# Co-designing Large Language Model Tools for Project-Based Learning with K12 Educators

arXiv: https://arxiv.org/abs/2502.09799 · HTML: https://mlsanity.com/paper/2502.09799/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 144 references that are in the map.
- First posted on arXiv 13 Feb 2025.

## Builds on (most cited first, 13 of 13)

- [Questioning the AI: Informing Design Practices for Explainable AI User Experiences](https://mlsanity.com/paper/2001.02478/) (2020)
- [Design Principles for Generative AI Applications](https://mlsanity.com/paper/2401.14484/) (2024)
- [AI-Augmented Brainwriting: Investigating the use of LLMs in group ideation](https://mlsanity.com/paper/2402.14978/) (2024)
- [Bias of AI-Generated Content: An Examination of News Produced by Large Language Models](https://mlsanity.com/paper/2309.09825/) (2023)
- [Towards LLM-based Autograding for Short Textual Answers](https://mlsanity.com/paper/2309.11508/) (2023)
- [Engaging Teachers to Co-Design Integrated AI Curriculum for K-12 Classrooms](https://mlsanity.com/paper/2009.11100/) (2020)
- [The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?](https://mlsanity.com/paper/2305.02878/) (2023)
- [Generative AI in the Wild: Prospects, Challenges, and Strategies](https://mlsanity.com/paper/2404.04101/) (2024)
- [Human-Centred Learning Analytics and AI in Education: a Systematic Literature Review](https://mlsanity.com/paper/2312.12751/) (2023)
- [Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Students](https://mlsanity.com/paper/2401.14915/) (2024)
- [Engaged and Affective Virtual Agents: Their Impact on Social Presence, Trustworthiness, and Decision-Making in the Group Discussion](https://mlsanity.com/paper/2308.10385/) (2023)
- [Designing Child-Centric AI Learning Environments: Insights from LLM-Enhanced Creative Project-Based Learning](https://mlsanity.com/paper/2403.16159/) (2024)
- [AI Audit: A Card Game to Reflect on Everyday AI Systems](https://mlsanity.com/paper/2305.17910/) (2023)

## Built on by (most cited first, 5 of 5)

- [Exploring Teacher-Chatbot Interaction and Affect in Block-Based Programming](https://mlsanity.com/paper/2603.20211/) (2026)
- [Beyond Text: Probing K-12 Educators' Perspectives and Ideas for Learning Opportunities Leveraging Multimodal Large Language Models](https://mlsanity.com/paper/2507.20720/) (2025)
- [AI Meets Mathematics Education: A Case Study on Supporting an Instructor in a Large Mathematics Class with Context-Aware AI](https://mlsanity.com/paper/2603.26679/) (2026)
- [Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education](https://mlsanity.com/paper/2604.07253/) (2026)
- [Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers](https://mlsanity.com/paper/2604.27231/) (2026)

## Abstract (arXiv)

The emergence of generative AI, particularly large language models (LLMs), has opened the door for student-centered and active learning methods like project-based learning (PBL). However, PBL poses practical implementation challenges for educators around project design and management, assessment, and balancing student guidance with student autonomy. The following research documents a co-design process with interdisciplinary K-12 teachers to explore and address the current PBL challenges they face. Through teacher-driven interviews, collaborative workshops, and iterative design of wireframes, we gathered evidence for ways LLMs can support teachers in implementing high-quality PBL pedagogy by automating routine tasks and enhancing personalized learning. Teachers in the study advocated for supporting their professional growth and augmenting their current roles without replacing them. They also identified affordances and challenges around classroom integration, including resource requirements and constraints, ethical concerns, and potential immediate and long-term impacts. Drawing on these, we propose design guidelines for future deployment of LLM tools in PBL.