Explore documented AI literacy and AI education implementations by learning context, learner level, AI use pattern, evidence type, outcomes, risk, privacy, and location.
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Systematic literature review synthesizing global K-12 AI literacy research and surfacing implementation patterns, gaps, and recommendations.
Systematic review of 25 peer-reviewed K-12 AI education studies (2018-2023), synthesizing topics taught, instructional strategies, learning tools, and reported student outcomes.
Field-tested hands-on workshop for 10-11 year-old elementary learners introducing AI literacy through programming and machine learning, including data quality, bias, and ethical reflection.
Quasi-experimental study comparing teacher-led classroom implementation of the DAILy AI literacy curriculum versus no intervention, showing gains in conceptual understanding and AI empowerment among middle school learners.
Informal, one-time public-library workshop (90 minutes) using a generative AI storytelling application to co-create Bluey-themed stories with elementary-age learners (approx. 5–11) in Yorba Linda, Southern California.
Afterschool summer camp (5 days) using a generative AI storytelling application plus AI concept slides with learners ages ~5–7 in Diamond Bar, Southern California. The activity emphasized creative storytelling and early AI awareness, with post-assessment included.
5-day mini AI summer camp (Grades 3–5; approx. ages 8–10) at an afterschool center in Diamond Bar, Southern California. The camp combined short educator-led AI concept lessons with hands-on Scratch projects (programming, data collection, pattern-based behavior, game creation, and introductory reinforcement learning concepts).
5-day mini AI summer camp (Grades 6–9; approx. ages 11–14) at an afterschool center in Diamond Bar, Southern California. The camp combined AI concept slides with simulation-based coding labs (CodeCombat AI HackStack) and hands-on browser-based model training (Teachable Machine), including discussion of bias, perspective, and limitations.
Informal case report of a 13-week quasi-experimental study investigating the impact of a curriculum-aligned generative AI chatbot (ArtChat) on self-regulated learning and engagement among digital media art students at an art university in eastern China.
Integrative review of 124 AI literacy studies (2020-2024) proposing a framework across AI perspectives (technical, tool, sociocultural) and literacy perspectives (functional, critical, indirectly beneficial), with trends in the post-GenAI era.
Systematic review of 25 empirical studies on AI literacy in primary schools, mapping definitions, theoretical frameworks, pedagogies, tools, assessment methods, outcomes, and implementation challenges.
Formative study with 13 middle/high school teachers examining AI literacy levels and co-design of project-based AI toolkit activities across subjects, highlighting adoption opportunities and implementation barriers.
K-12 classroom game resource that teaches critical and transformative AI literacy by having students spoof an image classifier and inspect saliency with XAI, emphasizing model brittleness, bias, and sociotechnical reflection.
Structured, replicable unplugged learning path integrating foundational AI concepts with primary-level mathematics, evaluated with fifth-grade students to improve conceptual understanding, reasoning, and engagement.
Qualitative international stakeholder study (33 experts) framing AI literacy for K-12 through technical and socio-cultural competencies, including conceptual understanding, ethics, critical reflection, and design/development perspectives.
Qualitative study with 76 Canadian educators examining opportunities, challenges, and school strategies for integrating generative AI in K-12 education. Findings highlight benefits for teaching/learning, administration, and assessment, alongside readiness, competency, and ethics concerns.
Scoping review (PRISMA-informed) across ACM, IEEE, Scopus, and Web of Science (March 2024) identifying 19 articles and 17 AI literacy frameworks from early childhood through university. The synthesis argues primary-level frameworks are underdeveloped and often over-emphasize constructionist technical making without fully theorizing human–non-human agency. The paper proposes an intelligence-based framework centered on “AI thinking”: cognitive, creative, and multi-perspective analysis with social, ethical, and environmental considerations, grounded in sociocultural mediation (Vygotsky) and post-humanist perspectives on knowledge infrastructures.
Scoping review of 16 empirical ECE studies (2016–2022) on AI literacy for young children, analyzing instructional design, AI learning tools, assessment methods, and learning outcomes, with recommendations for future research and practice.
Showing first 18 matches. Refine filters to narrow the view.
Compare cases across the core fields AAB needs for synthesis, standards work, and pilot selection.
