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Subject: search.filters.subject.Generative artificial intelligence

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    Integrating Generative AI into Live Case Studies for Experiential Learning in Operations Management
    (MDPI AG, 2025)
    Salinas-Navarro, David Ernesto  
    ;
    Vilalta-Perdomo, Eliseo
    ;
    Palma-Mendoza, Jaime Alberto
    ;
    Carlos-Arroyo, Martina
    This research-to-practice study examines how Generative Artificial Intelligence (GenAI) can be integrated into live case studies to enhance experiential learning in higher education. It explores GenAI’s potential as an agent to learn with scaffolding reflection and engagement and addresses gaps in existing applications that often focus narrowly on content generation. To explore GenAI’s agentive potential, the methodology illustrates this approach in a UK postgraduate operations management module. Students engaged in a live case study of a local ethnic restaurant to refine its business model and operations. The data sources used to examine students’ results included module materials, outputs, and feedback surveys. Thematic analysis was employed to assess how GenAI facilitated experiential learning. The findings suggest that GenAI integration facilitated exploration, reflection, conceptualisation, and experimentation. Students reported that the activity was engaging and relevant, facilitating critical decision-making and understanding of operations management. However, the outcomes varied according to GenAI literacy and student participation. Although GenAI-enriched learning is beneficial, human agency and contextual knowledge remain crucial. Overall, this study integrates GenAI as a cognitive partner throughout Kolb’s ELC. This study offers a transferable framework for active learning, illustrating how technology can enhance critical and reflective learning in authentic educational contexts. However, limitations include uneven student participation and engagement, resource constraints, overreliance on artificial intelligence outputs, differentiated impact on learning outcomes, and a single-case report, which must be addressed before the framework can be scaled up. Future research should test this through multi-case studies while developing GenAI literacy, measuring GenAI impact, and implementing ethical practices in the field. ©Los autores ©MDPI.
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    Challenging human creativity: an exercise of co-creation with generative artificial intelligence
    (Vilnius Gediminas Technical University, 2025)
    Flores Heymann, Bernardo
    ;
    Briedis, Mindaugas  
    This paper explores the collaborative potential between humans and generative artificial intelligence in creative contexts through a co-creation framework. The study uses ChatGPT to develop narrative elements such as slogans, taglines, and claims for university marketing programs, comparing human-generated and artificial intelligence-generated content to evaluate effectiveness and engagement. Results indicate that while artificial intelligence can contribute useful and creative content, human participants still prefer human-generated narratives in many instances. The study also highlights how generative artificial intelligence can enhance creative processes by accelerating ideation and reducing cognitive load, but it raises concerns regarding the originality and diversity of artificial intelligence-generated content. This research provides insights into the integration of artificial intelligence in collaborative creative work and suggests best practices for leveraging artificial intelligence tools in marketing and communication strategies. ©The authors ©Vilnius Gediminas Technical University.
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    Empowering Nanostores for Competitiveness and Sustainable Communities in Emerging Countries: A Generative Artificial Intelligence Strategy Ideation Process
    (MDPI, 2024)
    Salinas-Navarro, David Ernesto  
    ;
    Vilalta-Perdomo, Eliseo
    ;
    Michel-Villarreal, Rosario
    This exploratory study investigates Generative Artificial Intelligence’s (GenAI) use in strategy ideation for nanostores—i.e., small independent grocery retailers—to enhance their competitiveness while contributing to community sustainability. Nanostores, particularly in emerging countries, face intense competition and rapidly changing trends. These stores adopt various strategies by leveraging their proximity to consumers in neighbourhoods, resulting in different business configurations. While the existing literature highlights the broader nanostores’ functions, there is limited research on how they may develop comprehensive strategies to face their challenges. By employing a thing ethnography methodology, this work proposes GenAI thing interviewing—i.e., with ChatGPT 3.5 and Microsoft Copilot—through incremental prompting to explore potential strategy ideation and practices. Key findings suggest GenAI conversations can aid shopkeepers in strategy ideation through human-like written language, aligning with small business dynamics and structures. This proposition results in a GenAI ideation framework for strategy generation and definition. Moreover, this technology can enhance nanostore competitiveness and sustainability impact by enacting improved strategy practices in stakeholder engagements. Accordingly, this work’s main contribution underscores a GenAI-enabled conversational approach to facilitate nanostores’ strategy ideation and embedding in everyday business operations. Future work must address the limitations and further investigate GenAI’s influence on human understanding and technological creation, strategy ideation, adoption, and usability in nanostores. ©The authors ©MDPI
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    Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT
    (MDPI, 2023)
    Michel-Villarreal, Rosario
    ;
    Vilalta-Perdomo, Eliseo
    ;
    Salinas-Navarro, David Ernesto  
    ;
    Thierry-Aguilera, Ricardo
    ;
    Gerardou, Flor
    ChatGPT is revolutionizing the field of higher education by leveraging deep learning models to generate human-like content. However, its integration into academic settings raises concerns regarding academic integrity, plagiarism detection, and the potential impact on critical thinking skills. This article presents a study that adopts a thing ethnography approach to understand ChatGPT’s perspective on the challenges and opportunities it represents for higher education. The research explores the potential benefits and limitations of ChatGPT, as well as mitigation strategies for addressing the identified challenges. Findings emphasize the urgent need for clear policies, guidelines, and frameworks to responsibly integrate ChatGPT in higher education. It also highlights the need for empirical research to understand user experiences and perceptions. The findings provide insights that can guide future research efforts in understanding the implications of ChatGPT and similar Artificial Intelligence (AI) systems in higher education. The study concludes by highlighting the importance of thing ethnography as an innovative approach for engaging with intelligent AI systems and calls for further research to explore best practices and strategies in utilizing Generative AI for educational purposes. ©The authors.
    Scopus© Citations 195  32