AI in Higher Education: Flipping the Paradigm
Two years ago, we had the opportunity to contribute to a book chapter on the integration of artificial intelligence (AI) in management education. Back then, our understanding of AI was limited, and we saw it primarily as a tool to enhance teaching and learning experiences. We believed that AI would be willingly embraced by higher education institutions (HEIs) to promote inclusivity and personalized learning. However, the emergence of generative AI has completely disrupted the landscape of teaching and learning, leading to divided opinions among academics.
The Chronicle of Higher Education recently published an article titled “Caught Off Guard by AI,” which reflects the confusion and skepticism among academics about the role and future of higher education. Academics are desperately seeking clear guidance and practical advice on how to navigate this complex situation, but HEIs themselves are uncertain and often look for external support.
Before delving into our approach to using AI in teaching and learning, we want to clarify that this article was not generated using AI. We maintain an objective perspective and are neither innovators nor laggards. We are simply passionate academics who are dedicated to advancing teaching and learning in our profession.
In recent months, discussions around the use of AI in higher education have largely focused on generative AI, particularly its application in assessment creation. The predominant concerns revolve around academic integrity and the fear of compromising quality assurance. However, AI’s potential in assessment and academic integrity is just a small part of a much larger puzzle.
Traditionally, the purpose of higher education is to foster students’ development of higher-order thinking skills, including knowledge acquisition, sharing, and creation. These skills are grounded in the cognitive processes, ranging from lower-order thinking skills like remembering and understanding, to higher-order skills such as applying, analyzing, evaluating, and ultimately, creating. Bloom’s taxonomy encapsulates these cognitive processes and has influenced the design, teaching, and assessment practices in higher education.
However, our heavy reliance on Bloom’s taxonomy has made it difficult to think beyond its framework when it comes to assessment and teaching design. We have come to view knowledge creation as an outcome of going through these cognitive processes. AI, on the other hand, can generate content across various domains almost instantly, without the need for cognitive processing. It’s like bypassing multiple levels in a video game. This raises the question of how we can leverage this insight to evolve our understanding of learning and assessment design to incorporate new technologies.
The disruption caused by generative AI presents an opportunity for change. Imagine Bloom’s taxonomy as a pyramid, broad at the base (remembering) and tapering towards the pinnacle (creating). However, when we integrate generative AI into teaching, learning, and assessment, the pyramid flips. Instant creation of knowledge becomes accessible to all with a simple prompt, while remembering becomes a higher-order skill that involves evaluating, analyzing, and applying the information created by AI.
In light of this, we propose flipping our approach and starting with creation when integrating generative AI in teaching and learning. AI becomes a learning partner and co-creator that accelerates insights. For instance, students could use AI tools like ChatGPT to create a business model for a new entrepreneurial venture. They can then evaluate and analyze the model using various tools explored throughout the module. The outcomes of the evaluation and analysis can be applied to consider sustainable business strategies. Finally, in-person assessments such as presentations or reflective debates can assess students’ understanding and remembering.
It’s crucial to remember that AI is a tool created by humans. The quality of the output depends on what we input. As creators and disseminators of knowledge, we have a responsibility to ethically and effectively utilize digital tools like generative AI to benefit our profession and society in the long run.
Christine Rivers, a professor at Surrey Business School, University of Surrey, focuses on mindfulness in business education and the responsible use of AI to address challenges. Anna Holland, an associate professor and director of learning and teaching at Surrey Business School, University of Surrey, explores the integration of generative AI in learning, teaching, and student experience.
Editor Notes:
AI’s rapid advancement presents both opportunities and challenges in higher education. As academics navigate this changing landscape, it’s essential to embrace AI as a tool for innovation and improvement. The key lies in understanding how to effectively integrate AI into teaching, learning, and assessment practices while upholding academic integrity. By flipping our approach and starting with creation, we empower students to harness the potential of AI to accelerate insights and drive future success.
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**Opinion Piece – Editor Notes**
The integration of artificial intelligence (AI) has undoubtedly disrupted higher education, leaving many academics confused and skeptical about its role and impact. In this article, Christine Rivers and Anna Holland shed light on the potential of generative AI and propose a paradigm shift in teaching and learning practices. They advocate for starting with creation instead of relying solely on traditional cognitive processes, arguing that AI can serve as a co-creator and accelerate learning insights. As the HE community grapples with the challenges and opportunities presented by AI, it’s crucial to embrace innovation while upholding academic rigor. The responsibility lies with educators to harness the power of AI ethically and responsibly, ensuring its long-term benefit for our profession and society.
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