| Case | Setting | Learners | AI Capability | Evidence | Outcome | Risk / Privacy |
|---|---|---|---|---|---|---|
| AI literacy in K-12: a systematic literature reviewAAB-CASE-2023-RV-001 | In-school K-12 | K-12 learners across primary and secondary levels (varies by study) | Review of AI literacy tools, content, and teaching approaches in prior studies | Not specified | Not specified | MediumMedium (student-learning context; governance varies by implementation) |
| A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomesAAB-CASE-2024-RV-002 | In-school (K-12) | K-12 (majority secondary-level studies; some elementary and middle school) | Synthesis of AI learning tools used in K-12 interventions | Not specified | Not specified | MediumMedium (education context with student learning activities) |
| Understanding how Computers Learn: AI Literacy for Elementary School LearnersAAB-CASE-2024-RV-004 | In-school (K-12) | 10-11 years (5th grade) | Beginner AI literacy tools for elementary ML and programming activities | Not specified | Not specified | Low to MediumLow (classroom activity datasets and non-sensitive learner artifacts) |
| An Effectiveness Study of Teacher-Led AI Literacy Curriculum in K-12 ClassroomsAAB-CASE-2024-RV-011 | In-school (K-12) | Middle school (grades 6-8) | Comprehensive AI literacy curriculum (DAILy) with ethics and career integration | Not specified | Not specified | MediumMedium (student assessment and attitude survey data) |
| Yorba Linda Public Library AI StorytimeAAB-CASE-2025-LL-001 | Informal learning | Approx. ages 5–11 | Generative AI storytelling application | Not specified | High participation; students volunteered ideas actively; peer discussion increased after AI output | LowNone |
| Afterschool Mini AI Summer Camp K-2AAB-CASE-2025-LL-002 | Afterschool center | Approx. ages 5–7 | Generative AI storytelling application; AI concept slides | Not specified | Not specified | LowNone |
| Grades 3-5 Elementary Afterschool Mini AI Summer CampAAB-CASE-2025-LL-003 | Afterschool center | Grades 3–5 (approx. ages 8–10) | AI concept instructional slides (educator-led) | Not specified | High attendance and sustained participation | LowNone |
| Grades 6-9 Middle School Afterschool Mini AI Summer CampAAB-CASE-2025-LL-004 | Afterschool center | Grades 6–9 (approx. ages 11–14) | AI concept instructional slides | Not specified | High engagement throughout; frequent laughter and spontaneous discussion | LowNone |
| ArtChat StudyAAB-CASE-2025-RS-001 | In-class (Higher Ed) | Approx. 19–23 years (undergraduate students) | Curriculum-aligned generative AI chatbot | Not specified | High participation; ArtChat group demonstrated sustained interaction with the tool and increased voluntary engagement with course content | Not specifiedNot specified |
| AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative ReviewAAB-CASE-2025-RV-003 | In-school (K-12) | K-12 and undergraduate learners across included studies | Framework-level synthesis of AI literacy approaches (technical AI, AI tools, sociocultural AI) | Not specified | Not specified | MediumLow to Medium (literature synthesis; no single student dataset) |
| Artificial intelligence literacy education in primary schools: a reviewAAB-CASE-2025-RV-005 | In-school (K-12) | Primary school learners (young students in early and upper primary) | Synthesis of AI literacy learning tools and pedagogical configurations | Not specified | Not specified | MediumMedium (student-learning context with data literacy and bias-related tasks) |
| From Unseen Needs to Classroom Solutions: Exploring AI Literacy Challenges and Opportunities with a Project-Based Learning Toolkit in K-12 EducationAAB-CASE-2025-RV-006 | In-school (K-12) | Middle and high school learners (as represented in teacher-designed plans) | Project-based AI toolkit with multi-modal creation and conversation tools | Not specified | Not specified | MediumMedium (student-generated content and classroom AI interactions) |
| Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI)AAB-CASE-2025-RV-008 | In-school (K-12) | Grades 4-9 (approximately ages 10-15) | Browser-based spoofing game with XAI visual explanations and class leaderboard | Not specified | Not specified | MediumLow to Medium (in-session camera inputs and classroom-generated traces) |
| A Structured Unplugged Approach for Foundational AI Literacy in Primary EducationAAB-CASE-2025-RV-009 | In-school (K-12) | Primary school, grade 5 | Unplugged-first AI literacy pathway with selective digital demonstrations | Not specified | Not specified | Low to MediumLow (classroom tasks and anonymized assessment artifacts) |
| Framing AI Literacy for K-12 Education: Insights from Multi-Perspective and International StakeholdersAAB-CASE-2025-RV-010 | In-school (K-12) | K-12 learners (framework-level target) | Framework and competency elicitation for AI literacy in K-12 | Not specified | Not specified | MediumLow (anonymized expert survey data) |
