Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade Classrooms

Source publication / research team or educational organization described in paper

Not specified in extracted text

Researchers, educators, instructors, or facilitators as described in the source publication

• In-school (K-12)
• Informal learning
• Professional / adult learning

Workshop / professional learning activity

Not specified in extracted text

riety of disci- plines, it is increasingly important to teach AI concepts to K- 12 students in order to prepare them for an AI-driven future workforce. Hence, educators and researchers have been work- ing to dev; ve been work- ing to develop curricula that make these concepts accessible to K-12 students. We are designing and developing a compre- hensive AI curriculum delivered through a series of carefully crafted activi; with a single high-school student. They were further refined after a group of K-12 teachers examined and critiqued them during a two-week professional development workshop. Our teachers created a lesson plan aro

AI literacy / AI concepts

• Teacher readiness, time, support, and classroom integration may affect implementation quality.
• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

6-8, Adult / workforce

Mixed or not explicitly specified; infer from target learner group and intervention design.

Varies by intervention; not specified unless the paper explicitly describes prerequisites.

• Document the AI education intervention, course, tool, or resource described in the source publication.
• Extract the learner context, AI role, pedagogy, outcomes, and constraints for AAB registry comparison.
• As AI becomes more widely used across a variety of disci- plines, it is increasingly important to teach AI concepts to K- 12 students in order to prepare them for an AI-driven future workforce.

• Support AAB comparison across AI literacy, AI education, teacher training, higher education, and workforce contexts.
• Capture evidence maturity, transferability, and limitations rather than treating the publication as product endorsement.

• Not an AAB endorsement of the tool, curriculum, provider, or result.
• Not a direct replication record unless the source paper reports implementation details sufficient for replication.

AI literacy / AI concepts

Not specified in extracted text

• Learning object / concept model

• Primary interaction pattern inferred from publication: Curriculum / course design, Learning tool / resource design, Teacher professional development, Outreach / informal learning.
• AI capability focus: AI literacy / AI concepts.

• Use age-appropriate framing and teacher/facilitator oversight for any classroom deployment.

• Review the publication’s reported context, learner group, AI tool or curriculum, implementation process, and outcome evidence.
• Map the case to AAB registry fields for comparison across educational levels and AI capability types.
• Use the source publication and PDF for any manual verification before public registry release.

• Human educators/researchers remain responsible for instructional design, supervision, interpretation, and ethical safeguards.
• AI systems or AI concepts provide the learning object, support tool, evaluator, simulator, or automation context depending on the paper.

• Hands-on / experiential learning
• Registry extraction emphasizes explicit learning goals, observed outcomes, constraints, and safety limitations.

• Teacher readiness, time, support, and classroom integration may affect implementation quality.
• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

• Case classified under: Published curriculum / implementation paper.
• Pedagogical pattern: Hands-on / experiential learning.
• Any additional adaptations should be verified against the full paper before public-facing publication.

• Engagement evidence should be interpreted according to the source paper’s reported method and sample.
• In this work, we lay out the proposed content of our curriculum and present the design, development, and implementation results of the first unit of our curriculum that focuses on teaching the breadth-first search algorithm.

• In this work, we lay out the proposed content of our curriculum and present the design, development, and implementation results of the first unit of our curriculum that focuses on teaching the breadth-first search algorithm.

As AI becomes more widely used across a variety of disci- plines, it is increasingly important to teach AI concepts to K- 12 students in order to prepare them for an AI-driven future workforce. Hence, educators and researchers have been work- ing to develop curricula that make these concepts accessible to K-12 students.

• Use age-appropriate framing and teacher/facilitator oversight for any classroom deployment.

• Activity documentation

• Can be used as an AAB evidence record for cross-case comparison, standards drafting, and evidence-maturity mapping.
• Supports identification of recurring patterns in AI literacy, AI education implementation, teacher preparation, assessment, and responsible AI learning.

• Conceptual understanding
• Teacher readiness
• Curriculum / course design
• Learning tool / resource design
• Teacher professional development
• Outreach / informal learning
• AI literacy / AI concepts

• Completed

6-8, Adult / workforce

In-school (K-12), Informal learning, Professional / adult learning

AI literacy / AI concepts

Hands-on / experiential learning

Low to Medium

Medium

Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade Classrooms

• Bita Akram
• Spencer Yoder
• Cansu Tatar
• Sankalp Boorugu
• Ifeoluwa Aderemi
• Shiyan Jiang

Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36 No. 11, EAAI-22

2022

10.1609/aaai.v36i11.21544

https://ojs.aaai.org/index.php/AAAI/article/view/21544

https://ojs.aaai.org/index.php/AAAI/article/view/21544/21293

098_Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade Classrooms.pdf

8

As AI becomes more widely used across a variety of disci- plines, it is increasingly important to teach AI concepts to K- 12 students in order to prepare them for an AI-driven future workforce. Hence, educators and researchers have been work- ing to develop curricula that make these concepts accessible to K-12 students. We are designing and developing a compre- hensive AI curriculum delivered through a series of carefully crafted activities in an adapted Snap! environment for middle- grade students. In this work, we lay out the proposed content of our curriculum and present the design, development, and implementation results of the first unit of our curriculum that focuses on teaching the breadth-first search algorithm. The activities in this unit have been revised after being piloted with a single high-school student. They were further refined after a group of K-12 teachers examined and critiqued them during a two-week professional development workshop. Our teachers created a lesson plan around the activities and im- plemented that lesson in a summer workshop with 14 mid- dle school students. Our results demonstrated that our activ- ities were successful in helping many of the students in un- derstanding and implementing the algorithm through block- based programming while extra supplementary material was needed to assist some other students. In this paper, we explain our curriculum and technology, the results of implementing the first unit of our curriculum in a summer camp, and lessons learned for future developments.

• In-school (K-12)
• Informal learning
• Professional / adult learning

• Teacher readiness, time, support, and classroom integration may affect implementation quality.
• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

Not specified in extracted text unless noted in duration field.

Requires educators/researchers/facilitators with sufficient AI literacy and pedagogy knowledge for the target learners.

Infrastructure depends on AI tool type, learner devices, data access, and institutional policy context.

High

• duration

This entry was automatically extracted from the PDF text and manifest metadata. Fields should be manually verified before public registry publication, especially group size, location, duration, and outcome claims.