DeepSeek R1 as an AI Simulation in ESP Classes for Enhancing Negotiation Soft Skills in Moroccan Higher Education
DOI :
https://doi.org/10.60590/PRSM.itec-iss10.176Mots-clés :
DeepSeek R1, AIED, AI Negotiation, Human-Agent NegotiationRésumé
This article comes to play into the context of ESP by integrating DeepSeek R1 for teaching negotiation skills for Master students of legal conflicts and political sciences at Ibn Tofail university, Morocco. The experiment lasted for four weeks through four sessions where 30 students formed randomly five groups of 6 students. For data collection, a survey research and two reflection tasks were given to the groups for evaluating the agent. The findings show that the participants considered legal negotiation language, negotiation strategies, communication skills, and teamwork/group cooperation to be their most improved soft skills with other practice capabilities. Most of the participants declared that negotiation simulations with the agent reflected real contexts with flexibility, creativity, and instant feedback. Also, the most participants shared positive attitudes towards DSR1 and gave suggestions for more developments. The integration of such AI pedagogy in Moroccan higher education will surely provide opportunities for developing negotiation skills.
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(c) Tous droits réservés Innovation, Technologies, Education et Communication 2025

Ce travail est disponible sous licence Creative Commons Attribution - Pas d’Utilisation Commerciale 4.0 International.