| Opportunities, challenges and school strategies for integrating generative AI in educationAAB-CASE-2025-RV-012 | School-level | K-12 | LLM/Chat | Qualitative study | AI literacy | MediumMedium |
| A critical review of teaching and learning artificial intelligence (AI) literacy: Developing an intelligence-based AI literacy framework for primary school educationAAB-CASE-2025-RV-013 | Research-informed guidance | K-5 | Foundational AI concepts | Systematic / scoping review | AI literacy frameworks | Low (synthesis); Medium once tools deployed in classroomsLow for the review itself; variable when schools adopt tools |
| Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and OpportunitiesAAB-CASE-2025-RV-014 | Classroom-level | Pre-K | ML concepts | Scoping review | AI concepts | Medium (child data, vendor tools)Medium |
| A Differentiated Discussion About AI Education K‑12AAB-CASE-2025-RV-015 | System-level guidance | K-12 | Foundational AI concepts | Expert synthesis | Access and equity | Medium (varies by pathway)Medium (platform-dependent) |
| From Primary Education to Premium Workforce: Drawing on K-12 Approaches for Developing AI LiteracyAAB-CASE-2025-RV-016 | Partnership (university + union) | Adult / workforce | ML concepts | Pre/post survey | Knowledge gains | MediumMedium (workplace examples, surveys) |
| Teaching AI to K-12 Learners: Lessons, Issues, and GuidanceAAB-CASE-2025-RV-017 | Classroom-level | K-12 | ML concepts | Literature-informed position | Pedagogical design | MediumMedium (datasets, APIs, student work) |
| Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementationAAB-CASE-2025-RV-018 | Classroom-level | Pre-K | ML concepts | Literature synthesis | Digital equity | MediumMedium |
| Artificial Intelligence (AI) in early childhood education: Curriculum design and future directionsAAB-CASE-2025-RV-019 | Classroom-level | Pre-K | Robotics | Literature-based analysis | PBL recommendation | MediumMedium |
| Systematic review of research on artificial intelligence in K-12 education (2017–2022)AAB-CASE-2025-RV-020 | Classroom-level | K-12 | ML | Systematic review | Engagement | Medium–High (prediction, data)High in many primary studies |
| Behavioral-pattern exploration and development of an instructional tool for young children to learn AIAAB-CASE-2025-RV-021 | Classroom-level | K-5 | Image classification | Mixed methods | Engagement patterns | MediumMedium–High (images, logs) |
| ActiveAI: Introducing AI literacy for Middle School Learners with Goal-based Scenario LearningAAB-CASE-2025-RV-022 | Classroom-level | 6-8 | Classification | Design rationale | Engagement | MediumMedium |
| Artificial intelligence in K-12 education: An umbrella reviewAAB-CASE-2025-RV-023 | System-level guidance | K-12 | Broad AIEd applications | Review of reviews | Research mapping | VariesHigh in many underlying applications |
| Fostering responsible AI literacy: A systematic review of K-12 AI ethics educationAAB-CASE-2025-RV-024 | Curriculum / policy guidance | K-12 | Ethics and society | Systematic review | Ethical learning outcomes | MediumMedium |
| Exploring Teachers' Perceptions of Artificial Intelligence as a Tool to Support their Practice in Estonian K-12 EducationAAB-CASE-2025-RV-025 | School-level | K-12 | Intelligent tutoring | Survey | Teacher readiness | MediumMedium (future analytics on teaching) |
| Integrating artificial intelligence in literacy lessons for elementary classrooms: a co-design approachAAB-CASE-2025-RV-026 | Classroom-level | K-5 | Generative AI | Mixed methods | Engagement | MediumMedium |
| AI in STEM education: The relationship between teacher perceptions and ChatGPT useAAB-CASE-2025-RV-027 | Classroom-level | 9-12 | LLM/Chat | Survey | Teacher beliefs | MediumLow–Medium |
| Young children's understanding of AIAAB-CASE-2025-RV-028 | Research-informed guidance | 6-8 | Ethics and society | Interviews | Student voice | LowMedium (child discourse) |
| Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriersAAB-CASE-2025-RV-029 | Rural schools | K-12 | Generative AI | Mixed methods | Preparedness | MediumMedium |
| Primary school students’ perceptions of artificial intelligence – for good or badAAB-CASE-2025-RV-030 | Classroom-level | 6-8 | LLM/Chat | Mixed methods | Perceptions | Low–MediumMedium |
| Analyzing K-12 AI education: A large language model study of classroom instruction on learning theories, pedagogy, tools, and AI literacyAAB-CASE-2025-RV-031 | Classroom-level | K-12 | LLM/Chat | Learning analytics | Pedagogy patterns | Medium (method misuse)High (video) |
| Artificial Intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature reviewAAB-CASE-2025-RV-032 | Classroom-level | K-12 | ML | Systematic review | Learning outcomes | Low (synthesis)N/A |
