2025 ASEE Annual Conference & Exposition

In competitive high school robotics, mainly the For Inspiration and Recognition of Science and Technology (FIRST) Robotics Competition (FRC), learning and teaching robot design to a competitive level is a significant struggle for students and educators alike. A significant amount of domain-specific declarative and conditional knowledge and industry-equivalent proficiency levels in computer-aided Design (CAD) software are required to be able to design a highly competitive robot within the tight 1-2 week timeframe. This creates a large accessibility gap for exploring CAD, with many students choosing not to begin to learn due to the difficulty of learning.

The nature of the competition for high schoolers means that students have a short period to build these skills before graduating. As a result, the learning process must be optimized to master domain-specific knowledge and CAD skills efficiently and in much greater depth than is currently taught in a typical classroom setting.

We recently released and are continuing to develop a free, open-source learning course for Competitive Robotics called FRCDesign.org. This work is based on current engineering and learning research. By keeping it accessible, we can lower the barriers to entry while allowing for an extensive research pool. With over 6k users in the first month of its release, FRCDesign.org has become the primary resource for learning and teaching robot design and CAD for FIRST Robotics Competition teams. There is an improvement in the quality of life and learning efficiency for teams compared to previous methods. In some instances, students have, within a single month, achieved a level of mastery in CAD skills equivalent to what would have previously taken 2-3 years.

Utilizing generative learning, we balance the cognitive load by introducing declarative and procedural concepts by utilizing short projects related to robot design. Students quickly master CAD software and robot design by building the concepts on top of one another, while the application-focused methods maintain relevance and engagement. The activities are structured to keep students in the upper levels of Bloom’s Taxonomy without feeling overwhelmed. As students progress, increased self-regulation is required to identify weaknesses and maintain fast improvement. We test a rigorous self-review system and improvement format based on Kolb’s experimental learning theory to help support this, combined with self-recording and video review to help students self-identify their weaknesses.
For educators, we utilize a modified flipped classroom model while encouraging similar self-paced learning. The individual learner and educator models are tested on students of varying backgrounds and self-motivation levels, with mastery over time and sustained interest in CAD as the key metrics to evaluate the strengths and weaknesses of the two models.

We present the learning efficiency results and methods for developing the learning curriculum in addition to discoveries as we iterate and continue development. We will present data based on a combination of closely followed individual case studies and broader survey responses from users of varying resource and knowledge levels.