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In this paper, we explore the integration of an AI-based Learning Assistant, LLMentor, into a PESTLE (Political, Economic, Social, Technological, Legal, Environmental) case study learning activity. The study was conducted within a Business course at the Escola Politècnica Superior de Vilanova i la Geltrú (EPSEVG), part of the Bachelor’s Degree in Computer Engineering. LLMentor, developed using the LAMB (Learning Assistant Manager and Builder) framework, was utilized to assist students in analyzing a case study involving Tesla’s Optimus robot. The AI tool provided personalized learning support, streamlined information retrieval, and offered expert guidance throughout the activity. The implementation spanned two classroom sessions, facilitating team-based exploration of the PESTLE dimensions and integrating a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. We evaluated the effectiveness of LLMentor through a student survey, which indicated a positive reception towards the AI assistant’s role in enhancing learning efficiency and engagement. Our findings suggest that AI-based learning assistants can significantly enrich the educational experience by fostering deeper understanding and critical analysis skills.

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Using an AI Based Learning Assistant for a PESTLE Case Study Learning Activity

  • 会议论文

  • 发表日期：

    2025年

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  • Maria Jose Casañ,
  • Ariadna Llorens,
  • Marc Alier,
  • Juanan Pereira

摘要

In this paper, we explore the integration of an AI-based Learning Assistant, LLMentor, into a PESTLE (Political, Economic, Social, Technological, Legal, Environmental) case study learning activity. The study was conducted within a Business course at the Escola Politècnica Superior de Vilanova i la Geltrú (EPSEVG), part of the Bachelor’s Degree in Computer Engineering. LLMentor, developed using the LAMB (Learning Assistant Manager and Builder) framework, was utilized to assist students in analyzing a case study involving Tesla’s Optimus robot. The AI tool provided personalized learning support, streamlined information retrieval, and offered expert guidance throughout the activity. The implementation spanned two classroom sessions, facilitating team-based exploration of the PESTLE dimensions and integrating a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. We evaluated the effectiveness of LLMentor through a student survey, which indicated a positive reception towards the AI assistant’s role in enhancing learning efficiency and engagement. Our findings suggest that AI-based learning assistants can significantly enrich the educational experience by fostering deeper understanding and critical analysis skills.