| What are artificial intelligence literacy and competency? A comprehensive framework to support themAAB-CASE-2025-RV-033 | Classroom-level | 6-8 | Generative AI | Qualitative co-design | Competency framing | Low (framework)Low |
| Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic ReviewAAB-CASE-2025-RV-034 | Classroom-level | K-12 | Foundational AI concepts | Systematic review | Motivation | LowN/A |
| Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design ConsiderationsAAB-CASE-2025-RV-035 | Informal learning | K-12 | Generative AI | Literature synthesis | Design ethics | High if unmanagedHigh |
| Briteller: Shining a Light on AI Recommendation for ChildrenAAB-CASE-2025-RV-036 | Informal learning | 6-8 | Recommendation systems | User study | Concept learning | LowLow |
| Children's Mental Models of AI Reasoning: Implications for AI Literacy EducationAAB-CASE-2025-RV-037 | Classroom-level | K-5 | Reasoning | Mixed methods | Mental models | LowMedium |
| Taking the Magic Out of the Machine: Children as Creators of Real-World AI-Powered Tools for EducationAAB-CASE-2025-RV-038 | Classroom-level | 6-8 | Applied AI | Position paper | Agency | HighHigh |
| Artificial intelligence literacy in primary education: An arts-based approach to overcoming age and gender barriersAAB-CASE-2025-RV-039 | Classroom-level | K-5 | Ethics and society | Pre/post | Equity | MediumMedium |
| Secondary Students as Co-Researchers on Generative AI in Learning: Empowering Youth to Shape National Education PolicyAAB-CASE-2025-RV-040 | System-level guidance | 9-12 | Generative AI | Qualitative | Student voice | MediumMedium |
| Conceptualizing AI literacies for children and youth: A systematic review on the design of AI literacy educational programsAAB-CASE-2025-RV-041 | Classroom-level | K-12 | Broad | Systematic review | Framework critique | LowN/A |
| Developing a Holistic AI Literacy Framework for ChildrenAAB-CASE-2025-RV-042 | Cross-cutting | K-12 | Foundational AI concepts | Systematic review | Curriculum guidance | LowN/A |
| Building AI Literacy at Home: How Families Navigate Children’s Self-Directed Learning with AIAAB-CASE-2025-RV-043 | Informal learning | K-5 | Generative AI | Interviews | Home learning | MediumHigh |
| BrickSmart: Leveraging Generative AI to Support Children’s Spatial Language Learning in Family Block PlayAAB-CASE-2025-RV-044 | Informal learning | Pre-K | Generative AI | Comparative study | Spatial language | MediumMedium |
| Aligning technology with cognitive development: a five-tiered framework to generative AI in K-12 educationAAB-CASE-2025-RV-045 | System-level guidance | K-12 | Generative AI | Expert synthesis | Risk mitigation | VariesHigh |
| Attitudes, perceptions and AI self-efficacy in K-12 educationAAB-CASE-2025-RV-046 | System-level guidance | K-12 | LLM/Chat | Pre/post | Self-efficacy | Medium (integrity if misused)Medium |
| Empowering Children’s AI Literacy Through Co-Creating Stories with LLMAAB-CASE-2025-RV-047 | Informal learning | K-5 | LLM/Chat | Pre/post | Engagement | MediumMedium |
| AI literacy, educational level, and parenting self-efficacy of children’s education among parents of primary school studentsAAB-CASE-2025-RV-048 | Informal learning | K-5 | Broad | Pre/post | Self-efficacy | LowMedium |
| Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern educationAAB-CASE-2025-RV-049 | Classroom-level | Higher education | LLM/Chat | Literature synthesis | Curriculum guidance | MediumLow |
| AI Education in Middle School: Exploring the Mechanisms and Constraints of Generative AIAAB-CASE-2025-RV-050 | Classroom-level | 6-8 | LLM/Chat | Mixed methods | Knowledge | MediumMedium |
| Learner perspectives on AI teacher effectiveness: The role of engagement, motivation, efficiency, and educational experienceAAB-CASE-2025-RV-051 | Classroom-level | Higher education | LLM/Chat | Post assessment | Engagement | High if fully automated without supportMedium |
| Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI ErrorsAAB-CASE-2025-RV-052 | Classroom-level | Higher education | Generative AI | Post assessment | Skills | MediumLow |
| Teachers’ and students’ perceptions of AI-generated concept explanations: Implications for integrating generative AI in computer science educationAAB-CASE-2025-RV-053 | Classroom-level | K-5 | LLM/Chat | Mixed methods | Perceptions | MediumMedium |
| Understanding Student Perceptions of Artificial Intelligence as a TeammateAAB-CASE-2025-RV-054 | Classroom-level | 9-12 | Reasoning | Qualitative | Collaboration | MediumMedium |
| Pre-service teachers preparedness for AI-integrated education: An investigation from perceptions, capabilities, and teachers’ identity changesAAB-CASE-2025-RV-055 | Classroom-level | Higher education | Broad | Qualitative | Identity | LowMedium |
