Zheng Feei Ma is a Senior Lecturer in Public Health, SSHSW, College of Health, Science and Society. He specialises in advancing learning and teaching by applying evidence-based approaches to curriculum design, assessment, and student support.
Introduction
The use of generative artificial intelligence (AI) in higher education is now not only the subject of study, but it is also a pedagogical tool for reshaping how we teach, learn and assess. In addition, the use of AI tools such as ChatGPT and Copilot has intensified the debates about student learning, academic integrity and the role of teachers in classrooms. Therefore, in this article, I will draw on some of my initial experiences of integrating AI into teaching and learning, while highlighting the challenges, opportunities and strategies to guide the responsible use of AI in classrooms.
Rethinking about student learning
One of the important factors in the success of student educational processes is student engagement. The use of AI tools such as AI chatbots and Copilot helps to provide timely feedback and personalised learning experience to students. In Blackboard Ultra, the use of the AI Conversation tool facilitates deeper learning in students through interactive dialogues. In addition, the AI Conversation tool can be used to create AI-driven conversations around discipline-related scenarios such as Socratic questioning and role-playing to engage students in reflective learning and critical thinking.
On the other hand, it is important to teach students about AI literacy and the responsible use of AI. Students need to develop the skills to critically and ethically evaluate AI-generated responses.
Implications for assessment
The use of AI tools has raised concerns about the effectiveness of using written assignments to assess student academic performance. In discussion with colleagues, some suggested the need to redesign assessment with an emphasis on oral presentations, written examinations or authentic assessments linked to real-world case studies. Others continue to use written assignments but with a greater emphasis on the critical integration of literature sources and personal reflection to specific contexts that AI tools cannot easily replicate.
In conversations with students, their feedback highlighted that they wanted to have clear guidance on what is acceptable use of AI and what is academic misconduct. One suggestion was to co-create the assessment rubrics with students. Teachers can then explicitly acknowledge where AI may or may not be used in students’ works. The co-creation process also helps to build trust, consistency and transparency among students, and between students and teachers, which students value the most.
Towards a pedagogy of critical AI engagement
International students for whom English is not their first language can benefit from AI-assisted translation. Through ongoing discussions with colleagues across different disciplines both inside and outside UWE, we have seen that when AI is used as a scaffold, it creates opportunities for inclusive teaching, which supports students with diverse learning needs. Since not all students have equal familiarity with AI, teachers need to create structured opportunities in classrooms for students to explore AI. Therefore, during this educational process, the roles of teachers have started to shift from transmitters of knowledge to facilitators of critical engagements.
Thoughts for the future
Taken together, teaching with AI is more about cultivating new pedagogical mindsets, especially on how to embed AI into existing curriculum structures to critical thinking and inclusivity. For example, we use the AI Conversation tool in Blackboard Ultra to model public health workplace scenarios, bridging academic study with professional practice. Also, in practice, students can give one another qualitative feedback on their works by using the Qualitative Peer Review for assignments in the Blackboard Ultra course view. When they compare the human judgement feedback from their peers with AI-generated feedback, students are able to critically evaluate the differences between these two feedback outputs and reflect on the unique value of human judgement alongside with AI-generated feedback. Therefore, the introduction of AI in higher education is a catalyst and part of a longer trajectory of educational technological changes that constantly reshape teaching, learning and assessment strategies. We as the educators should continue to focus on developing higher-order skills in students that AI cannot fully substitute.
References
- Al-Mughairi H, Bhaskar P (2024) Exploring the factors affecting the affecting the adoption AI techniques in higher education: insights from teachers’ perspectives on ChatGPT. Journal of Research in Innovative Teaching & Learning. https://doi.org/10.1108/JRIT-09-2023-0129
- Ma ZF, Hill A (2024) Four steps for integrating generative AI in learning and teaching. Times Higher Education (THE) Campus. https://www.timeshighereducation.com/campus/four-steps-integrating-generative-ai-learning-and-teaching