The Future of Learning: Generative AI’s Impact on International Business Education
In November 2022, OpenAI publicly released ChatGPT, a chatbot that responds to written prompts and questions and delivers human-like responses. Since the release of ChatGPT and other forms of generative AI (text- and image-based), faculty and leaders at institutions of higher learning across the world have attempted to deal with the consequences of the tools. Responses have ranged from pretending that the problem does not exist to outright bans on the tools to more nuanced approaches that designate acceptable and unacceptable uses of generative AI. Considering the tools’ affordances and the downsides (biases and incorrect information in responses, inappropriate uses), it is clear that faculty and administrators in colleges and schools of business are having to address a number of short-, medium, and long-term issues related to: curriculum; academic integrity and misconduct; students’ learning competencies; assurance of learning; and digital literacy of faculty (Chaudry et al., 2023; Crawford et al., 2023; Lim et al., 2023). Accordingly, this special issue aims to investigate both the role and the impact generative artificial intelligence, a bundle of AI-based technologies ranging from machine learning to deep learning able to create new information adopting a probabilistic logic in an unsupervised learning environment, may have in an International Business Education (IBE) domain. Indeed, while previous IBE literature focused on digital platforms role in shaping effective virtual learning ecosystems (Upson & Bergiel, 2022), in capturing cultural nuances in curricula design (Pimpa, 2011; Henríquez Parodi & Alon, 2019), in pushing students’ performance (Aviles and Eastman, 2012) or engagement in online learning environments (Endress et al., 2023; Alstete, 2023), there is a lack of a comprehensive scholarly work to delve into the nuanced opportunities and pitfalls that the adoption of generative AI may imply for business education scholars and leaders on both the social and ethical side. To give an example, social issues such as students’ accessibility and digital divide and ethical issues related to limits in human-AI interaction for teaching and learning are until now underinvestigated. This opens a wide space of contribution, also considering the inherently relational and innovation-driven nature of IBE. This special issue aims to contribute to this underexplored field as follows:
- It would open to a debate on the social and ethical issues generative AI poses for education in an international business setting;
- It would deepen both methods and impacts of generative AI tools on learning outcomes also for international underserved communities
List of topic areas
- Institutional frameworks for using Generative AI in IBE;
- Use of Generative AI tools to support learners, including use cases such as: (including students and faculty) self-paced learning of skills/competencies, simulations/games, collaborative tools/personal learning assistant, conducting research;
- Generative AI and assessment of learning in IBE, including traditional and experiential learning;
- Ethical and equity issues in using Generative AI in IBE;
- Positive societal impacts of Generative AI in IBE, such as facilitating cultural exchange, intercultural sensitivity, supporting international students to adjusts to the learning and local cultural environment;
- Socio-ethical implications of Generative AI in IBE;
- Pedagogical boundaries of AI in Education;
- AI literacy requirements in IBE;
- Reliability of AI-generated knowledge in IBE;
- Imparting global business competencies via AI;
- Impact of Generative AI on learning outcomes in IBE;
- Case studies on Generative AI in IBE;
- Future trajectories of AI in IBE;
- Integrating cultural nuances with AI in IBE.
Antonio La Sala,
Sapienza University of Rome, Italy
Ryan P. Fuller,
California State University, Sacramento, USA
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