| Investigating pre-service teachers’ artificial intelligence perception from the perspective of planned behavior theoryAAB-CASE-2025-RV-056 | System-level guidance | Higher education | Foundational AI concepts | Post assessment | Attitudes | LowMedium |
| Fairness for machine learning software in education: A systematic mapping studyAAB-CASE-2025-RV-057 | System-level guidance | Higher education | Prediction / risk scoring | Systematic review | Equity | High if unfair models deployedHigh |
| Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI-enhanced methodsAAB-CASE-2025-RV-058 | System-level guidance | Higher education | Generative AI | Mixed methods | Attitudes | MediumMedium |
| Artificial intelligence in education: A systematic literature reviewAAB-CASE-2025-RV-059 | Cross-cutting | K-12 | Broad | Systematic review | Research synthesis | LowN/A |
| Artificial intelligence in teaching and teacher professional development: A systematic reviewAAB-CASE-2025-RV-060 | Cross-cutting | K-12 | Broad | Systematic review | Research synthesis | LowN/A |
| Learning to Use AI for Learning: Teaching Responsible Use of AI Chatbot to K-12 Students Through an AI Literacy ModuleAAB-CASE-2026-RV-007 | In-school (K-12) | Secondary school learners (middle and high school) | LLM-based prompting literacy learning and assessment module | Not specified | Not specified | MediumMedium (student-written prompts and learning assessment traces) |
| Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language ModelsAAB-CASE-2026-RV-061 | Higher education | Higher education | LLM/Chat | Pre/post or experimental evidence | Conceptual understanding | MediumMedium |
| Making Transparency Advocates: An Educational Approach Towards Better Algorithmic Transparency in PracticeAAB-CASE-2026-RV-062 | Professional / adult learning | Adult / workforce | Explainable AI / robustness | Activity documentation | AI literacy | MediumLow to Medium |
| The Essentials of AI for Life and Society: An AI Literacy Course for the University CommunityAAB-CASE-2026-RV-063 | Higher education | Higher education | Assessment / tutoring analytics | Qualitative study | AI literacy | Low to MediumMedium |
| Developing a Postgraduate Program for AI in Medicine with Kern’s Six-Step Curriculum Development Approach in SingaporeAAB-CASE-2026-RV-064 | Higher education | Graduate / professional | Ethics / responsible AI | Activity documentation | Conceptual understanding | MediumLow to Medium |
| Artificial Intelligence for Future Presidents: Teaching AI Literacy to EveryoneAAB-CASE-2026-RV-065 | Research / curriculum design context | Unspecified / broad education | AI literacy / AI concepts | Activity documentation | AI literacy | Low to MediumMedium |
| Automated Assessment of Student Self-Explanation in Code Comprehension Using Pre-Trained Language ModelsAAB-CASE-2026-RV-066 | Research / curriculum design context | Unspecified / broad education | NLP / text classification | Design / conceptual evidence | Conceptual understanding | MediumMedium |
| Computational Thinking with Computer Vision: Developing AI Competency in an Introductory Computer Science CourseAAB-CASE-2026-RV-067 | Higher education | Higher education | Computer vision / image classification | Survey | AI literacy | MediumMedium |
| AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics Behind AIAAB-CASE-2026-RV-068 | Research / curriculum design context | Unspecified / broad education | Ethics / responsible AI | Activity documentation | AI literacy | MediumLow to Medium |
| Using Explainable AI and Hierarchical Planning for Outreach with RobotsAAB-CASE-2026-RV-069 | In-school (K-12) | K-12 | Robotics / physical AI | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| Human-Computer Interaction for AI Systems Design: Reflections on an Online Course on Human-AI Interaction for ProfessionalsAAB-CASE-2026-RV-070 | Higher education | Higher education | Assessment / tutoring analytics | Activity documentation | Engagement / motivation | Low to MediumMedium |
| Bridging the AI Gap: Evaluating the Impact of an AI Education Program for Caregivers on Parental LeaveAAB-CASE-2026-RV-071 | Professional / adult learning | Adult / workforce | ML concepts / supervised learning | Survey | AI literacy | Low to MediumMedium |
| Can LLMs Reliably Simulate Human Learner Actions? A Simulation Authoring Framework for Open-Ended Learning EnvironmentsAAB-CASE-2026-RV-072 | Research / curriculum design context | Unspecified / broad education | LLM/Chat | Design / conceptual evidence | Conceptual understanding | MediumMedium |
| Comparing Artificial Intelligence Curricula in Canadian and US UniversitiesAAB-CASE-2026-RV-073 | Higher education | Higher education | Computer vision / image classification | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Using Case Studies to Teach Responsible AI to Industry PractitionersAAB-CASE-2026-RV-074 | Professional / adult learning | Adult / workforce | Ethics / responsible AI | Activity documentation | Conceptual understanding | MediumLow to Medium |
