Observatorio IA - uso en educación

10 Ways Technology Leaders Can Step Up and In to the Generative AI Discussion in Higher Ed
Lance Eaton, Stan Waddell EDUCAUSE (03/10/2023)
The use of generative AI tools on campus is an excellent opportunity for technology and other leaders to provide guidance to students, faculty, and staff about how to navigate these new technological waters. In April 2023, we were involved in a panel with students at College Unbound. The conversation —"Generative AI and Higher Education: Disruption, Opportunities, and Challenges"— offered many different highlights, and the students brought rich thoughts, provocative considerations, and smart ideas, reinforcing the fact that discussions around what to do about generative AI (or about anything else, for that matter) are enhanced when students are involved. Toward the end of the panel conversation, Stan asked the students what they thought could be done to help faculty, students, and staff navigate the rise of AI. Essentially, he was curious to hear about the roles that technology and other leaders could fulfill. After thinking about their answers and engaging in further reflection, we came up with ten suggestions for how to step up and in to the generative AI discussion in higher education.
First 100 days of ChatGPT at Australian universities
Samuel Fowler, Malgorzata Korolkiewicz, Rebecca Marrone Learning Letters (13/08/2023)
This article examines the potential impact of large language models (LLMs) on higher education, using the integration of ChatGPT in Australian universities as a case study. Drawing on the experience of the first 100 days of integration, the authors conducted a content analysis of university websites and quotes from spokespeople in the media. Despite the potential benefits of LLMs in transforming teaching and learning, early media coverage has primarily focused on the obstacles to their adoption. The authors argue that the lack of official recommendations for Artificial Intelligence (AI) implementation has further impeded progress. Several recommendations for successful AI integration in higher education are proposed to address these challenges. These include developing a clear AI strategy that aligns with institutional goals, investing in infrastructure and staff training, and establishing guidelines for the ethical and transparent use of AI. The importance of involving all stakeholders in the decision-making process to ensure successful adoption is also stressed. This article offers valuable insights for policymakers and university leaders interested in harnessing the potential of AI to improve the quality of education and enhance the student experience.
New principles on use of AI in education
Russell Group Russell Group (04/07/2023)
A new set of principles has been created to help universities ensure students and staff are ‘AI literate’ so they can capitalise on the opportunities technological breakthroughs provide for teaching and learning. The statement, published today (4 July) and backed by the 24 Vice Chancellors of the Russell Group, will shape institution and course-level work to support the ethical and responsible use of generative AI, new technology and software like ChatGPT. Developed in partnership with AI and educational experts, the new principles recognise the risks and opportunities of generative AI and commit Russell Group universities to helping staff and students become leaders in an increasingly AI-enabled world. The five principles set out in today’s joint statement are: Universities will support students and staff to become AI-literate. Staff should be equipped to support students to use generative AI tools effectively and appropriately in their learning experience. Universities will adapt teaching and assessment to incorporate the ethical use of generative AI and support equal access. Universities will ensure academic rigour and integrity is upheld. Universities will work collaboratively to share best practice as the technology and its application in education evolves.
A comprehensive AI policy education framework for university teaching and learning
Cecilia Ka Yuk Chan International Journal of Educational Technology in Higher Education (07/07/2023)
This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the study proposes an AI Ecological Education Policy Framework to address the multifaceted implications of AI integration in university teaching and learning. This framework is organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension concentrates on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training. The framework fosters a nuanced understanding of the implications of AI integration in academic settings, ensuring that stakeholders are aware of their responsibilities and can take appropriate actions accordingly.
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