy focused on three main concepts: (1) core concepts and related synonyms, (2) STEM and health-related domains using an exhaustive list of STEM and health-related domains, and (3) the educational context, using “education” and related synonyms. The search strategy was developed iteratively in consultation with an experienced librarian and refined by testing various combinations of terms across the databases.

The science education literature and recent STEM reform proposals consistently employ several related terms: concepts, core concepts, concept learning, and foundational concepts, which appear throughout discussions across all STEM fields (Michael et al., 2017). This observation necessitated the development of our operational definition of core concepts as fundamental, enduring, useful, and discipline-specific ideas underpinning a field of knowledge to support the identification and selection of studies.

A search log was maintained throughout this process to track details such as the date, time, search terms, and databases used. The final search string (see Supplementary material 1), which yielded the most comprehensive capture of our gold set articles, was implemented for this review on March 1st, 2024. All search results and citations were imported into EndNote (Version 20, Clarivate Analytics, Philadelphia, PA, United States) for an initial deduplication process. The deduplicated library was then transferred to Covidence (Covidence, Melbourne, VIC, Australia) systematic review software, where a secondary deduplication process was performed before the screening process.

2.6 Selection of sources of evidence

The evidence selection process involved two stages: Title with abstract and full-text screening. A complete dual review approach (Stoll et al., 2019) was followed, where two independent reviewers, AUE and AKN, screened each title and abstract against the predetermined inclusion and exclusion criteria. A third independent reviewer, PJW, resolved conflicts. During the full-text screening, two reviewers (from the pool of co-authors AUE, TA, MW, and KJ) independently assessed each article, documenting reasons for exclusion. A third reviewer (PJW) resolved conflicts at this stage. The search was complemented with backward citation searching of identified full-text publications.

2.7 Data charting process

Data extraction was conducted for all 30 included publications to obtain key study characteristics, such as the citation, country of authors, domain (field of knowledge), and aims/purpose. Subsequent extractions were organized according to the three main research objectives of the scoping review. For each review objective, specific data extraction approaches were implemented:

For review objective 1, AUE conducted a content analysis (Morse, 2008) of the reasoning behind core concept identification, as presented in the background sections of the included publications. Initial coding involved assigning summative words or short phrases to specific text segments that captured the essence of the authors’ reasoning for core concept identification. These coded text segments were extracted from the publications and organized using Excel (Microsoft Corporation, Redmond, WA) and Miro (RealtimeBoard Inc., San Francisco, CA). Following the initial coding, repetitive or consistent patterns in the codes (occurring more than twice in the data) were identified and grouped together (Wolgemuth et al., 2024). These patterns were then consolidated into broader categories, each representing a distinct rationale for core concept identification. This enabled identifying and describing categories as rationales for core concept identification.

For review objective 2, which focused on the research design used for core concept identification and the specific methods employed, data was extracted from the methods sections of the included studies. Key methodological characteristics were charted to enhance understanding of the research designs. This included:

  • Participant types, i.e., the study participants or groups selected for the research.

  • Criteria for core concepts, including examples of criteria used across publications and how they were applied in the research methods.

  • Methods were charted into two categories: (a) methods used for candidate concept identification (approaches for gathering an initial/preliminary list of concepts) and (b) methods used for concept refinement (approaches for further developing the initial list of concepts).

  • Research design, combining methods from both procedural categories

  • The utilization of research frameworks, particularly if any theoretical and/or conceptual frameworks were employed and

  • The utilization of a pilot study

For review objective 3, which focused on presenting findings about core concept identification across domains, data was extracted from the results and discussion sections. This included the total number of core concepts identified in each study, examples of these concepts, the format in which they were presented, and any reported practical intentions for the concepts.

3 Results

3.1 Selection of sources of evidence

Figure 1 shows the flow diagram for the selection of evidence. From an initial pool of 3,447 records (3,429 from database searches and 18 from citation searching), 522 duplicates were removed through Endnote and Covidence screening. Of the remaining 2,925 records screened at the title and abstract stage, 85 were selected for the full-text screening phase. During this phase, 55 records were eliminated primarily because they did not focus on core concepts identification (n = 42), had insufficient methodological description (n = 6), were from non-STEM/health disciplines (n = 3), were non-English language publications (n = 2), or did not focus on formal education (n = 2). This resulted in a final selection of 30 publications for inclusion in the review.

Figure 1

3.2 General characteristics of included publications

The review included 30 research publications on core concept identification for formal education in STEM and health-related domains (see Table 2). The publications span diverse domains, with biochemistry and molecular biology, nursing, pharmacology, psychology, and neuroscience each contributing two publications, while 17 other STEM and health-related domains contributed one. For Neuroscience, the most recent and comprehensive publications for neuroscience were included as multiple papers covered the same research (Chen et al., 2022; Chen et al., 2023). All included publications were post-secondary school level and peer-reviewed except for one report from a professional organization in plant biology (American Society of Plant, 2011). Supplementary material 2 shows an overview of these 30 included publications.

