Foundational thinking for later use of technology, particularly coding, is necessary for an inclusive and sustainable future. Inclusive practices beginning in early childhood recognize children’s innate development of computational thinking—sequencing, repetition and looping, debugging, decomposing and composing, representation, and causality. This qualitative research describes processes of developing and evaluating hypothesized developmental progressions. Inclusive engagement of children with and without disabilities is described in examples for each level of each developmental progression. Implications for teaching and learning with inclusive practices are described for children with and without disabilities.

Early science, technology, engineering, and math (STEM) learning experiences often exclude children with disabilities and intersecting identities. To promote learning in STEM for all children, the Curriculum Research Framework (CRF) was applied to build learning trajectories of STEM for children from birth to age 5. The CRF was extended and enhanced to generate explicitly inclusive learning trajectories for children with and without disabilities. The process of generating a priori foundations, building learning trajectories, and testing the results in inclusive settings led to new resources for early childhood education (ECE) and early childhood special education (ECSE) practitioners and generated implications for creating and evaluating learning trajectories in ways that affirm that all children belong in STEM. Challenges faced and lessons learned in this process are presented to guide future research and development using the revised and enhanced CRF.

Early Learning Guidelines (ELGs) support early childhood educators, administrators, and professionals in developing and implementing early learning experiences to support young children’s knowledge and skill development. Previous reviews of ELGs examined content addressed across states. However, no reviews have focused on science, technology, or engineering, which are becoming increasingly prevalent as target areas for all learners in the United States. The current review examined the extent (or count) to which science, technology, and engineering content are identified and included within ELGs and the content and processes included in the indicators. The results indicated most ELGs included specified science domains, with far fewer specified domains for technology or engineering. However, all ELGs addressed content at the indicator level for science, technology, and engineering. Individual indicators focused on earth and life science, physics, building and creating, and sequencing. Explicitly identifying content as science, engineering, and technology and expanding on the content to include additional topics (such as planning, designing, simple machines, and foundational computational thinking) could empower early educators to address these topics. To ensure indicators clearly articulate inclusive learning for science, technology, and engineering, additional evaluation of the content of indicators is needed.