Fostering K-12 educational leadership for sustainable space exploration: an AI-enhanced collaborative framework

Xiuli Chen et al.

Quality Assurance in Education2026https://doi.org/10.1108/qae-02-2025-0040article
AJG 1
Weight
0.50

What the paper says

Purpose This study aims to examine how the combined use of technologies, such as Artificial Intelligence (AI), equity-oriented access strategies and sustainability-infused, interdisciplinary curricula, fosters the leadership competencies that K-12 systems need to support a future, ethically grounded space sector. Design/methodology/approach A PRISMA-guided systematic review of Google Scholar (2021 – May 2025) screened 3,570 records retrieved with the string “K-12 outer space education” AND STEM AND “transformative OR distributed OR instructional” AND “sustainability OR SDG” AND “equity OR inclusion” AND “Artificial Intelligence (AI)”. After dual-reviewer filtering and quality appraisal, 67 high-relevance studies were synthesized thematically and mapped onto a hybrid leadership framework. Findings When transformational vision, distributed decision-making and instructional data routines are present alongside VR/AR or AI tools it raises leadership self-efficacy, widens underrepresented participation and embeds sustainability literacy. AI personalization and analytics act as catalysts, but most interventions are short-term and geographically concentrated in North America and Europe. Originality/value Linking EdTech, equity scaffolds and SDG-aligned interdisciplinarity with a tri-paradigm (transformational–distributed–instructional) leadership lens, it is significant to translate those links into a quality-assurance framework that educational agencies can operationalize for the emerging space-education economy.

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https://doi.org/https://doi.org/10.1108/qae-02-2025-0040

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@article{xiuli2026,
  title        = {{Fostering K-12 educational leadership for sustainable space exploration: an AI-enhanced collaborative framework}},
  author       = {Xiuli Chen et al.},
  journal      = {Quality Assurance in Education},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/qae-02-2025-0040},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.