Table 2

CountryDomainNumber of PublicationsCitations
United States of AmericaBiochemistry and Molecular Biology2Tansey et al. (2013); Wright et al. (2013)
Biological Sciences1Michael (2007)
Comparative vertebrate anatomy and morphology1Danos et al. (2022)
Cybersecurity1Parekh et al. (2018)
Digital libraries for the scientific domain (Plate Tectonics, Weather and Climate, and Biological Evolution)1Foster et al. (2012)
Digital logic within computer science and engineering1Herman and Loui (2012)
Evolutionary Developmental Biology1Hiatt et al. (2013)
Evolutionary medicine1Grunspan et al. (2018)
Genetics1Hott et al. (2002)
Interdisciplinary environmental and sustainability (IES)1Horne et al. (2024)
Microbiology1Merkel (2012)
Neuroscience1Chen et al. (2023)
Nursing2Valiga and Bruderle (1994); Giddens and Brady (2007)
Physiology1Michael and McFarland (2011)
Plant Biology1American Society of Plant (2011)
Psychology2Boneau (1990); Zechmeister and Zechmeister (2000)
Thermal and transport science1Streveler et al. (2003)
Toxicology1Gray et al. (2019)
Traffic signals engineering1Hurwitz et al. (2013)
AustraliaBiochemistry1Rowland et al. (2011)
Dietetics1Tweedie et al. (2020)
Physiology1Tangalakis et al. (2023)
Australia and New ZealandPharmacology1White et al. (2021)
ChinaChemistry1Qian et al. (2023)
International collaboration*Pharmacology1White et al. (2022)
New ZealandElectromagnetics1Smaill et al. (2008)
United KingdomBehavioral and social sciences in medicine1Peters and Livia (2006)
Total Publication30

Geographic and domain distribution of included publications.

*

International Collaboration includes Australia, UK, USA, Ireland, Canada, India, China, Brazil, Sweden, Malta, Qatar, Lebanon, Colombia, Nigeria, and Japan.

The geographical distribution of research on core concept identification reveals important patterns in the field. The United States dominates the research landscape, contributing 19 out of 30 publications (63.3%), followed by Australia (including joint work with New Zealand) with 4 publications. Other countries (UK, China, New Zealand) have minimal representation with 1 publication each. One notable international collaboration involved 14 countries, potentially signaling an emerging trend toward global cooperative efforts (White et al., 2022).

3.3 Results for review objective one: rationale for identifying core concepts

The results of content analysis of the background sections from the 30 included publications are shown in Table 3. From this analysis, seven categories of rationales for core concepts identification in STEM and health-related domains emerged. These are content prioritization, conceptual assessment, educational reform, ontological understanding, learning-centric approaches, curriculum design, and resource optimization—spanning from the need to identify essential teaching content within expanding disciplinary knowledge through to optimizing resources to address educational resource constraints. Table 3 presents these categories along with their descriptions, supporting citations, and illustrative examples from the literature. The findings show that these rationales frequently overlap across studies, demonstrating the complex interplay of factors that drive core concept identification across different domains.

Table 3

CategoriesDescriptionSupporting citationIllustrative quote
Content prioritizationEnvelopes the rationale for identifying core concepts based on the need to prioritize essential teaching content, particularly within an expanding knowledge base. This includes establishing a core knowledge base, clarifying critical curriculum concepts, addressing the lack of consensus on core vocabulary and concepts, developing conceptual frameworks, and ensuring alignment between existing core concepts and learning objectives in content-rich curricula.Boneau (1990); Valiga and Bruderle (1994); Zechmeister and Zechmeister (2000); Hott et al. (2002); American Society of Plant (2011); Herman and Loui (2012); Hurwitz et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); Gray et al. (2019); White et al. (2021); Danos et al. (2022); White et al. (2022); Chen et al. (2023); Tangalakis et al. (2023)“The need for community-derived core concepts is pressing, because both the pace of research and number of neuroscience programs are rapidly expanding”(Chen et al., 2023)
Conceptual assessmentEncompasses rationale related to the need for educational aids that support educators in developing concept inventories and assessing conceptual attainment.Streveler et al. (2003); Michael (2007); Smaill et al. (2008); Michael and McFarland (2011); Hiatt et al. (2013); Hurwitz et al. (2013); Tansey et al. (2013); White et al. (2021); Horne et al. (2024)“………… but the lack of such validated and reliable assessment tools has certainly impeded research about the learning of biology and, specifically, physiology.” (Michael, 2007)
Educational reformsReflects rationale driven by calls for educational reforms, specifically the shift toward student-centered learning and conceptual understanding rather than rote memorization.Merkel (2012); Gray et al. (2019); Danos et al. (2022); Chen et al. (2023)“In light of the recommendations coming from the national reports, the Education Board of the American Society for Microbiology decided to revisit the microbiology curriculum guidelines as a strong statement of support for embracing ASM’s recommendations for concept-based, student-centered learning.” (Merkel, 2012)
OntologicalReflects rationale for identifying core concepts based on the inherent nature of how knowledge emerges and is represented within the domain, particularly in contexts with multidisciplinary and interdisciplinary roots.Wright et al. (2013); Parekh et al. (2018); White et al. (2021); Horne et al. (2024)“The multi-disciplinary nature of pharmacology, with roots in biology, chemistry, and physics, and the enormous body of knowledge in this field means that educators struggle to decide what to teach and assess.” (White et al., 2021)
Learning centricCovers rationale focused on facilitating meaningful learning connections. This includes developing conceptual knowledge frameworks, enhancing learners’ conceptual understanding, and identifying and addressing misconceptions or alternative conceptions of learning.Zechmeister and Zechmeister (2000); Streveler et al. (2003); Rowland et al. (2011); White et al. (2021); Qian et al. (2023)“to help students develop a set of key understandings in biochemistry that would enrich their understanding of other courses in their programs of study and be useful to them in the long term, regardless of their career ambitions.” (Rowland et al., 2011)
Curriculum designEnvelopes rationale related to various curriculum development contexts, including informing the curriculum design process, addressing curricular variability, and adopting concept-based curricula.Peters and Livia (2006); Giddens and Brady (2007); Tweedie et al. (2020)“The process for developing a concept-based curriculum starts with an identification of the core (foundational) concepts of the discipline and their definitions followed by the development of exemplars that best illustrate the concept” (Tweedie et al., 2020)
Resources optimizationEncompasses rationales driven by the need to optimize inadequate educational resources, including selection of resources, course development materials, and management of limited training timeFoster et al. (2012); Gray et al. (2019); White et al. (2021); White et al. (2022)“No pharmacology program, however well-resourced, has sufficient time to teach students all the knowledge in the discipline.” (White et al., 2021)

