Instructors

• PD Dr. Erica Melis
• Prof. Dr. Jörg Siekmann
• Dr. Bruce McLaren

Course administration

• Oliver Scheuer

General information

• Lecture type: Advanced Course CS
• Credit points: 6 CP
• Time: Tuesdays 10:00-12:00
• Location: HS003 in Geb E1.3
• Start: October 28

Informationen für Nicht-Informatiker

Neben Informatikstudenten wendet sich die Vorlesung an Studenten der Informationswissenschaft, Lehramt Mathematik/Informatik und Psychologie (mit Informatik-Hintergrund).

Studierende der Informationswissenschaft können im Rahmen der Vorlesungen einen Leistungsnachweis ("Schein") nach Rücksprache mit Priv.-Doz. Dr. Christoph Igel erwerben.

Registration

Click here to register for the course.

NOTE: This is only for our course-internal record of participants. In case your study programme is subject to HISPOS (e.g., computer science students), you will need to register for this course also in the HISPOS system (due date: Dec, 5).

Course description and topics

The course introduces and discusses the components and techniques needed for implementing technology enhanced learning systems, among them the ActiveMath system developed at our university. The course teaches the principles underlying the design of intelligent learning technology and the components needed in such systems. The following topics will be covered:

• Intelligent tutoring systems (Cognitive Tutors, ActiveMath)
  • Student modelling and competencies
  • Pedagogical components, instructional planning
  • Interactivity and feedback
  • Error diagnosis
• Meta-cognitive support (on help, on erroneous examples)
• Collaborative learning technologies
• Educational data mining
• Multi-Media Learning principles
• Web-based systems (ontologies, metadata, navigation, architectures, collabotative authoring)
• Authoring tools

In projects for groups of 2-3 students, you will implement simple components, encode educational content, or conduct empirical studies.

Prerequisites

Knowledge about Artificial Intelligence techniques is useful but not required.

Requirements and grading criteria

For passing the course, the following requirements have to be satisfied (a grading key will follow soon)

• course wiki participation
• student project: report and presentation
• presence in lectures

Student projects

This course will be accompanied by student projects (instead of 35 hours 'Übungen'). Each project will be performed by groups of 2-3 student and presented at one of the last lectures by the students. Click here for the list of available projects.

NEW: We have set up a mailing list where you can discuss topics not directly related to course contents. You can use this list to find collaborators for your student projects. Course contents should be discussed in the Course-Wiki. Contents discussed on this list will not be considered for the grading of your Wiki participation. Here to the registration page (please also have a look into the list archive to see requests for project collaborators that were issued prior to your registration).

Course Wiki

During the course students will contribute to the course wiki. Click here to get to the wiki pages and to receive further instruction.

Preliminary course syllabus

• 28.10.2008: Introduction (pdf)
• 04.11.2008: Intelligent tutoring systems (1) - Cognitive Tutors (pdf)
• 11.11.2008: Intelligent tutoring systems (2) - ActiveMath (pdf)
• 18.11.2008: Student modelling (pdf, see slides 1-41)
• 25.11.2008: Student modelling (pdf, see slides 42-78)
• 02.12.2008: Pedagogical components, instructional planning (pdf)
• 09.12.2008: Meta-cognitive support (1) - Help (pdf)
• 16.12.2008: Error diagnosis and feedback (pdf)
• 06.01.2009: Error diagnosis and feedback (pdf)
• 13.01.2009: Collaborative learning technologies
• 20.01.2009: Multi-Media Learning principles
• 27.01.2009: Web-based systems
• 03.02.2009: Educational data mining
• 23.02.2009: Project presentations by students