Lesson 21

• Artificial Intelligence (AI)


  The manner by which machines think, react, and work like the human brain
• AI


  • Allows machines to process data, patterns, and models in order to perceive, reason, plan, solve problems, make predictions, and manipulate objects
• Digital systems related to AI

  • Algorithms
  • Big data
  • Machine learning
  • Deep learning
  • Data mining
  • Learning analytics
• Algorithms


  Sets of instructions for handling data by computers
• Big data


  Digital ecosystems that capture, manage, process, and transfer extremely large data sets
• Machine learning


  An approach where algorithms are tested so they can make data automatically generate results
• Deep learning


  Draws inspiration from the brain's neural network structure to interpret data through interconnections, layers of meaning, and propagation directions
• Data mining


  The process of looking for useful patterns and relationships in big data
• Learning analytics


  The critical evaluation of raw data and the generation of patterns of learner habits, predicting their response and providing feedback
• Roles of AI in education

  • Automation of basic activities in education
  • Supporting students through additional AI tutors
  • Source of feedback via AI-driven programs
  • Making trial and error less intimidating
  • Transforming the teacher, the learner, and the learning process
• Digital literacy


  The ability to access, manage, understand, integrate, communicate, evaluate and create information safely and appropriately through digital devices and networked technologies for participation in economic and social life
• Digital literacy competency areas


  • Fundamentals of hardware and software
  • Information and data literacy
  • Communication and collaboration
  • Digital content creation
• Computational thinking


  A problem solving process that involves formulating and solving problems with the use of computer and other tools, logically organizing and analyzing data, representing data through abstractions, automating solutions through algorithmic thinking, identifying, analyzing, and implementing possible solutions, and generalizing and transferring this problem-solving process to a wide variety of problems