This workshop explores Human-AI collaboration in ideation within design-based learning, a pedagogical approach widely used in engineering education. With the rise of Generative AI and generative language models (GLMs), new possibilities have emerged to support both divergent and convergent thinking in creative problem-solving. However, while AI agents have shown promise in generating ideas and guiding the ideation process, their integration into educational contexts remains underexplored, particularly from the perspective of educators. Participants engaged in a structured, hands-on exploration of AI-assisted ideation. The workshop began with an introduction followed by an interactive demonstration, where participants experienced an AI-supported ideation activity from a student’s perspective. This was followed by a guided tutorial on implementing AI-generated feedback in a collaborative online environment (Graasp.org), allowing participants to tailor the behavior of the AI agent for their own educational scenario. The final segment consisted of a structured discussion, where participants reflected on the benefits, limitations, and pedagogical implications of AI feedback for ideation, as well as shared their perspectives and expectations regarding human-AI collaboration for ideation activities. By the end of the workshop, participants had firsthand experience designing and integrating AI feedback in ideation activities, and contributed to a collective report capturing educator insights—informing ongoing research and practice at the intersection of AI, design-based learning, and engineering education.