Source-linked AI summary
Engaging Teachers to Co-Design Integrated AI Curriculum for K-12 Classrooms
Jessica Van Brummelen, Phoebe Lin
TL;DR
AI education is increasingly important in K-12 settings, but accessible integration into core subjects remains underexplored. The authors co-designed curricula with 15 teachers and found that integrated lessons can connect AI to subject-related datasets, engagement, reflection, and ethics. The study highlights teacher–researcher collaboration while cautioning that its small, non-technical-subject focus limits generalization.
Problem
AI education is increasingly popular, but little research has examined how to make it accessible to all learners through integration with core curriculum.
Method
The authors conducted a two-day co-design workshop with 15 K-12 teachers and researchers to create AI-integrated lesson plans.
Results
Teachers co-created AI-integrated curricula for social studies, literacy, and ESL, connecting AI with datasets, engagement, reflection, and ethics.
Takeaways & Limitations
Embedding AI concepts in core subjects and incorporating supports for engagement, collaboration, reflection, ethics, and data discussions may improve AI education accessibility.
Takeaways & Limitations
Because the study focused on a small group of teachers integrating AI with non-technical subjects, broader applications should be approached cautiously.
Abstract
from arXiv · showhide
Artificial Intelligence (AI) education is an increasingly popular topic area for K-12 teachers. However, little research has investigated how AI education can be designed to be more accessible to all learners. We organized co-design workshops with 15 K-12 teachers to identify opportunities to integrate AI education into core curriculum to leverage learners' interests. During the co-design workshops, teachers and researchers co-created lesson plans where AI concepts were embedded into various core subjects. We found that K-12 teachers need additional scaffolding in the curriculum to facilitate ethics and data discussions, and value supports for learner engagement, collaboration, and reflection. We identify opportunities for researchers and teachers to collaborate to make AI education more accessible, and present an exemplar lesson plan that shows entry points for teaching AI in non-computing subjects. We also reflect on co-designing with K-12 teachers in a remote setting.
1 INTRODUCTION
AI education is gaining attention, but teachers need support to make it accessible beyond computing subjects. This study co-designs integrated AI curriculum with K-12 teachers to address teaching needs and leverage learners’ interests.
- AI education is increasingly popular, prompting calls for K-12 students to develop AI literacy and critically evaluate AI’s societal impact.
- Teachers often lack sufficient AI understanding or capacity to add curriculum, while existing resources are difficult to implement accessibly.
- AI should extend beyond computing subjects because it connects with topics including government, journalism, and art.
- The study used a two-day co-design workshop with 15 teachers to identify implementation needs and create integrated AI lesson plans.
- The work contributes teacher-informed design considerations, an exemplar integrated curriculum, and reflections on remote co-design.
2 RELATED WORK
Prior AI education work includes standalone tools and some curriculum integrations, but teacher involvement and regular-classroom validation remain limited. This study applies teacher–researcher co-design to AI-integrated core curricula.
- Few studies describe co-designing AI concepts with K-12 teachers for integration into core curriculum.
- Many AI teaching tools are standalone products or extensions of computer science curricula.
- Most instructor-focused AI education research involves researchers rather than K-12 teachers, potentially missing classroom expertise and feedback.
- Existing core-curriculum integrations often use researchers as facilitators and have not been tested in regular classrooms with teacher-designed curricula.
- A prior Australian K-6 example integrated AI and science with teacher collaboration, but further research on widespread integrated curricula is needed.
- The study adopts teacher co-design considerations emphasizing classroom context, concrete innovation challenges, and accountability for product quality.
3 METHOD
The study used a remote, two-day co-design workshop with 15 educators, combining AI orientation, preparation activities, group curriculum design, reflection, surveys, and thematic analysis.
- Fifteen educators participated in a two-day workshop with pre-work, surveys, and three smaller co-design groups.
- Session 1: Session 1 established shared AI understanding through presentations, discussions, tool demonstrations, and a card-sorting activity.
- Session 1: Participants explored AI tools and selected classroom curricula before Session 2 to identify opportunities for integrated AI instruction.
- Session 2: Session 2 grouped participants with domain expertise to analyze an exemplar and co-design implementable AI curricula for specific subjects.
- Session 2: Every group produced a first draft integrating AI with a core subject, followed by reflection and post-workshop questionnaires.
- Researchers transcribed and thematically coded workshop recordings, questionnaires, and participant deliverables to examine processes, priorities, and challenges.
- Average self-rated AI familiarity increased from 4.8 to 5.8 out of 7 across the workshop.
4 RESULTS AND DISCUSSION
Three groups created curriculum drafts integrating AI with social studies, literacy for students with learning disabilities, and ESL. The drafts addressed shared teacher considerations while supporting diverse learner needs.
- Three groups completed curriculum drafts on government policy and data, vocabulary learning with AI, and an AI-powered pronunciation application.
- The drafts addressed AI integration for social studies, literacy for students with learning disabilities, and ESL contexts.
