Cybernetic insights on active learning in higher education

David Ernesto Salinas-Navarro et al.

Kybernetes2026https://doi.org/10.1108/k-09-2025-2324article
AJG 1
Weight
0.50

What the paper says

Purpose This study examines the active learning pedagogical approach, incorporating core concepts of cybernetic theory, and investigates how cybernetics can inform pedagogical strategies in higher education. Design/methodology/approach An adapted conceptual systematic review was conducted using top-cited articles and systematic literature reviews on the definition of active learning. A nine-dimensional coding frame was developed from first- and second-order cybernetics, including agentive, adaptive, homeostatic, and ethical elements, to systematically interpret the literature. Findings Active learning implicitly embodies cybernetic principles such as feedback loops, self-organisation, and recursive interactions. However, crucial aspects such as homeostasis (balancing cognitive load) and ethics (equity and inclusion) remain underexplored. The coding frame demonstrates the explanatory value of cybernetics while identifying systemic gaps in current pedagogy. Research limitations/implications The study is conceptual and based on secondary sources in English-language higher education literature. Future empirical research should validate the coding frame across diverse educational levels and cultural contexts. Practical implications The coding frame provides educators with a systemic tool to design adaptive, balanced, and inclusive active learning environments by integrating feedback, regulation, and ethical considerations. Social implications By highlighting equity and well-being as neglected dimensions, the study supports the development of more inclusive and socially responsive pedagogies. Originality/value This is the first study to systematically apply cybernetic theory to study active learning, offering a novel systems-based perspective that bridges educational theory and practice.

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https://doi.org/https://doi.org/10.1108/k-09-2025-2324

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@article{david2026,
  title        = {{Cybernetic insights on active learning in higher education}},
  author       = {David Ernesto Salinas-Navarro et al.},
  journal      = {Kybernetes},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/k-09-2025-2324},
}

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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

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