Sustainable Learning Habituation: A Systems-Based Framework for Understanding Adaptation in E-Learning Environments for Sustainable Development

Education for Sustainable Development (ESD) increasingly relies on e-learning environments to deliver scalable, flexible, and accessible educational experiences. While existing research has extensively examined the role of digital technologies in facilitating sustainability-oriented learning, significantly less attention has been given to how learners themselves adapt to the structures and dynamics of these environments. This study adopts a theory-building approach, grounded in integrative conceptual synthesis, to develop a coherent explanatory framework that combines insights from cognitive load theory, self-regulated learning, neurocognitive adaptation, and systems theory. The paper proposes the Sustainable Learning Loop, a recursive mechanism describing how repeated interaction with e-learning systems leads to pattern recognition, expectation stabilization, reduced cognitive effort, decreased active engagement, and the emergence of stable behavioral learning patterns. In addition, a novel typology of Sustainable Learning Habituation (SLH) is developed, distinguishing between cognitive, engagement, behavioral, and sustainability habituation. The framework highlights a dual dynamic in digital learning environments. On the one hand, habituation enhances efficiency, usability, and scalability, supporting the broader goals of sustainable education. On the other hand, it introduces critical risks, including superficial sustainability learning, reduced critical thinking, platform dependency, and the emergence of an illusion of learning, where perceived competence exceeds actual understanding. The study contributes to the literature by reframing e-learning as a co-adaptive system that actively shapes cognitive and behavioral processes, rather than merely delivering content. From a practical perspective, the findings underscore the need to design digital learning environments that balance efficiency with reflexivity, ensuring that ESD remains transformative rather than procedural. The framework also offers actionable design implications, suggesting that e-learning environments for ESD should incorporate reflective prompts, task variability, learning analytics indicators, and metacognitive feedback mechanisms to prevent excessive routinization and support deeper sustainability-oriented engagement. Future research should focus on the empirical operationalization of SLH and the development of adaptive systems that support critical engagement and sustainable learning outcomes.