GenAI for feedback design

Expected Outcomes

The case is expected to result in a GenAI-supported tool that is firmly grounded in classroom practices and shaped by teachers’ workflows, assessment strategies, and pedagogical intentions. It will also contribute to the identification and articulation of effective pedagogical practices for feedback design in project-based learning contexts. In addition, the case will generate evidence-based insights into how GenAI-based tools can be co-designed with teachers by meaningfully accounting for their needs, expertise, and professional judgment.

Benefits to the Teachers

Teachers gain support in developing their professional skills for effectively integrating GenAI into their teaching practices and enhancing their feedback literacy. They are also involved as co-creators, actively shaping and refining GenAI-driven educational solutions for instructional design, ensuring the tools reflect their expertise, needs, and real classroom contexts.

Why This Case Matters

Delivering effective formative feedback is cognitively demanding and time-intensive. It requires teachers to carefully balance learning goals, students’ progress, and the specific instructional context. However, many existing GenAI tools are not designed with these realities in mind. They often overlook pedagogical intent, concrete learning objectives, and the professional judgment teachers rely on in daily practice. This GenAI case addresses this gap by focusing on how generative AI can meaningfully support teachers in providing high-quality, context-aware feedback that genuinely enhances teaching and learning.

Role of AI-Based Tools

The GenAI-based tool helps teachers deepen their understanding of instructional design and its connection to learning objectives, project-based assignment difficulty, and student achievement. It supports teachers in considering multiple aspects of feedback, including focus (such as performance, process, or self-regulation), type (for example, hints, cues, or direct correction), timing (immediate or delayed), as well as alignment with course objectives and students’ knowledge levels. Based on this understanding, the tool can propose tailored feedback interventions that vary in focus, type, and timing, enabling more effective and context-aware guidance for learners.

Key Challenges

Key challenges include equipping teachers with the instructional expertise and digital skills needed to collaborate effectively with GenAI in instructional design, especially in the complex and time-intensive task of providing feedback on project-based assignments. Another critical challenge is developing AI systems that are truly grounded in classroom realities, as many existing tools overlook important factors such as instructional context, specific learning objectives, and the professional judgment and practical needs of teachers.