Rationales for core concepts identification in STEM and health-related domains.

3.4 Results for review objective two: research design for identifying core concepts

Table 4 presents a mapping of methodological characteristics found in the core concept identification publications with a focus on the participant types, criteria for core concepts, research frameworks, and the utilization of pilot studies. The findings for criteria for core concepts are organized to highlight those that appeared in three or more instances.

Table 4

Methodological characteristicsDescriptionCitations
Participant typesCategories of individuals involved in the core concept identification process
Domain educators (n = 12)Teaching faculty actively involved in student training, instruction and curriculum deliveryZechmeister and Zechmeister (2000); Hott et al. (2002); Peters and Livia (2006); Michael (2007); Foster et al. (2012); Herman and Loui (2012); Merkel (2012); Tansey et al. (2013); Wright et al. (2013); White et al. (2021); White et al. (2022); Tangalakis et al. (2023)
Domain experts (n = 11)A mix of domain specialists with theoretical and practical knowledge, including educators, professionals, researchers, and textbook authorsBoneau (1990); Streveler et al. (2003); Michael (2007); Smaill et al. (2008); Rowland et al. (2011); Hiatt et al. (2013); Hurwitz et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); Gray et al. (2019); Chen et al. (2023)
Others (n = 6)Additional stakeholders including educational program leaders, professional association members, and studentsValiga and Bruderle (1994); American Society of Plant (2011); Rowland et al. (2011); Danos et al. (2022); Qian et al. (2023); Horne et al. (2024)
No participant (n = 1)The study relies solely on document analysis without human participantsTweedie et al. (2020)
Criteria for core conceptsStandards/characteristics used to support what qualifies as a core concept within the domain
Importance (n = 12)The concept holds fundamental significance to the domainBoneau (1990); Zechmeister and Zechmeister (2000); Hott et al. (2002); Streveler et al. (2003); Smaill et al. (2008); Foster et al. (2012); Herman and Loui (2012); Hiatt et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); Qian et al. (2023); Horne et al. (2024)
Teaching Inclusion (n = 3)The concept is frequently included in educational programsValiga and Bruderle (1994); Giddens and Brady (2007); Hiatt et al. (2013)
Difficult and challenging (n = 3)The concept requires special attention due to its complexityStreveler et al. (2003); Parekh et al. (2018); White et al. (2021)
Enduring and timeless (n = 3)The concept maintains relevance over timeWhite et al. (2021); White et al. (2022); Chen et al. (2023)
Criteria application in data collectionApproach by which use of criteria was implemented in the study
Explicit application (n = 16)Clear, documented use of criteria in research instruments (surveys) as well as analysis processBoneau (1990); Valiga and Bruderle (1994); Hott et al. (2002); Peters and Livia (2006); Giddens and Brady (2007); Smaill et al. (2008); Michael and McFarland (2011); Herman and Loui (2012); Hiatt et al. (2013); White et al. (2021); White et al. (2022); Chen et al. (2023); Qian et al. (2023)
Non-explicit application (n = 4)Implicit use of criteria in conceptualizationZechmeister and Zechmeister (2000); Michael (2007); Hurwitz et al. (2013); Horne et al. (2024)
Research frameworks
Use of Conceptual Framework (n = 6)
Use of apriori structure organizing research/ existing core concepts frameworks from related domainsGiddens and Brady (2007); American Society of Plant (2011); Merkel (2012); Tansey et al. (2013); Gray et al. (2019); Tangalakis et al. (2023)
Pilot study utilization
Publications reported conducting a pilot (n = 10)
Preliminary testing of research methods to validate approaches and instrumentsBoneau (1990); Valiga and Bruderle (1994); Hott et al. (2002); Hurwitz et al. (2013); Tweedie et al. (2020); White et al. (2021); White et al. (2022); Chen et al. (2023); Horne et al. (2024)

Methodological characteristics: focus on participant types, criteria for core concepts, utilization of research frameworks, and pilot studies for core concept identification.

Table 5 maps methodological procedures employed in core concept identification studies across two main phases: candidate identification and candidate refinement. This phase-wise process begins with candidate identification to generate preliminary terms/concepts from participants and documents, followed by candidate refinement to develop and validate the initial list. Various methods are applied individually and/or in combination throughout these phases. Findings revealed that various methods were used in each phase, with expert group techniques and document analysis dominating the identification phase. In contrast, surveys and expert group techniques were prominent in the refinement phase. By examining the combination of methods used across both phases, we identified the underlying research designs, which were predominantly mixed methods approaches, even when not explicitly stated in the original publication. This methodological breakdown offers a view of how researchers identified and validated core concepts for education in their domains.

