Jacqueline Rohde
Papers
1
Total Citations
2
H-Index
1
About
Dr. Jacqueline Rohde is a rising leader in engineering education research, with a focused expertise on the integration of artificial intelligence into technical pedagogy. Her work critically examines how large language models (LLMs) can be leveraged to transform assessment and learning in engineering disciplines, particularly in circuit analysis. Her most cited work, "Benchmarking Large Language Models on Homework Assessment in Circuit Analysis" (2025), provides a foundational framework for evaluating the capabilities and limitations of LLMs in grading and providing feedback on complex, problem-based homework. This contribution is pivotal for educators seeking to responsibly adopt AI tools without compromising academic rigor. By systematically testing LLMs against real student work, Rohde’s research directly addresses the practical challenges of automated assessment, offering evidence-based insights that bridge the gap between cutting-edge AI and classroom application. With her work already garnering attention in the nascent field of AI-assisted education, Dr. Rohde is establishing herself as a key voice in shaping how future engineers are trained, ensuring that technology enhances rather than replaces meaningful learning experiences.
Research Focus
Key Achievements
Top Papers
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