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Cursus: INFOMTFL
INFOMTFL
Technologies for learning
Cursus informatie
CursuscodeINFOMTFL
Studiepunten (EC)7,5
Cursusdoelen
 After this course you should be able to:
  • identify, relate and explain fundamental concepts in the field of computer-based education with a particular focus on adaptive and intelligent technologies;               
  •  understand the basics of the underlying pedagogical and cognitive theories and frameworks supporting human learning;
  • apply these concepts in practice by designing, developing and/or evaluating components of adaptive and intelligent educational systems as well as analyzing datasets produced by students using such systems
  • use relevant literature to examine existing projects and form an opinion about innovations in the field
  • investigate a problem within the field of computer-based educational technologies and set up a plan for a group project targeting it.
Assessment
  • in-class work: individual or group topics presentations and discussions: 25% of the final mark
  • group project (execution, presentation and report): 45%
  • Final exam: 30%
The repair test requires at least a 4 for the original test.
Inhoud
The list of topics we will research includes but is not limited to:
  • student modelling technologies for representing knowledge, metacognitive skills and strategies and affective state of a student working with an adaptive education system
  • technologies for adaptive learning support, such as intelligent tutoring systems and adaptive educational hypermedia
  • technologies for supporting collaborative, group-based and social learning scenarios;
  • technologies exploiting big data set in education for empowering student and teachers, as well as improving the behavior of intelligent educational software
  • modern HCI methods used in education for creating effective learning interfaces including dialog systems, learning companions, serious games and virtual reality
This academic field is extremely interdisciplinary. Hence, the background necessary to study and work with these technologies can be very diverse: knowledge of data mining and machine learning, parsing and rewriting, artificial intelligence and HCI are all useful.
The course material as well as topics for group project will be adjusted to the background of the students in order to use the cumulative expertise of the class as much as possible.

Course form
  • lectures
  • student presentations
  • in-class discussions
  • group project

Literature
Necessary research articles will be provided.

Materials
Remove software (UA10182 Haskell 2013)

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