Table 5

Methodological characteristics*DescriptionCitation
1. Procedures for core concept identification
A. Candidate Identification Phase
Expert group techniques (n = 13)A collaborative and iterative collection of methods that leverages the collective knowledge of individuals identified as knowledgeable and/or experienced in a subject matter to identify, evaluate, and refine core concepts in that domainSee below for specific corresponding methods
Discussions/workshops (n = 6)Structured group interactions with clear objectivesHott et al. (2002); Giddens and Brady (2007); Michael (2007); American Society of Plant (2011); Merkel (2012); Tansey et al. (2013); Wright et al. (2013)
The first round of Delphi (n = 5)First round of Delphi process (subsequent rounds reported in the candidate refinement phase)Streveler et al. (2003); Hurwitz et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); Tangalakis et al. (2023)
Brainstorming (n = 2)Open-ended ideas generation activitiesHiatt et al. (2013)Danos et al. (2022)
Document analysis (n = 8)Analysis of domain textbooks, curriculum materials, learning syllabi, learning outcomes and outlines, competency standards, and guidelinesSee below for specific corresponding methods
Content analysis (n = 7)Non-automated analysis of the domain-relevant textual resourcesBoneau (1990); Zechmeister and Zechmeister (2000); Peters and Livia (2006); Smaill et al. (2008); Gray et al. (2019); Tweedie et al. (2020); Qian et al. (2023)
Text mining (n = 1)Automated analysis of textbooks to extract keywordsWhite et al. (2022)
Other methodsMethods used that are less the 5 instances across all studiesSee below for specific corresponding methods
Open-ended surveys (n = 5)Using a research instrument that asks participants questions without providing predetermined response options.Michael and McFarland (2011); Rowland et al. (2011); White et al. (2021); White et al. (2022); Chen et al. (2023)
literature reviews (n = 4)A comprehensive analysis of existing academic research, publications and scholarly works to support the core concept identification processValiga and Bruderle (1994); Hiatt et al. (2013); White et al. (2021); Horne et al. (2024)
Interviews (n = 1)A structured, semi-structured, or unstructured conversation with participants to gather in-depth information regarding core conceptsQian et al. (2023)
Algorithm application (n = 1)Using an automated systematic set of rules or procedures to extract conceptsFoster et al. (2012)
B. Candidate Refinement Phase
Surveys (n = 14)Using research instruments that ask participants to respond through various formatsBoneau (1990); Valiga and Bruderle (1994); Zechmeister and Zechmeister (2000); Hott et al. (2002); Peters and Livia (2006); American Society of Plant (2011); Michael and McFarland (2011); Merkel (2012); Hiatt et al. (2013); Wright et al. (2013); White et al. (2021); Chen et al. (2023)
Expert group techniques (n = 12)A collaborative and iterative collection of methods that leverages the collective knowledge of individuals identified as knowledgeable and/or experienced in a subject matter to identify, evaluate, and refine core concepts in that domainSee below for specific corresponding methods
Discussions/workshops/consultations (n = 5)Structured interactions with participants in groups or individuallyMerkel (2012); Gray et al. (2019); White et al. (2021); Danos et al. (2022); Chen et al. (2023)
Subsequent rounds of Delphi (n = 7)Subsequent Delphi rounds used for candidate refinementStreveler et al. (2003); Herman and Loui (2012); Hurwitz et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); White et al. (2022); Tangalakis et al. (2023)
Other methodsMethods used that are less than 5 instances across all studiesSee below for specific corresponding methods
Document analysis (n = 2)Analysis of domain textbooks, curriculum materials, learning syllabi, learning outcomes and outlines, competency standards, and guidelinesHott et al. (2002); Horne et al. (2024)
Machine learning techniques (n = 1)Specific computational method that enables systems to learn patterns from data and make predictions or decisions for core concept identificationFoster et al. (2012)
2. Research designA combination of methods used in candidate identification and concept refinement
Mixed methods (n = 20)Combined qualitative and quantitative approachesBoneau (1990); Zechmeister and Zechmeister (2000); Streveler et al. (2003); Giddens and Brady (2007); Smaill et al. (2008); American Society of Plant, 2011; Michael and McFarland (2011); Rowland et al. (2011); Foster et al. (2012); Herman and Loui (2012); Merkel (2012); Hiatt et al. (2013); Hurwitz et al. (2013); Grunspan et al. (2018); Parekh et al. (2018); White et al. (2021); White et al. (2022); Chen et al. (2023); Qian et al. (2023); Tangalakis et al. (2023)
Multimethod (n = 3)Multiple methods of the same type, either qualitative or quantitative, but not bothHott et al. (2002); Gray et al. (2019); Danos et al. (2022)
Quantitative (n = 2)Predominantly quantitative approachesBoneau (1990); Valiga and Bruderle (1994)
Qualitative (n = 5)Predominantly qualitative approachesMichael (2007); Tansey et al. (2013); Wright et al. (2013); Tweedie et al. (2020); Horne et al. (2024)

Methodological characteristics: focus on procedures, methods, and research design for core concept identification.

*

Main categories are shown in bold. Procedures for Core Concept Identification encompass both the Candidate Identification and Concept Refinement phases in italics. n = number of publications using each method.

