Transformative Deep Learning Pedagogy
Apply neuroscience and cognitive psychology to optimize learning: design brain-based teaching strategies using educational theory and neural mechanisms.
Apply neuroscience and cognitive psychology to optimize learning: design brain-based teaching strategies using educational theory and neural mechanisms.
This comprehensive education course empowers educators and education leaders with cutting-edge approaches to deep learning. Combining insights from cognitive psychology, contemporary educational theories, and neuroscience, the course equips participants with powerful teaching strategies that foster creative, connected, and collaborative problem-solving abilities in students. Participants learn to cultivate independent thinking, innovation, and effective communication while leveraging digital technologies to enhance learning outcomes. The course emphasizes practical implementation of deep learning principles, offering differentiated learning experiences for both individual educators and organizational leaders. Developed as part of Microsoft's K-12 Education Leadership initiative, it provides valuable resources for adapting to evolving educational landscapes and technology integration.
Instructors:
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What you'll learn
Understand the fundamental differences between surface and deep learning
Apply neuroscientific and psychological principles to enhance teaching practices
Develop effective communication strategies for deeper student engagement
Implement motivation techniques that foster positive learning relationships
Design and deliver impactful feedback mechanisms
Integrate technology thoughtfully into educational practices
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 4 modules in this course
This course provides a comprehensive exploration of deep learning in education, integrating research from cognitive psychology, educational theories, and neuroscience. It covers essential aspects of effective teaching and learning, including surface versus deep learning concepts, communication skills, student motivation, and feedback mechanisms. The course emphasizes practical application, offering participants concrete strategies to implement deep learning practices in their educational settings. Special attention is given to technology integration and leadership perspectives, making it valuable for both individual educators and organizational leaders.
Surface to deep learning
Module 1 · 3 Hours to complete
Communication skills - verbal and nonverbal
Module 2 · 3 Hours to complete
Motivating students
Module 3 · 3 Hours to complete
Feedback
Module 4 · 3 Hours to complete
Fee Structure
Instructors
Distinguished Leader in Mathematics Education and STEM Research
Merrilyn Goos serves as Professor of Education at the University of the Sunshine Coast in Australia, following her role as Professor of STEM Education and Director of EPI*STEM at the University of Limerick from 2017-2020. Her career began as a food technologist before transitioning to teaching mathematics, chemistry, and food science in secondary schools and technical colleges in Australia. Her research portfolio spans crucial areas including students' mathematical thinking, digital technologies in mathematics education, interdisciplinary mathematics learning, professional development of mathematics teachers, curriculum reform, and gender equity in STEM education. As Editor-in-Chief of Educational Studies in Mathematics and founding co-Editor-in-Chief of Research in Integrated STEM Education, she has shaped scholarly discourse in mathematics education. Her leadership extends to serving as Vice-President of the International Commission on Mathematical Instruction and former President of the Mathematics Education Research Group of Australasia. In 2022, she received MERGA's Career Research Medal for sustained achievement in mathematics education. Her work has garnered significant research funding from various sources, including the Australian Research Council, EU Horizon 2020, and Science Foundation Ireland. She has also made substantial contributions to education policy, serving as Chair of Queensland's Mathematics Syllabus Advisory Committee and participating in the OECD's Strategic Advisory Group for the PISA 2021 Mathematics framework.
Pioneer in Neural Circuit Research and Learning Science
Pankaj Sah stands as a distinguished neuroscientist serving as Director of the Queensland Brain Institute at The University of Queensland. His academic journey began with medical training at The University of New South Wales, followed by a Ph.D. from the Australian National University and postdoctoral work at the University of California, San Francisco. His groundbreaking research focuses on understanding neural circuits underlying learning and memory formation, particularly in the amygdala and hippocampus. After establishing his laboratory at the University of Newcastle in 1994 and working at the John Curtin School of Medical Research, he joined QBI as a founding member in 2003 and became Director in 2015. Sah's laboratory employs sophisticated techniques including molecular tools, electrophysiology, anatomical reconstruction, calcium imaging, and behavioral studies to examine brain function and disease impacts. His pioneering work has revolutionized understanding of synaptic plasticity and interneuron function in the amygdala, contributing significantly to anxiety disorder research. As Editor-in-Chief of npj Science of Learning, he bridges the gap between neuroscience, psychology, and education research. His contributions include over 110 peer-reviewed publications and recent work with patients undergoing deep brain stimulation for conditions like Parkinson's disease and Tourette's syndrome. His research has fundamentally changed our understanding of central nervous system function and emotional learning processes
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