Lecture
Learning sciences concepts
In course
DEMO: adipisicing ea consequat
Pariatur nostrud aliquip commodo aliqua ipsum officia consectetur est labore velit. Irure reprehenderit tempor mollit exercitation adipisicing ut minim dolor minim sunt adipisicing veniam. Culpa aliqua eiusmod et elit. Adipisicing quis irure deserunt ipsum cupidatat irure. Qui culpa eu qui velit consectetur nostrud voluptate fugiat duis elit. Aliquip sint esse dolore ullamco reprehenderit occaecat nulla.
Description
This lecture covers key concepts in learning sciences, including sensory memory, working memory, cognitive load, metacognition, and instructional design. It explores topics such as knowledge taxonomy, cognitive tasks taxonomy, and transversal skills.
Instructors (2)
laborum et
Eiusmod ad sunt ipsum nulla eu et irure. In duis quis magna velit proident eu laborum officia deserunt. Consequat excepteur ea magna irure aute ullamco nisi officia aute.
et Lorem
Qui amet adipisicing consequat ad non et elit. Incididunt proident occaecat officia ad sit aliquip occaecat est nulla non officia aliqua. Incididunt occaecat dolor in aliquip do excepteur consequat.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (31)
Formative Test Analysis
Explores engagement, working memory, and effective learning methods like concept maps and peer debating.
Learning Through Connections
Explores learning through connections and effective strategies to enhance memory.
Interactive Learning Activities: Empathy Studies and Metacognition
Introduces a structured plan for engaging in empathy studies and developing metacognitive skills.
Learning Sciences Concepts
Explores cognitive load, metacognition, learning environments, and inductive reasoning, with examples of exam questions and the city of Godthåb.
Neuroscience Inspired Artificial Intelligence
Explores the historical development of deep learning, reinforcement learning, attention mechanisms, and memory systems in AI inspired by neuroscience.