3.5 Results for review objective three: key outputs with a focus on the number of core concepts, concept format, and intention for practical use

Table 6 presents two key outputs of core concepts across domains: the number of core concepts and their presentation format. Core concepts ranged from 3 to 352 across studies, with most disciplines having fewer than 10 concepts (n = 12). The concepts were primarily presented as terms (n = 21), with fewer studies using statements (n = 7) or hybrid formats (n = 2). These patterns suggest varying approaches to organizing and expressing disciplinary knowledge across fields.

Table 6

Key findings characteristicsDescriptionDomain and citation
Number of core conceptsSixteen publications identified 3 to 10 core conceptsBiochemistry (Rowland et al., 2011), Biochemistry and molecular biology (Tansey et al., 2013; Wright et al., 2013), Biological sciences (Michael, 2007), Comparative vertebrate anatomy and morphology (Danos et al., 2022), Digital logic (Herman and Loui, 2012) Electromagnetics (Smaill et al., 2008), Evolutionary developmental biology (Hiatt et al., 2013), Genetics (Hott et al., 2002), Interdisciplinary environmental and sustainability (Horne et al., 2024), Microbiology (Merkel, 2012), Neuroscience (Chen et al., 2023) Physiology (Michael and McFarland, 2011; Tangalakis et al., 2023), Toxicology (Gray et al., 2019) Traffic signals engineering (Hurwitz et al., 2013)
Five publications identified 10 to 50 concepts core conceptsEvolutionary medicine (Grunspan et al., 2018), Pharmacology(White et al., 2021; White et al., 2022), Plant Biology (American Society of Plant, 2011), Thermal and transport science (Streveler et al., 2003)
Nine studies identified more than 50 core conceptsBehavioral and social sciences in medicine (Peters and Livia, 2006), Chemistry (Qian et al., 2023), Cybersecurity (Parekh et al., 2018), Dietetics (Tweedie et al., 2020), Digital libraries (Foster et al., 2012), Nursing (Valiga and Bruderle, 1994; Giddens and Brady, 2007), Psychology (Boneau, 1990; Zechmeister and Zechmeister, 2000)
Concept format: The structural presentation and organization of core concepts, reflecting different approaches to expressing disciplinary knowledge.
Concept formatTerms—a word or group of words (n = 21)
E.g., “cognition” in psychology and “homeostasis” in physiology
Behavioral and social sciences in Medicine (Peters and Livia, 2006), Biochemistry (Rowland et al., 2011) Biochemistry and Molecular Biology(Tansey et al., 2013), Chemistry (Qian et al., 2023), Comparative vertebrate anatomy and morphology (Danos et al., 2022), Cybersecurity (Parekh et al., 2018), Dietetics (Tweedie et al., 2020), Digital logic (Herman and Loui, 2012), Electromagnetics (Smaill et al., 2008), Interdisciplinary environmental and sustainability (Horne et al., 2024), Nursing (Valiga and Bruderle, 1994; Giddens and Brady, 2007), Pharmacology (White et al., 2021; White et al., 2022) Physiology (Michael and McFarland, 2011; Tangalakis et al., 2023), Psychology (Boneau, 1990; Zechmeister and Zechmeister, 2000), Thermal and transport science (Streveler et al., 2003), Toxicology (Gray et al., 2019), Traffic signals engineering (Hurwitz et al., 2013)
Statement---a sentence or assertion (n = 7)
E.g. in evolutionary medicine, “Sexual selection shapes traits that result in different health risks between sexes”
Biochemistry and Molecular Biology (Wright et al., 2013), Biological Sciences (Michael, 2007), Digital Libraries (Foster et al., 2012), Evolutionary Developmental Biology (Hiatt et al., 2013), Evolutionary medicine (Grunspan et al., 2018), Genetics (Hott et al., 2002), Microbiology (Merkel, 2012)
Hybrid ---Use of both terms and/or statements (n = 2)Plant biology (American Society of Plant, 2011), Neuroscience (Chen et al., 2023)

Key outputs with a focus on the number of core concepts and their presentation formats across domains.

Table 7 shows four primary intended uses for core concepts across domains. Most studies emphasized these concepts as guiding rather than prescriptive resources, with many reporting multiple intended applications. This suggests that core concepts are expected to serve diverse practical purposes in academic fields, from curriculum planning to establishing common frameworks.

Table 7

Reported intention for the practical usesIllustrative quoteCitation
Curriculum development“Neuroscience core concepts are intended for use by neuroscience educators, including program directors, department chairs, and instructional faculty in neuroscience higher education. The core concepts can be used to inform curricular and course development, as well as curricular and programmatic assessment, given that they represent input from a diverse group of neuroscience educators.” (Chen et al., 2023)Valiga and Bruderle (1994); Giddens and Brady (2007); American Society of Plant (2011); Hurwitz et al. (2013); Grunspan et al. (2018); Gray et al. (2019); Tweedie et al. (2020); White et al. (2021); White et al. (2022); Chen et al. (2023); Tangalakis et al. (2023)
Teaching and learning“Based on results of surveys and interviews with students, we suggest that teaching core concepts (CCs) within a framework that integrates supporting concepts (SCs) from both evolutionary and developmental biology can improve evo-devo instruction.” (Hiatt et al., 2013)Zechmeister and Zechmeister (2000); Hott et al. (2002); Rowland et al. (2011); Herman and Loui (2012); Merkel (2012); Hiatt et al. (2013); Parekh et al. (2018); White et al. (2022)
Assessment and evaluation“Results from the Delphi processes lay a foundation for improving cybersecurity teaching and learning by helping educators design better assessment tools, learning materials, and curricula.” (Parekh et al., 2018)Streveler et al. (2003); Michael (2007); Smaill et al. (2008); Michael and McFarland (2011); Hiatt et al. (2013); Hurwitz et al. (2013); Tansey et al. (2013); Wright et al. (2013); Parekh et al. (2018); White et al. (2021); Danos et al. (2022); Chen et al. (2023); Qian et al. (2023)
Standardization and common framework“Defined partially by their explanatory breadth and importance to the field, core principles also provide a framework to organize research. The framework of core principles provided here can help clarify connections between ongoing research that may be based on larger ideas and not on topics or methodology.” (Grunspan et al., 2018)Boneau (1990); Peters and Livia (2006); Foster et al. (2012); Tansey et al. (2013); Grunspan et al. (2018); Danos et al. (2022); Qian et al. (2023); Tangalakis et al. (2023); Horne et al. (2024)

