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⏱ 2h 48m📚 28 lessons
Motivation in Learning: Foundations for Educators
Understand the psychology of motivation and apply evidence-based strategies to foster engagement and persistence in any learning environment.
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About this course
Ever wondered why some learners thrive while others struggle, even with similar abilities? Motivation is the powerful force that drives engagement and persistence in learning. This course provides a foundational understanding of motivational psychology, equipping you with the insights and tools to analyze, understand, and cultivate motivation in yourself and others, leading to more effective and fulfilling learning experiences. What you'll learn: Understand the core concepts, definitions, and characteristics of motivation and motivators. Explore foundational theories of motivation, including behavioral, cognitive, and humanistic perspectives. Apply practical strategies to identify and nurture intrinsic motivation in diverse learning contexts. Recognize the profound educational significance of motivation for academic success and personal growth. Learn to integrate modern approaches like growth mindset to build resilience and a love for learning. Discover how self-determination theory can inform the design of engaging and autonomy-supportive learning environments. The course begins with essential terminology and the fundamental psychological principles of motivation, then progresses through major theories and their practical applications, concluding with modern strategies for fostering motivated learners. This course is designed for beginners with no prior knowledge of psychology or education, including aspiring educators, parents, trainers, and anyone curious about how motivation impacts learning. Start reading today to unlock the secrets of effective learning motivation.
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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⚡Short & focused 2h 48m of practical content
Certificate of completion
Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.