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Join us for an inspiring and thought-provoking conversation with Dr. Jennifer McBride, one of only two Academic Excellence and Teaching Excellence Leads at the University of Manchester. In this episode, we learn about her journey into academia, her groundbreaking research in cognitive psychology, and her innovative approaches to teaching and student engagement. From exploring the complexities of attention and memory to pioneering new methods for enhancing the learning experience, Dr. McBride shares fascinating insights and practical applications that bridge the gap between science and education. Whether you're passionate about psychology, curious about cutting-edge teaching methods, or just love learning, this episode is packed with wisdom and inspiration. Don't forget to like, comment, and subscribe for more engaging discussions with incredible minds! Chapters 0:00 Introduction & overview of Jennifer’s work 0:43 Origin story – path into academia 1:32 Discovering psychology and choosing a degree 2:43 First taste of research and deciding on a PhD 3:35 PhD focus – context effects in visual search 5:35 Post-PhD shift to action control and affordances 7:02 Neuropsychological patients and utilisation behaviour 9:51 Inhibition versus action selection and free-will questions 11:06 Making cognitive science visual in teaching 12:43 Applying cognition to a teaching-excellence leadership role 15:01 Explaining the Teaching Excellence Framework (TEF) 18:07 “Assessment for the Future” university initiative 19:45 Equity, awarding gaps and supporting diverse students 24:29 Scalable teaching tactics – discussion boards & large classes 27:06 Pandemic “watch-party” lectures and live chat innovation 32:15 Research evidence for chat-box learning gains 38:11 Other universities’ watch-party experiences and replication 41:45 Parallel scientific discoveries and the nature of truth 49:59 Active self-feedback, marking schemes and generative AI 57:01 Is psychology a mature science? 1:05:56 AI tools versus brain-inspired models 1:09:00 Practical uses of attention research (radiology, aviation, teaching) 1:14:11 Convolutional neural networks and human vision parallels 1:20:10 Differentiating AI tools from cognitive models; closing remarks