Key outputs with focus on intended use of identified core concepts.

4 Discussion

Adopting a scoping review methodology, this review examined 30 publications on core concept identification within STEM and health-related educational domains to highlight the rationale, the research approaches, and key outputs. Figure 2 shows an overview of the findings of this review in the context of the rationale, process, and outputs of core concept identification in STEM and Health-Related Education Domains.

Figure 2

4.1 The rationale for core concepts identification

Core concept identification within formal education in STEM and health-related fields is motivated by a complex interplay of factors, revealed through the analysis of 30 publications as seven distinct categories of rationales (see Table 3). These findings demonstrate the diverse motivations driving researchers’ pursuit of core concept identification in their respective domains.The identification of core concepts is driven mainly by the need to prioritize essential content within expanding knowledge bases of domains (White et al., 2021; White et al., 2022; Chen et al., 2023). This includes lacking of existing core concepts (American Society of Plant, 2011; Grunspan et al., 2018; Parekh et al., 2018; Danos et al., 2022), establishing core knowledge (Boneau, 1990), clarifying key concepts (Valiga and Bruderle, 1994), standardizing domain vocabulary (Zechmeister and Zechmeister, 2000), and aligning core concepts with learning objectives in the educational curricula (Tangalakis et al., 2023).

Complementary to this is the learning-centric rationale for identifying core concepts, where developing conceptual frameworks (Zechmeister and Zechmeister, 2000), strengthening conceptual understanding (Rowland et al., 2011; Qian et al., 2023), and addressing students’ misconceptions (Streveler et al., 2003; White et al., 2021) all come together to enhance learning. This rationale aligns with Ausubel’s theory of meaningful learning (Ausubel, 2012), where learning becomes meaningful when new information is intentionally integrated into existing cognitive structures rather than memorized in isolation as facts. Core concepts function as cognitive anchoring points that allow learners to incorporate new knowledge into their existing mental frameworks. When educators identify and emphasize core concepts, they are essentially providing students with the cognitive infrastructure necessary for this integration process, facilitating the development of enduring understanding. This learning-centric rationale for core concepts identification also intersects with pedagogical content knowledge (PCK) in that core concept identification precedes PCK application, where establishing the fundamental knowledge structures of the domain will subsequently support teaching and learning approaches (Loewenberg Ball et al., 2008). Ultimately, this connects to the conceptual assessment rationale, where educators require valid tools to measure deeper conceptual understanding rather than mere recall(Streveler et al., 2003; Michael, 2007; Smaill et al., 2008; Michael and McFarland, 2011; Hiatt et al., 2013; Hurwitz et al., 2013; Tansey et al., 2013; White et al., 2021; Horne et al., 2024). These assessment needs reflect the broader challenge of evaluating authentic conceptual understanding across various knowledge dimensions.

The educational reform rationale reflects a paradigm shift toward student-centered learning and conceptual understanding, moving away from traditional rote memorization approaches (Merkel, 2012; Gray et al., 2019; Danos et al., 2022; Chen et al., 2023). For instance, in physiology education, the initiative was driven by a broader educational transformation that aimed to move beyond simple memorization toward conceptual understanding, with the specific goal of helping students transfer their learning across different topics (Schaefer and Michael, 2024). This educational reform reason for core concepts identification approach aligns with the paradigm shift in education from teaching isolated facts toward shaping the conceptual mind. When educators identify and teach through concepts, they enable students to move beyond surface-level memorization to a deeper understanding of the transferable principles that organize a domain facilitating students’ ability to see patterns, connections, and relationships between seemingly disparate facts and examples—precisely the kind of cognitive integration that strengthens conceptual understanding and addresses misconceptions (Erickson et al., 2017). The ontological rationale for identifying core concepts is particularly evident in interdisciplinary fields like pharmacology (White et al., 2021), where knowledge’s inherent and underlying nature necessitates careful consideration of content organization and presentation. This rationale acknowledges the unique challenges posed by fields that integrate multiple disciplinary perspectives and knowledge frameworks.

