A conceptual framework for developing a nature loving education teaching module to foster spirituality in young children

Early childhood education is increasingly expected to support children’s holistic development, including emotional, moral and spiritual dimensions. In Malaysia, national preschool curricula emphasise values and character education; however, spirituality in classroom practice often remains implicit, ritualistic and weakly connected to children lived experiences, particularly in relation to nature-based learning. To address this gap, this study proposes the development of a Nature Loving Education Teaching (NLET) module to support preschool children’s spiritual development through meaningful engagement with the natural environment. Guided by constructivist learning theory, the Biophilia Hypothesis, Fowler’s Faith Development Theory and Miller’s Spiritual Child Theory, spirituality is conceptualised as children’s experiences of awe, connectedness and meaning-making rather than as religious instruction. Nature Loving Education is positioned as a values-oriented pedagogical framework grounded in peer-reviewed research on nature connection and early childhood spirituality, treated as a provisional framework requiring systematic investigation. The study adopts a Design and Development Research (DDR) approach comprising needs analysis (targeting a purposive sample of n = 100 preschool teachers and 7 parents), design and development (utilising the Fuzzy Delphi Method with a panel of 11 experts to establish mathematical consensus) and implementation and evaluation phases. Children’s spirituality is operationalised through the three interrelated dimensions of awe/wonder, connectedness and meaning-making, which are translated into observable and developmentally appropriate indicators during nature-based learning experiences. This paper contributes a theoretically informed and practically relevant conceptual framework that supports the intentional integration of universal spirituality into preschool education, providing a structured pathway for future empirical validation and module implementation.