- Participants shared considerations across groups, while each group addressed them differently in its curriculum design.
4.1 RQ1: How might we address the values and considerations of K-12 teachers when designing AI curriculum?
Teachers identified evaluation, engagement, logistics, and collaboration as central considerations when designing K-12 AI curriculum. They sought scaffolding for assessing conceptual understanding, engaging learners, selecting workable resources, and structuring inclusive group work.
- Evaluation: Teachers viewed evaluation as critical and wanted evidence that students understood AI concepts correctly.They emphasized conceptual knowledge rather than technical knowledge and considered alternatives such as exit interviews and engineering logs.
- Engagement: Teachers used real-world contexts and challenging questions as anchors to promote student engagement with AI activities.Social studies groups connected projects to law, government, and real-world AI applications.
- Logistics: Teachers needed guidance on lesson structure, classroom resources, technology choices, and age-appropriate learning activities.Participants often looked to researchers for help deciding when and how tools such as Machine Learning for Kids or Google Quick Draw could be used.
- Collaboration: Collaboration supported data collection, model training, and discussion of design and ethics decisions.Group work also created opportunities for students to discuss these decisions with peers and teachers.
- Collaboration: Teachers stressed that group size and available technology should be designed so every student can contribute and learn.They described smaller groups, including duos, as effective while recognizing that technology constraints can limit grouping choices.
4.2 RQ2: How might AI curricula support teachers when they teach AI?
Teachers integrated AI into core subjects by connecting AI tools and concepts with subject content and overlapping ideas. Their curricula used data, reflection, and ethics as entry points, while workshop findings showed strong interest in ethics alongside apprehension about teaching it without scaffolding.
- Integrated curriculum design: Teachers connected AI with core subjects by relating AI tools to subject content, relating subject content to AI, and identifying overlapping concepts.Examples included style transfer and history, recommendation algorithms and social studies, and shared concepts such as representation and reasoning.
- Points of integration: The co-designed curricula integrated AI through data, reflection, and ethics.These three integration points supported teaching AI concepts alongside core curriculum requirements.
- Data: Core classroom activities provided data for AI learning, including airplane construction, pronunciation practice, and vocabulary-image classification.These activities connected data-related competencies and machine-learning steps with physics, language, and literacy learning.
- Reflection: Reflection activities linked AI methods and competencies with patterns, data literacy, critical interpretation, ethics, and subject standards.Students reflected on model inputs and outputs, image-category data, social norms, resource access, and peer consensus.
- Ethics: Teachers were highly interested in teaching ethics but apprehensive about implementing ethics activities without planned curricular support.Participants described planned lessons as making ethics discussions less intimidating for teachers.
- Ethics: The authors identify ethics scaffolding as a way to support core-curriculum integration and teachers’ confidence in teaching ethics.The proposed scaffolding addresses both curriculum design and teacher implementation concerns.
4.3 Reflecting on Remote Co-design
The co-design workshop was conducted remotely during COVID-19 and was generally perceived as helpful, with presentations receiving the most votes. Teachers reported increased familiarity and confidence, but the workshop lacked a baseline measure and involved discipline mismatches and limited time with tools.
- Workshop activities: 11 votes rated presentations most helpful, followed by 9 for the co-design activity and 7 each for Why AI? and Ethics discussions.The Card sorting activity received 4 votes.
- Participant takeaways: Teachers valued meeting like-minded educators, accessing tool and link lists, and seeing AI as accessible beyond computing-focused audiences.They also described AI as opening opportunities for coding and learning.
- Outcomes: The workshop showed a slight increase in AI familiarity and high confidence integrating AI, but no baseline was established.The absence of a baseline limits interpretation of the reported change in familiarity.
- Design reflections: Remote grouping with researchers supported collaboration but sometimes placed teachers in groups working outside their disciplines.Participants also requested more time to use AI tools and process presentations.
4.4 Broader Implications and Limitations
Co-design with teachers supported integrating AI into core subjects and reaching non-technical learners, while the study’s small, non-technical-subject focus limits broader application.
- Broader Implications: Teacher-researcher co-design connected AI curriculum to actual classroom contexts and supported embedding AI in subjects such as social studies and English.The authors emphasize teacher buy-in and contextual understanding as important for classroom adoption.
- Broader Implications: Integrated AI curricula can leverage students’ existing interests in non-technical subjects as pathways into AI.
- Limitations: The study’s findings should be extended cautiously because the exploration involved a small group of teachers and focused on integrating AI with non-technical subjects.
5 CONCLUSION
The paper explored how AI education can be integrated into existing K-12 core curricula through teacher-researcher co-design. It found that teachers valued curriculum addressing student evaluation and engagement.
- 5 CONCLUSION: A two-day co-design workshop engaged K-12 teachers and researchers to create lesson plans embedding AI concepts in social studies, ESL, and literacy for students with learning disabilities.
- 5 CONCLUSION: Teachers valued curriculum that addresses student evaluation and engagement.