From these categories of rationales and their emerging domains, we posit that a strong disciplinary focus, responding to the unique challenges and epistemological structures of each domain, is at the nucleus of these reasons for identifying core concepts. This aligns with existing literature, as the adoption of core concepts approaches in STEM teaching varies significantly across disciplines, with each field implementing this strategy to meet distinct disciplinary needs (Schaefer and Michael, 2024). Supporting this assertion for instance we see in pharmacology (White et al., 2021) emerged across five rationale categories, reflecting its interdisciplinary roots, nature, and complex knowledge integration challenges, while Neuroscience (Chen et al., 2023) were inherently both content prioritization and educational reforms, responding to its rapidly expanding knowledge base. Chemistry, on the other hand (Qian et al., 2023), focuses on learner-centric approaches to address the challenges of conceptual understanding, which can be peculiar to teaching abstract concepts. Perhaps, these disciplinary differences extend to epistemological structures where systems-focused disciplines like physiology (Michael, 2007) prioritize strategies for assessing the attainment of conceptual understanding. Hence, the rationale for core concept identification responds to discipline-specific needs, with each discipline’s approach appearing tailored to its unique knowledge structures, pace of knowledge evolution, professional requirements, and student learning challenges—reinforcing that core concept identification is fundamentally a discipline-contextualized practice.

4.2 Methods for core concepts identification

There is a clear preference for mixed methods approaches (see Table 5), reflecting a pragmatic worldview that prioritizes practical solutions over strict methodological adherence (Creswell, 2015). This choice aligns well with the rigorous process of core concept identification, which requires integrating and triangulating multiple perspectives and data, enhancing the reliability of the research-driven core concept identification outputs. The identification process typically followed a two-phase approach: an initial candidate concept identification phase followed by a subsequent concept refinement phase. This process aligns with a sequential exploratory design, where qualitative exploration precedes quantitative validation (Fetters et al., 2013), allowing researchers to generate potential core concepts and subject them to rigorous validation. Exploratory methods like document analysis and expert group techniques—discussions, workshops, and initial Delphi rounds—dominated the candidate identification phase (See Table 5). In contrast, surveys and expert group techniques—subsequent Delphi rounds and consultations — were prevalent in the refinement phase, suggesting systematic progression from broad exploration to focused validation of the concepts.

A crucial methodological finding is the predominance of a collection of similar research methods termed expert group techniques, described in previous research publications as techniques that involve group members engaged in a series of collaborative iterations (Ralph and Walker, 2014) and have been used to develop a set of guidelines in the context of health professionals (Skirton et al., 2014). Based on its use in the core concepts identification publications within this review, we operationally define expert group techniques as a collaborative and iterative collection of methods that leverages the collective knowledge of individuals identified as knowledgeable and/or experienced in a subject matter to identify, evaluate, and refine core concepts in that domain. This was employed in 29 of 30 studies, drawing on domain experts, including textbook authors, educators, professionals, and researchers (see Tables 4, 5). This finding shows that core concept identification has relied heavily on the collective judgment of individuals identified as experts to define core disciplinary knowledge, aligning with established practices in educational research (de Villiers et al., 2005; Laughlin et al., 2006; Hakkarainen et al., 2016).

We surmise that the expert group techniques have important elements for researchers to consider in core concept identification. Participant selection criteria may or may not be determined a priori (Streveler et al., 2003; Herman and Loui, 2012; Hurwitz et al., 2013; Grunspan et al., 2018; Parekh et al., 2018; White et al., 2022; Tangalakis et al., 2023), composing mainly of educators, professionals, researchers, and other stakeholders in education (See Table 4). The strategic selection of experts across disciplines reveals important core concept identification methodology insights. While studies have employed various expert profiles—from textbook authors in psychology (Boneau, 1990) to dual-role teacher-researchers in evolutionary biology(Hiatt et al., 2013), the common thread is a balance between theoretical knowledge and practical application expertise. This balanced approach to expert selection appears intentional rather than incidental, suggesting that researchers recognize that effective core concept identification requires both deep disciplinary expertise in the context of knowledge, understanding and experience. The significance of this pattern is particularly evident in recent studies (Chen et al., 2023; Qian et al., 2023), where diverse stakeholder perspectives were deliberately integrated into their core concepts identification work compared to earlier studies, which focused on one education stakeholder. This suggests a growing interest in inclusive expert selection strategies that incorporate theory and practice.

Establishing clear initial goals is essential, though iterative adjustments may occur. Methodological flexibility enables using varied formats and activities suited to specific disciplinary needs. The expert group techniques complement other methods, incorporating robustness into identifying the domain’s core concept.

The methodological approaches to core concept identification require careful consideration, particularly regarding research frameworks and pilot testing of data collection and analysis processes. The absence of theoretical frameworks across all included publications highlights that core concept identification is driven more by pragmatic focus than theoretical concerns. This pragmatic emphasis may limit the development of robust methodological approaches, potentially sacrificing methodological rigor (Morgan, 2007; Tracy, 2010). The limited use of pilot testing (see Table 4) raises concerns about rigor, as piloting is crucial for validating research instruments and procedures, addressing concerns of methodological reliability and verification (Morse et al., 2002; Van Teijlingen and Hundley, 2002). Additionally, while several criteria were used for core concept identification (See Table 4), their inconsistent application in data collection and analysis across publications suggests that more standardized concept evaluation approaches are needed.