| We Are AI: Taking Control of TechnologyAAB-CASE-2026-RV-075 | Higher education | Higher education | Ethics / responsible AI | Activity documentation | AI literacy | MediumLow to Medium |
| Towards an AI Course Based on Neural NetworksAAB-CASE-2026-RV-076 | Research / curriculum design context | Unspecified / broad education | ML concepts / supervised learning | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Developing Chatbots for Sustainability: Experiential Learning in an Undergraduate Business CourseAAB-CASE-2026-RV-077 | Higher education | Higher education | LLM/Chat | Activity documentation | AI literacy | MediumMedium |
| “AlphAI”: Teaching AI Algorithms to K12 by Training Learning Robots and Visualizing How It WorksAAB-CASE-2026-RV-078 | In-school (K-12) | K-5 | Robotics / physical AI | Design / conceptual evidence | AI literacy | Low to MediumLow to Medium |
| Designing Characters with AI: An Art & AI Learning ActivityAAB-CASE-2026-RV-079 | In-school (K-12) | 9-12 | Generative AI | Survey | Conceptual understanding | MediumMedium |
| Understanding K-12 Teachers’ Needs for AI Education: A Survey-Based StudyAAB-CASE-2026-RV-080 | In-school (K-12) | K-12 | LLM/Chat | Survey | AI literacy | MediumMedium |
| Advancing Research on Equitable AI Education Through a Focus on Implementation: Insights from a Middle School Computer Vision Module Beta-TestAAB-CASE-2026-RV-081 | In-school (K-12) | 6-8 | Computer vision / image classification | Qualitative study | AI literacy | MediumMedium |
| Smart Motor: A Low-Cost Hardware and Software Toolkit for Introducing Supervised Machine Learning to Elementary School StudentsAAB-CASE-2026-RV-082 | In-school (K-12) | K-5 | Robotics / physical AI | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| Empowering Educators in AI: Insights from Co-Designing an AI Microcredential with and for K-12 EducatorsAAB-CASE-2026-RV-083 | In-school (K-12) | K-12 | AI literacy / AI concepts | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Shaping AI Interest in Rural Middle Schools with Unplugged Learning: Gender Differences and Teacher InsightsAAB-CASE-2026-RV-084 | In-school (K-12) | 6-8 | AI literacy / AI concepts | Survey | Conceptual understanding | Low to MediumMedium |
| A Versatile Low-Cost Kit for Teaching Novice Learners AI Using Robotics Components and a No-Code Development PlaygroundAAB-CASE-2026-RV-085 | In-school (K-12) | K-12 | Robotics / physical AI | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Fostering Epistemic Insights into AI Ethics through a Constructionist Pedagogy: An Interdisciplinary Approach to AI LiteracyAAB-CASE-2026-RV-086 | In-school (K-12) | K-5 | Generative AI | Pre/post or experimental evidence | AI literacy | MediumMedium |
| Supporting AI Literacy Teaching Through the Development of Assessments for Classroom UseAAB-CASE-2026-RV-087 | In-school (K-12) | 9-12 | Ethics / responsible AI | Activity documentation | AI literacy | MediumMedium |
| Learning About Algorithm Auditing in Five Steps: Scaffolding How High School Youth Can Systematically and Critically Evaluate Machine Learning ApplicationsAAB-CASE-2026-RV-088 | In-school (K-12) | 9-12 | Generative AI | Activity documentation | Conceptual understanding | MediumLow to Medium |
| What Can Youth Learn About Artificial Intelligence and Machine Learning in One Hour? Examining How Hour of Code Activities Address the Five Big Ideas of AIAAB-CASE-2026-RV-089 | In-school (K-12) | K-12 | ML concepts / supervised learning | Activity documentation | AI literacy | Low to MediumMedium |
| An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based RecommendingAAB-CASE-2026-RV-090 | In-school (K-12) | K-12 | Explainable AI / robustness | Pre/post or experimental evidence | Conceptual understanding | MediumHigh |
| Learning to Think Like a Neuron in Middle SchoolAAB-CASE-2026-RV-091 | In-school (K-12) | 6-8 | ML concepts / supervised learning | Survey | Conceptual understanding | Low to MediumMedium |
| AI Chef Trainer: Introducing Students to the Importance of Data in Machine LearningAAB-CASE-2026-RV-092 | In-school (K-12) | K-5 | ML concepts / supervised learning | Design / conceptual evidence | AI literacy | Low to MediumMedium |
| Word2Vec4Kids: Interactive Challenges to Introduce Middle School Students to Word EmbeddingsAAB-CASE-2026-RV-093 | In-school (K-12) | 6-8 | NLP / text classification | Survey | AI literacy | Low to MediumMedium |
| Does Any AI-Based Activity Contribute to Develop AI Conception? A Case Study with Italian Fifth and Sixth Grade ClassesAAB-CASE-2026-RV-094 | In-school (K-12) | K-5 | AI literacy / AI concepts | Activity documentation | AI literacy | Low to MediumLow to Medium |
