Department of Information and Computing Sciences

Departement Informatica Onderwijs
Bachelor Informatica Informatiekunde Kunstmatige intelligentie Master Computing Science Game&Media Technology Artifical Intelligence Business Informatics

Onderwijs Informatica en Informatiekunde

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Technologies for learning

Website:website containing additional information
Course code:INFOMTFL
Credits:7.5 ECTS
Period:period 1 (week 36 through 45, i.e., 5-9-2016 through 11-11-2016; retake week 1)
Participants:up till now 25 subscriptions
Schedule:Official schedule representation can be found in Osiris
Teachers:Dit is een oud rooster!
lecture   Mon 11.00-12.4537-45 ANDRO-O004 Johan Jeuring
Ivica Milovanovic
Wed 11.00-12.4537-45 SGG-C024
Contents:In this course you will learn about the use of software technology to support student learning.
Student learning is supported by applications such as: These applications use technologies such as:
  • Model tracing: does a student follow a desirable path towards a solution?
  • Constraint-based modeling: does a student product satisfy a number of requirements?
  • Learning analytics: what do students do in a learning application?
  • User modeling: what does a student know?
which build upon:
  • Strategies, parsing and rewriting
  • Bayesian networks
  • Datamining
  • Constraint solving
  • Artificial Intelligence
and domain-specific technologies, such as compiler technology (like static and dynamic analysis) for the domain of programming.
After completing this course, you will be able to:
  • develop technology for:
    • comparing student behavior with desirable behavior
    • giving feedback in an application for learning
    • modeling the knowledge of a student
    • finding out what students do in a learning environment
  • use this technology in applications for supporting learning
  • read, present, and use results from papers from the important conferences and journals in the field.
This course will prepare you to contribute to research in this area.
Literature:Several papers which will be listed on the webpage for the course.
Course form:Lectures, reading sessions/paper presentations, research projects.
Exam form:
  • Lab, individual, 10%
  • Research project - work in a team to formulate and solve a research problem, present results in a presentation and report
    • research proposal, team, 10%
    • code for the research project, team, 20%
    • final report and presentation of the research, team, 30%
    • oral examination, individual, 30%
Minimum effort to qualify for 2nd chance exam:Om aan de aanvullende toets te mogen meedoen moet de oorspronkelijke uitslag minstens 4 zijn.

In this course you will study advanced software technologies for learning, such as serious games in which you have to develop a sustainable city, simulations such as a virtual company that you have to run, competing against several other virtual companies, intelligent tutoring systems for learning mathematics, physics, or logic, etc. In particular, you will study the underlying intelligence necessary to determine what a student has learned, what a student should do next, give feedback to a student, etc.

The background necessary to solve some of the problems is very diverse: knowledge of data mining techniques, parsing and rewriting, artificial intelligence, etc. is all useful. I will try to adapt the projects to the background of the students, and try to use available knowledge as much as possible.