Research

This report identifies foundational AI learning priorities for K–12 students, organized by grade band across five major categories. It also offers recommendations related to AI curriculum, instruction, future research, and updates to the AI4K12 Guidelines.

This community-generated report reflects collaboration across K–12 education, postsecondary institutions, and industry to articulate foundational CS content that all high school graduates should learn and to outline possible pathways for continued study beyond that foundation.

This report analyzes how widely used K–12 CS curricula align with the 2017 CSTA K–12 Standards. It identifies patterns in curriculum coverage, areas of strong alignment, and standards or concepts that may receive less attention in commonly used instructional materials.

This report examines the current state of the CS teaching profession, with attention to teacher preparedness, professional learning, support systems, and implementation conditions. The findings can help leaders understand what teachers need to bring a broader, more human-centered vision of CS education to life.

This report synthesizes expert recommendations for strengthening computing impacts and ethics throughout an early draft of the CSTA standards. It includes guidance on topics such as ethical frameworks, harms and power, and critical design practices.

This analysis compares the 2017 CSTA K–12 Standards and Reimagining CS Pathways report with other CS, STEM, arts, and humanities standards and frameworks. It identifies implications for standards structure, content organization, and areas where revised CS standards could be strengthened.

This report examines the similarities and differences between state-adopted K–12 CS standards and the 2017 CSTA K–12 Standards. This analysis includes basic information about the standards, such as counts by state and level, their cognitive complexity, and more detailed information about their relationship to the CSTA standards.

This report examines the similarities and differences between K–12 CS standards across seven international locations. This analysis includes background information on each of the locations included in the study, trends in content, and comparisons by topic area.

This report synthesizes research on algorithms and programming learning progressions, including sequence, variables, control, modularity, and program development. It highlights where the 2017 standards remain well aligned with research and where updates may be needed, such as program comprehension and the growing role of AI.

This report synthesizes research on student understanding of computing systems, networks, the internet, hardware, software, and cybersecurity. It highlights common student conceptions and misconceptions that can inform more developmentally appropriate standards and instruction.

This report summarizes research related to data collection, preparation, investigations, and impacts. It can help standards writers and curriculum developers understand how students develop increasingly sophisticated ways of collecting, preparing, analyzing, visualizing, and communicating with data.

This review focuses on the history of computing as an emerging priority within the Standards. It draws on social studies and history education approaches to recommend how students can explore computing’s relationship to society, beginning with local and familiar contexts and expanding toward broader historical and global perspectives.

This resource provides concepts, practices, ethical standpoints, and example language related to computing impacts and ethics, based on a literature review. It is intended to help standards writers more intentionally foreground the social, ethical, and systemic dimensions of computing.

This brief translates findings from standards and framework comparisons into concrete recommendations for the structure of revised CS standards. It addresses grade-band organization, standard length, integration of concepts and practices, and the role of supplementary materials.

This brief provides recommendations for Computing Systems and Security standards based on the literature review and related cybersecurity learning standards. It addresses grade-band expectations for hardware and software, networks, internet concepts, data flow, security practices, and cybersecurity.

This brief provides grade-band recommendations for Data and Analysis standards based on related learning progressions in statistics, mathematics, science, and data science education. It emphasizes a developmental progression from familiar, small datasets to larger, more complex investigations using computational tools.

This brief connects AI-related learning outcomes from Reimagining CS Pathways with the AI4K12 Framework. It provides recommendations for incorporating AI concepts across grade bands, including representation, machine learning, societal impacts, ethical design, and the use of generative AI in programming.