2024 ASEE Annual Conference & Exposition

Iterative Learning: Using AI-Bots in Negotiation Training

Presented at Engineering Management Division (EMD) Technical Session 2

SUBMISSION TYPE: PRACTICE PAPER / WIP

Negotiation skills are essential in management education and in engineering practice. Traditional teaching paradigms, centered around role-playing activities, often meet challenges, especially when students are unprepared or unable to simulate their roles authentically.

To addressing this pedagogical gap, I developed "AdVentures with chatGPT." In this two-round negotiation exercise, students assume the roles of job candidates, negotiating terms with an AI-bot recruiter. The AI facilitates the first negotiation round, providing students immediate, objective feedback upon completion. Students reflect on their performance, identify improvements and strategies, before re-engaging in the second negotiation round with the AI.

In a pilot study, there was an average improvement of 10% in student performance. Further research is needed to confirm this finding. However, based on these early results, the use of AI is promising for teaching students to create and claim value in negotiation. This AI-enabled, iterative approach contributes to the pedagogical toolbox in engineering management education, offering a technologically advanced, scalable solution to negotiation training.

Authors
  1. Dr. Renee Rottner University of California, Santa Barbara [biography]
Download paper (2.14 MB)

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