Coursebooks 2017-2018

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Digital education & learning analytics

CS-411

Lecturer(s) :

Dillenbourg Pierre
Jermann Patrick

Language:

English

Summary

This course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies on this topic: do student actually learn due to technologies?

Content

Learning theories and learning processes. Instructional design: methods, patterns and principles. Orchestration graphs. On-line education. Effectiveness of learning technologies. Methods for empirical research. Learning analytics. History of learning technologies. 

Keywords

learning, pedagogy, teaching, online education, MOOCs 

Learning Prerequisites

Recommended courses

One of these courses is recommended:

- Machine Learning (Jaggi / Urbanke)

- Applied Data Analysis (West)

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

The course will combine participatory lectures with a project around learning analytics

 

Expected student activities

The project will include several milestones to be delivered along the semester.

Assessment methods

Supervision

Office hours No
Assistants Yes
Forum Yes

Resources

Moodle Link

In the programs

Reference week

 MoTuWeThFr
8-9 INR113   
9-10    
10-11 INR113   
11-12    
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German