Popis predmeta

Course Description

Learning theories and cognitive processes. Educational video materials. Lecture captures. Classroom interaction systems and audience response systems. Tools for testing factual, procedural and conceptual knowledge. Features and capabilities of virtual labs and simulators.

Learning Outcomes

  1. Describe how humans learn
  2. Create short educational video
  3. Create computer based assesment of factual, procedural and conceptual knowledge
  4. Choose and apply approrpiate audience response tools for classroom.
  5. Define required technical properties of a virtual laboratory or simulator

Forms of Teaching

Lectures

Lectures are held weekly. There is a class preparation assignment for each lecture.

Seminars and workshops

Within the course students work on a practical assignment thematically related to the course.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 50 % 10 % 0 % 0 %
Seminar/Project 50 % 60 % 50 % 60 %
Mid Term Exam: Written 0 % 1 % 0 %
Final Exam: Written 50 % 29 %
Exam: Written 50 % 40 %

Week by Week Schedule

  1. Learning theories
  2. Cognitive processes
  3. Creating educational material
  4. Lecture captures
  5. Educational video
  6. Classroom response systems
  7. Computer assisted and automated knowledge assessment
  8. Midterm exam
  9. Computer assisted and automated knowledge assessment
  10. Computer assisted and automated knowledge assessment
  11. Virtual laboratories and simulations
  12. Virtual laboratories and simulations
  13. Programmed and guided learning
  14. Programmed and guided learning
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Elective Course of the profile (3. semester) Elective Course of the Profile (1. semester)

Literature

Peter Jarvis, John Holford, Colin Griffin (2003.), The Theory & Practice of Learning, Psychology Press
Isaac I. Bejar (2016.), Automated Scoring of Complex Tasks in Computer-based Testing, Psychology Press
Spratt, Christine, Lajbcygier, Paul (2009.), E-Learning Technologies and Evidence-Based Assessment Approaches, IGI Global

For students

General

ID 223089
  Winter semester
5 ECTS
L3 English Level
L2 e-Learning
30 Lectures
10 Laboratory exercises

Grading System

90 Excellent
80 Very Good
70 Good
60 Acceptable

Learning Outcomes

  1. Describe how humans learn
  2. Create short educational video
  3. Create computer based assesment of factual, procedural and conceptual knowledge
  4. Choose and apply approrpiate audience response tools for classroom.
  5. Define required technical properties of a virtual laboratory or simulator

Forms of Teaching

Lectures

Lectures are held weekly. There is a class preparation assignment for each lecture.

Seminars and workshops

Within the course students work on a practical assignment thematically related to the course.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 50 % 10 % 0 % 0 %
Seminar/Project 50 % 60 % 50 % 60 %
Mid Term Exam: Written 0 % 1 % 0 %
Final Exam: Written 50 % 29 %
Exam: Written 50 % 40 %

Week by Week Schedule

  1. Learning theories
  2. Cognitive processes
  3. Creating educational material
  4. Lecture captures
  5. Educational video
  6. Classroom response systems
  7. Computer assisted and automated knowledge assessment
  8. Midterm exam
  9. Computer assisted and automated knowledge assessment
  10. Computer assisted and automated knowledge assessment
  11. Virtual laboratories and simulations
  12. Virtual laboratories and simulations
  13. Programmed and guided learning
  14. Programmed and guided learning
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Elective Course of the profile (3. semester) Elective Course of the Profile (1. semester)

Literature

Peter Jarvis, John Holford, Colin Griffin (2003.), The Theory & Practice of Learning, Psychology Press
Isaac I. Bejar (2016.), Automated Scoring of Complex Tasks in Computer-based Testing, Psychology Press
Spratt, Christine, Lajbcygier, Paul (2009.), E-Learning Technologies and Evidence-Based Assessment Approaches, IGI Global

For students

General

ID 223089
  Winter semester
5 ECTS
L3 English Level
L2 e-Learning
30 Lectures
10 Laboratory exercises

Grading System

90 Excellent
80 Very Good
70 Good
60 Acceptable