The emergence of generative artificial intelligence (AI) has created legitimate concerns surrounding academic integrity and the ease with which such technologies might lead to cheating in assessment, in particular. However, fixating solely on potential misconduct is overshadowing a more profound, transformative interaction between learners and machines. This commentary article delves into the relationship between students and AI, aiming to highlight the need for revised pedagogical strategies in the AI age. We argue that the much-discussed approaches that prioritise AI literacy or augmented critical thinking might be inadequate. Instead, we contend that a more holistic approach emphasising self-regulated learning (SRL) and co-regulation of learning is needed. SRL promotes autonomy, adaptability, and a deeper understanding, qualities indispensable for navigating the intricacies of AI-enhanced learning environments. Furthermore, we introduce the notion of a network of co-regulation, which underscores the intertwined learning processes between humans and machines. By positioning the self at the core of this network, we emphasise the indispensable role of individual agency in steering productive human-AI educational interactions. Our contention is that by fostering SRL and understanding co-regulated dynamics, educators can better equip learners for an interconnected AI-driven world.
- While concerns about AI's potential for cheating are valid, exploring its transformative potential in enhancing learning experiences is vital.
- Self-regulated learning (SRL) is becoming increasingly crucial. SRL equips students to navigate the complexities of AI-enhanced environments effectively.
- While AI literacy and an emphasis on critical thinking are important, they may not be enough. A more holistic approach to learning with AI is needed.
- Educators should focus on ensuring students not only use AI but also understand, adapt to, and learn collaboratively with it.
- Students are increasingly navigating a complex network, including generative AI that helps them regulate their learning.
Lodge, J. M., de Barba, P., & Broadbent, J. (2023). Learning with Generative Artificial Intelligence Within a Network of Co-Regulation. Journal of University Teaching & Learning Practice, 20(7). https://doi.org/10.53761/1.20.7.02