| A Study of Students’ Learning of Computing through an LP-Based Integrated Curriculum for Middle SchoolsAAB-CASE-2026-RV-095 | In-school (K-12) | 6-8 | AI literacy / AI concepts | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| AI and Parallelism in CS1: Experiences and AnalysisAAB-CASE-2026-RV-096 | Higher education | Higher education | ML concepts / supervised learning | Survey | Conceptual understanding | Low to MediumMedium |
| Shared Tasks as Tutorials: A Methodical ApproachAAB-CASE-2026-RV-097 | Research / curriculum design context | Unspecified / broad education | Robotics / physical AI | Activity documentation | Implementation guidance | Low to MediumMedium |
| Maestro: A Gamified Platform for Teaching AI RobustnessAAB-CASE-2026-RV-098 | Higher education | Higher education | Explainable AI / robustness | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Exploring Social Biases of Large Language Models in a College Artificial Intelligence CourseAAB-CASE-2026-RV-099 | Higher education | Higher education | LLM/Chat | Pre/post or experimental evidence | Conceptual understanding | HighMedium |
| An Analysis of Engineering Students’ Responses to an AI Ethics ScenarioAAB-CASE-2026-RV-100 | Higher education | Higher education | Ethics / responsible AI | Survey | Conceptual understanding | HighMedium |
| Autonomous Agents: An Advanced Course on AI Integration and DeploymentAAB-CASE-2026-RV-101 | Higher education | Higher education | Robotics / physical AI | Activity documentation | Assessment / feedback quality | Low to MediumMedium |
| AI Made by Youth: A Conversational AI Curriculum for Middle School Summer CampsAAB-CASE-2026-RV-102 | In-school (K-12) | 6-8 | LLM/Chat | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Learning Affects Trust: Design Recommendations and Concepts for Teaching Children—and Nearly Anyone—about Conversational AgentsAAB-CASE-2026-RV-103 | In-school (K-12) | K-12 | LLM/Chat | Activity documentation | Conceptual understanding | Low to MediumMedium |
| FOLL-E: Teaching First Order Logic to ChildrenAAB-CASE-2026-RV-104 | In-school (K-12) | K-12 | Computer vision / image classification | Design / conceptual evidence | Conceptual understanding | Low to MediumLow to Medium |
| Responsible Robotics: A Socio-Ethical Addition to Robotics CoursesAAB-CASE-2026-RV-105 | Research / curriculum design context | Unspecified / broad education | Computer vision / image classification | Activity documentation | Conceptual understanding | MediumMedium |
| Data Labeling for Machine Learning Engineers: Project-Based Curriculum and Data-Centric CompetitionsAAB-CASE-2026-RV-106 | Higher education | Higher education | ML concepts / supervised learning | Activity documentation | AI literacy | Low to MediumMedium |
| Does Knowing When Help Is Needed Improve Subgoal Hint Performance in an Intelligent Data-Driven Logic Tutor?AAB-CASE-2026-RV-107 | Research / curriculum design context | Unspecified / broad education | Assessment / tutoring analytics | Pre/post or experimental evidence | Conceptual understanding | Low to MediumMedium |
| Ripple: Concept-Based Interpretation for Raw Time Series Models in EducationAAB-CASE-2026-RV-108 | Research / curriculum design context | Unspecified / broad education | ML concepts / supervised learning | Learning analytics | Conceptual understanding | HighHigh |
| Exploring Tradeoffs in Automated School Redistricting: Computational and Ethical PerspectivesAAB-CASE-2026-RV-109 | Research / curriculum design context | Unspecified / broad education | LLM/Chat | Qualitative study | Ethics and responsible use | HighHigh |
| Learning Logical Reasoning Using an Intelligent Tutoring System: A Hybrid Approach to Student ModelingAAB-CASE-2026-RV-110 | Research / curriculum design context | Unspecified / broad education | Assessment / tutoring analytics | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| Context-Aware Analysis of Group Submissions for Group Anomaly Detection and Performance PredictionAAB-CASE-2026-RV-111 | Higher education | Higher education | Generative AI | Learning analytics | Conceptual understanding | HighHigh |
| CLGT: A Graph Transformer for Student Performance Prediction in Collaborative LearningAAB-CASE-2026-RV-112 | Research / curriculum design context | Unspecified / broad education | Explainable AI / robustness | Learning analytics | Conceptual understanding | HighHigh |
| H-AES: Towards Automated Essay Scoring for HindiAAB-CASE-2026-RV-113 | Research / curriculum design context | Unspecified / broad education | NLP / text classification | Design / conceptual evidence | Conceptual understanding | HighHigh |
| Detecting Exclusive Language during Pair ProgrammingAAB-CASE-2026-RV-114 | Research / curriculum design context | Unspecified / broad education | NLP / text classification | Design / conceptual evidence | Implementation guidance | MediumMedium |