4.3 Key outputs of core concepts identification

A core concepts approach to teaching STEM disciplines is increasingly evident with intention to solve different problems in different disciplines (Schaefer and Michael, 2024).The outputs of core concept identification vary in terms of the number of these core concepts, their presenting formats, and their intended use. This striking variation reveals important differences in what constitutes a ‘core’ concept across disciplines. The scope and complexity of different domains clearly influence the quantity of identified core concepts. Digital Logic, an introductory course (Herman and Loui, 2012), features just three core concepts, while Digital Libraries, a broad scientific field (Foster et al., 2012), encompasses over 352. This difference likely reflects both the inherent complexity of these domains and differing approaches to concept granularity across them, presenting that core concepts can be identified at varying levels of a domain such as micro level at a single/ course level through to macro level being the of the domain. Also, the Biological sciences often identify fewer core concepts, typically between 5 and 15 (Michael, 2007; American Society of Plant, 2011; Michael and McFarland, 2011; Merkel, 2012; Gray et al., 2019; Danos et al., 2022; Chen et al., 2023). In contrast, health-related fields such as Dietetics (Tweedie et al., 2020) and Nursing (Valiga and Bruderle, 1994; Giddens and Brady, 2007) tend to identify more concepts. Perhaps, these disciplinary differences stem from a combination of pedagogical requirements, domain complexity, and varying philosophical approaches to what constitutes the ‘core’ in each domain. The format of the core concept presentation varied widely. While most studies listed concepts as discrete terms, others used statements or hierarchical formats (see Table 6), reflecting diverse pedagogical needs and disciplinary preferences. Some studies used hierarchical structures (Hott et al., 2002; Merkel, 2012; Hiatt et al., 2013; Wright et al., 2013), suggesting the interconnected nature of core concepts within the domain’s conceptual structure. Core concepts were intended to be used by educators as a guide in curriculum development, teaching and learning improvement, assessment, and standardization (See Table 7). This suggests that core concept identification is largely driven by pedagogical and educational goals rather than theoretical aims. Emphasis on curriculum and assessment development indicates a shift towards structured, evidence-based educational approaches across disciplines.

4.4 Implications

Based on the findings from this scoping review, several implications emerge for enhancing core concept identification in education. Developing standardized protocols and quality criteria for expert group techniques would strengthen methodological rigor and consistency across domains. Establishing clear guidelines for methodological reporting, particularly regarding pilot testing and validation procedures, would improve transparency and reproducibility. The observed variations in core concept identification suggest a need for standardized criteria to guide this process. Moving forward, future research should focus on developing comprehensive methodological guidelines for expert group techniques, providing research frameworks to guide identification efforts, and establishing clear criteria for determining how “core” is a concept for a domain. These developments would effectively advance the identification and validation of core concepts across different domains. Additionally, investigating the relationship between different presentation formats of core concepts and their educational effectiveness would provide valuable insights for pedagogical practice.

4.5 Limitations

The operational definition of core concepts as “fundamental, enduring, useful, and discipline-specific ideas that form the foundation of a field of knowledge” may have limited the scope of our search. While this definition provided our common understanding and supported study selection, it may have excluded studies that explored similar concepts under different terminology. Including only articles published in English may have limited the diversity of studies analysed in this review. However, this criterion was only applied in the final screening phase and resulted in exclusion of only 2 studies. Also, the involvement of multiple reviewers in the full-text review phase may have introduced the potential for varying interpretations of the inclusion criteria; however, reviewer training and using a third independent reviewer to mitigate this concern. The research team published and followed an a priori protocol but made methodological adaptations by modifying the extraction template in response to the unanticipated volume and complexity of data. Although this adaptation enabled more precise data extraction for each research objective, deviating from the original protocol’s single extraction template represents a limitation in terms of protocol adherence.

5 Conclusion

This scoping review synthesizes research on core concepts in STEM and health-related domains, providing valuable insights into the rationales for their identification, methodological approaches, and key outputs. The findings highlight the predominance of expert-driven approaches and the need for more standardized methodological frameworks. Recognizing that core concept development is intellectually demanding and time-consuming, this review provides a valuable resource for educators and researchers to adopt this evidence-based approach.

Statements

Author contributions

AE: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. MW: Conceptualization, Investigation, Methodology, Supervision, Writing – review & editing. KJ: Conceptualization, Investigation, Methodology, Supervision, Writing – review & editing. AN: Investigation, Writing – review & editing. TA: Conceptualization, Investigation, Writing – review & editing. PW: Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was made possible by support from the Australian Government Research Training Program (RTP) Scholarship.

Acknowledgments

We would like to thank Gabby Lamb, Liaison Librarian at Monash University, for her expert assistance in developing the search strategy, and Yassmin Samak for her helpful insights and shared experience in conducting a literature review in a related context.

Conflict of interest

The authors declare that the research was conducted without any commercial or financial relationships that could potentially create a conflict of interest.

Generative AI statement

The author(s) declare that no Gen AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2025.1547994/full#supplementary-material

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Summary

Keywords

core concept, stem education, health science education, scoping review, concept identification, mixed methods, content prioritization, big ideas

Citation

Etukakpan AU, Waldhuber MG, Janke KK, Netere AK, Angelo T and White PJ (2025) Core concept identification in STEM and related domain education: a scoping review of rationales, methods, and outputs. Front. Educ. 10:1547994. doi: 10.3389/feduc.2025.1547994

Received

19 December 2024

Accepted

31 March 2025

Published

11 April 2025

Volume

10 - 2025

Edited by

Xiang Hu, Renmin University of China, China

Reviewed by

Vicki S. Napper, Weber State University, United States

Yan Wang, Beijing Normal University, China

Updates

Copyright

*Correspondence: Paul J. White,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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