Tejpaul, R., & Henderson, T., & Kennedy, N., & Papanikolopoulos, N. (2025, June), Using Generative AI to Improve the Research Experience of MS Students in Robotics    Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--57304

\bibitem{asee_peer_57304}
  Tejpaul, R., \& Henderson, T., \& Kennedy, N., \& Papanikolopoulos, N. (2025, June), \emph{Using Generative AI to Improve the Research Experience of MS Students in Robotics  }
  Paper presented at 2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada .
  10.18260/1-2--57304

Resha Tejpaul, Travis Henderson, Nicole Kennedy, and Nikos Papanikolopoulos.  "Using Generative AI to Improve the Research Experience of MS Students in Robotics  ".  2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada , 2025, June.  ASEE Conferences, 2025.  https://peer.asee.org/57304 Internet.  28 Aug, 2025

\bibitem{asee_peer_57304}
  Resha Tejpaul, Travis Henderson, Nicole Kennedy, and Nikos Papanikolopoulos.
  "Using Generative AI to Improve the Research Experience of MS Students in Robotics  ".
  \emph{2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada , 2025, June}.
  ASEE Conferences, 2025.
  https://peer.asee.org/57304 Internet.  28 Aug, 2025

@INPROCEEDINGS{asee_peer_57304
author = "Resha Tejpaul, Travis Henderson, Nicole Kennedy, and Nikos Papanikolopoulos"
title = "Using Generative AI to Improve the Research Experience of MS Students in Robotics  "
booktitle = "2025 ASEE Annual Conference \& Exposition "
year = "2025"
month = "June"
address = "Montreal, Quebec, Canada "
publisher = "ASEE Conferences"
note = {https://peer.asee.org/57304}
number = {10.18260/1-2--57304}
}

TY  - CPAPER
AB  - The Minnesota Robotic Institute at the University of Minnesota Master’s program in Robotics located in the United States prepares students for professional careers focused on research and innovation within both academic and industrial sectors. The curriculum prioritizes applied learning methodologies through research initiatives and problem-solving exercises, thereby enabling students to customize elective courses in accordance with their personal interests. Each participant is required to complete either a capstone project or a research thesis. The program, which spans three semesters, commences with rigorous coursework and culminates in a comprehensive final project. Students opting for a thesis engage in advanced research endeavors, while those fulfilling the capstone requirements exercise considerable autonomy in the design and dissemination of their projects. The increasing attraction of this experiential, student-centered model has resulted in a rise in enrollment, thereby presenting challenges in maintaining personalized faculty oversight. In response to these developments, the program has investigated the application of various Generative AI (GenAI) tools to enhance student learning experiences. This study analyzes survey responses collected from 19 Master of Science students in robotics program, elucidating the prevalent use of Generative AI tools, particularly ChatGPT, for tasks involving coding and writing. Additionally, it highlights significant ethical considerations, including the spread of misinformation and the lack of established usage guidelines. Many of the respondents support the incorporation of Generative AI into the curriculum, provided that clear limitations are set. They emphasize the need for formal training and updates to the academic curriculum to effectively leverage the benefits of such technologies while minimizing associated risks.
AU  - Resha Tejpaul
AU  - Travis Henderson
AU  - Nicole Kennedy
AU  - Nikos Papanikolopoulos
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - Using Generative AI to Improve the Research Experience of MS Students in Robotics  
UR  - https://peer.asee.org/57304
DO  - 10.18260/1-2--57304
ER  -