| Solving Math Word Problems concerning Systems of Equations with GPT-3AAB-CASE-2026-RV-115 | Research / curriculum design context | Unspecified / broad education | LLM/Chat | Design / conceptual evidence | Conceptual understanding | MediumMedium |
| AI Audit: A Card Game to Reflect on Everyday AI SystemsAAB-CASE-2026-RV-116 | In-school (K-12) | 9-12 | Explainable AI / robustness | Activity documentation | AI literacy | MediumMedium |
| Beyond Black-Boxes: Teaching Complex Machine Learning Ideas through Scaffolded Interactive ActivitiesAAB-CASE-2026-RV-117 | In-school (K-12) | 9-12 | ML concepts / supervised learning | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| Exploring Artificial Intelligence in English Language Arts with StoryQAAB-CASE-2026-RV-118 | In-school (K-12) | 6-8 | Generative AI | Design / conceptual evidence | Conceptual understanding | MediumMedium |
| An Introduction to Rule-Based Feature and Object Perception for Middle School StudentsAAB-CASE-2026-RV-119 | In-school (K-12) | 6-8 | Computer vision / image classification | Design / conceptual evidence | Conceptual understanding | MediumHigh |
| Scratch for Sports: Athletic Drills as a Platform for Experiencing, Understanding, and Developing AI-Driven AppsAAB-CASE-2026-RV-120 | In-school (K-12) | K-12 | Assessment / tutoring analytics | Design / conceptual evidence | Conceptual understanding | Low to MediumMedium |
| “How Can I Code A.I. Responsibly?”: The Effect of Computational Action on K-12 Students Learning and Creating Socially Responsible A.I.AAB-CASE-2026-RV-121 | In-school (K-12) | K-12 | Ethics / responsible AI | Survey | Conceptual understanding | MediumMedium |
| Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering ArchitectureAAB-CASE-2026-RV-122 | In-school (K-12) | K-5 | LLM/Chat | Activity documentation | AI literacy | MediumMedium |
| Develop AI Teaching and Learning Resources for Compulsory Education in ChinaAAB-CASE-2026-RV-123 | In-school (K-12) | K-5 | AI literacy / AI concepts | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Guiding Students to Investigate What Google Speech Recognition Knows about LanguageAAB-CASE-2026-RV-124 | In-school (K-12) | 6-8 | Computer vision / image classification | Pre/post or experimental evidence | Conceptual understanding | MediumHigh |
| Literacy and STEM Teachers Adapt AI Ethics CurriculumAAB-CASE-2026-RV-125 | Higher education | Higher education | Ethics / responsible AI | Design / conceptual evidence | AI literacy | MediumMedium |
| Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade ClassroomsAAB-CASE-2026-RV-126 | In-school (K-12) | 6-8 | AI literacy / AI concepts | Activity documentation | Conceptual understanding | Low to MediumMedium |
| A Socially Relevant Focused AI Curriculum Designed for Female High School StudentsAAB-CASE-2026-RV-127 | In-school (K-12) | 9-12 | NLP / text classification | Survey | Conceptual understanding | Low to MediumMedium |
| Interactive Visualizations of Word Embeddings for K-12 StudentsAAB-CASE-2026-RV-128 | In-school (K-12) | K-12 | NLP / text classification | Pre/post or experimental evidence | Teacher readiness | Low to MediumMedium |
| Smartphone-Based Game Development to Introduce K12 Students in Applied Artificial IntelligenceAAB-CASE-2026-RV-129 | In-school (K-12) | 9-12 | Computer vision / image classification | Design / conceptual evidence | Conceptual understanding | MediumHigh |
| Preparing High School Teachers to Integrate AI Methods into STEM ClassroomsAAB-CASE-2026-RV-130 | In-school (K-12) | 9-12 | ML concepts / supervised learning | Activity documentation | Conceptual understanding | MediumMedium |
| Introducing Variational Autoencoders to High School StudentsAAB-CASE-2026-RV-131 | In-school (K-12) | 9-12 | Generative AI | Design / conceptual evidence | Conceptual understanding | MediumMedium |
| Paving the Way for Novices: How to Teach AI for K-12 Education in ChinaAAB-CASE-2026-RV-132 | In-school (K-12) | K-12 | AI literacy / AI concepts | Activity documentation | Conceptual understanding | Low to MediumMedium |
| Teaching AI with the Hands-On AI Projects for the Classroom SeriesAAB-CASE-2026-RV-133 | In-school (K-12) | K-12 | AI literacy / AI concepts | Activity documentation | Teacher readiness | Low to MediumMedium |
| StoryQ—an Online Environment for Machine Learning of Text ClassificationAAB-CASE-2026-RV-134 | In-school (K-12) | K-12 | NLP / text classification | Design / conceptual evidence | Conceptual understanding | MediumLow to Medium |
| AI Snap! Blocks for Speech Input and Output, Computer Vision, Word Embeddings, and Neural Net Creation, Training, and UseAAB-CASE-2026-RV-135 | In-school (K-12) | K-12 | Computer vision / image classification | Activity documentation | Conceptual understanding | MediumHigh |
