LEGO Robot Vehicle Afterschool Workshops: Transportation Engineering Problem Solving (Year 1 & 2)
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Summary
This report evaluates a two-year workforce development initiative (2012–2013) designed to introduce middle school students to transportation engineering and increase their awareness of Science, Technology, Engineering, and Math (STEM) careers. Motivated by projected growth in civil engineering jobs and the need to recruit young people into the field, the project utilized LEGO® Mindstorms NXT robots to demonstrate how Intelligent Transportation Systems (ITS) and advanced technologies mitigate traffic congestion. The study aimed to connect abstract STEM concepts to real-world transportation problems, such as recurrent congestion and signal optimization, thereby fostering interest in engineering as a viable career path. The research was conducted by the Center for Transportation and the Environment at North Carolina State University in collaboration with the University of Florida. In Year 1, a three-day, six-hour afterschool workshop was delivered to eleven academically gifted students at Centennial Campus Magnet Middle School. Students worked in teams to program robot vehicles using educational software, applying logic and mathematics to simulate congestion mitigation scenarios. In Year 2, the program expanded to include 134 students at Robbinsville High School in an economically distressed region, offering nine sessions covering calculus, physics, and highway design alongside robotics. Data collection involved pre- and post-course tests rated on a five-point Likert scale, open-ended questions, and observational assessments of student engagement and problem-solving behaviors. Findings indicated significant improvements in student knowledge and attitudes. Responses to the statement “I can program a LEGO Mindstorm Robot” increased by 55% in Year 1 and 52% in Year 2. Understanding of transportation engineering roles also rose, with a 41% increase in Year 1 and 30% in Year 2. While interest in math and science remained relatively stable, students reported that the course helped them understand the application of STEM to technology. Qualitative data revealed that students gained a clearer definition of engineering as problem-solving and expressed enthusiasm for the hands-on robotics components. Observations noted that students developed confidence, utilized teamwork to debug programs, and often exceeded tutorial requirements. The expanded Year 2 outreach successfully engaged students in a region with limited engineering mentorship resources. The study concludes that LEGO® robot vehicle workshops are an effective tool for introducing middle school students to transportation engineering and enhancing STEM awareness. The hands-on nature of the curriculum allowed students to relate technical concepts to societal issues like traffic congestion, making the subject matter accessible and engaging. The authors recommend maintaining the condensed workshop format, as it sustained student interest without causing fatigue, and emphasize the value of having transportation engineers present initial overviews to contextualize the technical lessons. The project demonstrates that integrating robotics with transportation engineering concepts can successfully recruit youth into STEM fields, particularly in underserved areas.
Key finding
Participants showed a 55% increase in Year 1 and a 52% increase in Year 2 in their ability to program a LEGO Mindstorm robot, alongside improved understanding of transportation engineering and STEM applications.
Methodology
mixed_methods
Sample size: 145
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 24 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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