Strategic Leverage Points in Blended Learning: A Systems Science Approach Using Grey-DEMATEL-ISM-MICMAC Framework in Higher Education.
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| Title: | Strategic Leverage Points in Blended Learning: A Systems Science Approach Using Grey-DEMATEL-ISM-MICMAC Framework in Higher Education. |
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| Authors: | Liu, Xiaohan1 xiaohanliu@cmu.ac.th, Yodmongkol, Pitipong1 pitipong.y@cmu.ac.th |
| Source: | Electronic Journal of e-Learning. 2026, Vol. 24 Issue 2, p112-131. 20p. |
| Subject Terms: | *Blended learning, *Digital learning, *Higher education, Critical success factor, Causal models, Multiple criteria decision making, Systems theory |
| Abstract: | E-learning has emerged as a cornerstone of contemporary higher education, offering flexible and technology-mediated environments that accommodate modern learning needs. Among its various modalities, blended learning (BL), which strategically integrates face-to-face and online instruction, has become a pivotal approach in higher education for enhancing learning outcomes and fostering talent cultivation. However, its successful implementation depends on the coordinated interaction of individual, technological, environmental, and course dimensions, constituting a complex network of interdependent factors that often remain fragmented in practice. Existing studies typically examine these factors in isolation and commonly rely on linear analytical approaches, providing limited insights into the systematic, comprehensive, and hierarchical understanding of the interrelationships among them. Understanding these structural interrelationships is therefore essential for identifying strategic leverage points that can optimise system performance and ensure the sustainable success of BL initiatives. To address this gap, this study proposes a systems science-based analytical framework that integrates the Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL), Interpretive Structural Modelling (ISM), and Matrix Impact Cross Multiplication Applied to Classification (MICMAC). This integrated approach enables comprehensive and data-driven modelling of the causal parameters, hierarchical structure, and driving-dependence relationships among critical success factors of BL. First, ten critical success factors were identified through a systematic literature review and were then pairwise evaluated by twelve experts from a higher education institution in Thailand. Grey-DEMATEL was subsequently employed to quantify the causal properties and relative significance of these factors, while ISM was applied to construct a multi-layer hierarchical structure. MICMAC analysis further categorised the factors according to their driving and dependence powers. The results reveal a three-layer hierarchical structure of BL critical success factors, where policy support (R - C = 2.78), system quality (R - C = 1.73), and technical support (R - C = 1.62) serve as key causal drivers, forming the institutional and technological foundation of the BL system. Course design and technology experience act as mediating linkages connecting institutional mechanisms with learning outcomes, while attitude, perceived usefulness, and interaction represent outcome-level indicators of system performance. Among these factors, course design exhibits the highest level of centrality value (R + C = 18.6) with the causal structure. The findings extend the understanding of the causal hierarchy and strategic leverage points for achieving BL success, illustrate how institutional and technological investment are realised through course design to improve individual experience. The study offers actionable insights for policymakers and instructional designers to inform data-driven decision-making and strategic planning in higher education, as well as how this is implemented at the level of the individual academic. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
| Abstract: | E-learning has emerged as a cornerstone of contemporary higher education, offering flexible and technology-mediated environments that accommodate modern learning needs. Among its various modalities, blended learning (BL), which strategically integrates face-to-face and online instruction, has become a pivotal approach in higher education for enhancing learning outcomes and fostering talent cultivation. However, its successful implementation depends on the coordinated interaction of individual, technological, environmental, and course dimensions, constituting a complex network of interdependent factors that often remain fragmented in practice. Existing studies typically examine these factors in isolation and commonly rely on linear analytical approaches, providing limited insights into the systematic, comprehensive, and hierarchical understanding of the interrelationships among them. Understanding these structural interrelationships is therefore essential for identifying strategic leverage points that can optimise system performance and ensure the sustainable success of BL initiatives. To address this gap, this study proposes a systems science-based analytical framework that integrates the Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL), Interpretive Structural Modelling (ISM), and Matrix Impact Cross Multiplication Applied to Classification (MICMAC). This integrated approach enables comprehensive and data-driven modelling of the causal parameters, hierarchical structure, and driving-dependence relationships among critical success factors of BL. First, ten critical success factors were identified through a systematic literature review and were then pairwise evaluated by twelve experts from a higher education institution in Thailand. Grey-DEMATEL was subsequently employed to quantify the causal properties and relative significance of these factors, while ISM was applied to construct a multi-layer hierarchical structure. MICMAC analysis further categorised the factors according to their driving and dependence powers. The results reveal a three-layer hierarchical structure of BL critical success factors, where policy support (R - C = 2.78), system quality (R - C = 1.73), and technical support (R - C = 1.62) serve as key causal drivers, forming the institutional and technological foundation of the BL system. Course design and technology experience act as mediating linkages connecting institutional mechanisms with learning outcomes, while attitude, perceived usefulness, and interaction represent outcome-level indicators of system performance. Among these factors, course design exhibits the highest level of centrality value (R + C = 18.6) with the causal structure. The findings extend the understanding of the causal hierarchy and strategic leverage points for achieving BL success, illustrate how institutional and technological investment are realised through course design to improve individual experience. The study offers actionable insights for policymakers and instructional designers to inform data-driven decision-making and strategic planning in higher education, as well as how this is implemented at the level of the individual academic. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 14794403 |
| DOI: | 10.34190/ejel.24.2.4510 |
