The STEM+ Research Coaching Framework: Integrating Authentic Inquiry, Human–AI Co-Intelligence, and STEM Identity Development

The rapid expansion of generative artificial intelligence, authentic inquiry, and interdisciplinary STEM+ education has renewed interest in understanding how STEM identity develops in contemporary educational contexts. Although previous research has substantially advanced knowledge of STEM identity, authentic inquiry, mentoring, and artificial intelligence in education, these perspectives have largely evolved as parallel research traditions, providing limited guidance for intentionally designing Relational Research Ecosystems in which they operate as an integrated pedagogical system. This integrative literature review analyzes and integrates scholarship on STEM identity, authentic inquiry, mentoring, relational pedagogy, Human–AI Co-Intelligence, and twenty-first-century competencies to develop the STEM+ Research Coaching Framework, a relational pedagogical framework for intentionally designing Relational Research Ecosystems. The framework conceptualizes STEM+ Research Coaching as an integrated relational process in which Methodological Coherence, Intentional Mentoring, Strategic Questioning, Human–AI Co-Intelligence, and Reflective Meaning-Making function as five complementary mechanisms that collectively cultivate authentic inquiry, collaborative knowledge co-construction, scientific agency, and STEM identity development. Rather than conceptualizing artificial intelligence as a tool for task automation, the framework positions Human–AI Co-Intelligence as a relational pedagogical process that supports collaborative knowledge co-construction while preserving human intentionality, disciplinary judgment, ethical responsibility, and critical reflection. By integrating complementary theoretical traditions, the framework shifts the focus from explaining why STEM identity develops toward understanding how educators intentionally cultivate it through the orchestration of Relational Research Ecosystems.

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Publication Details

Journal
Ciencia Latina Revista Científica Multidisciplinar
Published
2026-11-03
DOI
https://doi.org/10.37811/cl_rcm.v10i5.26438
Primary Topic
Science Education and Pedagogy
Type
article
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article

The STEM+ Research Coaching Framework: Integrating Authentic Inquiry, Human–AI Co-Intelligence, and STEM Identity Development

Germán Collazos Guzmán, Mateo Collazos Roa
Ciencia Latina Revista Científica Multidisciplinar
Science Education and Pedagogy
article

The STEM+ Research Coaching Framework: Integrating Authentic Inquiry, Human–AI Co-Intelligence, and STEM Identity Development

Germán Collazos Guzmán, Mateo Collazos Roa
article en

Abstract

The rapid expansion of generative artificial intelligence, authentic inquiry, and interdisciplinary STEM+ education has renewed interest in understanding how STEM identity develops in contemporary educational contexts. Although previous research has substantially advanced knowledge of STEM identity, authentic inquiry, mentoring, and artificial intelligence in education, these perspectives have largely evolved as parallel research traditions, providing limited guidance for intentionally designing Relational Research Ecosystems in which they operate as an integrated pedagogical system. This integrative literature review analyzes and integrates scholarship on STEM identity, authentic inquiry, mentoring, relational pedagogy, Human–AI Co-Intelligence, and twenty-first-century competencies to develop the STEM+ Research Coaching Framework, a relational pedagogical framework for intentionally designing Relational Research Ecosystems. The framework conceptualizes STEM+ Research Coaching as an integrated relational process in which Methodological Coherence, Intentional Mentoring, Strategic Questioning, Human–AI Co-Intelligence, and Reflective Meaning-Making function as five complementary mechanisms that collectively cultivate authentic inquiry, collaborative knowledge co-construction, scientific agency, and STEM identity development. Rather than conceptualizing artificial intelligence as a tool for task automation, the framework positions Human–AI Co-Intelligence as a relational pedagogical process that supports collaborative knowledge co-construction while preserving human intentionality, disciplinary judgment, ethical responsibility, and critical reflection. By integrating complementary theoretical traditions, the framework shifts the focus from explaining why STEM identity develops toward understanding how educators intentionally cultivate it through the orchestration of Relational Research Ecosystems.

Ciencia Latina Revista Científica MultidisciplinarVol. 10(5)
Openalex Percentile: Top 8%
Science Education and Pedagogy
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