IV127 Adaptive Learning Seminar

Faculty of Informatics
Autumn 2016
Extent and Intensity
0/2/0. 2 credit(s) (plus 1 for the colloquium). Type of Completion: k (colloquium).
Teacher(s)
doc. Mgr. Radek Pelánek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 14:00–15:50 A220
Prerequisites (in Czech)
SOUHLAS
Krom schopnosti číst odborný anglický text je klíčovým předpokladem pouze zájem o studovanou oblast. Souhlas je udělen na základě individuální domluvy ohledně dílčího tématu, kterému se student bude věnovat.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
Students gain experience with reading and presenting research papers and they perform and present their own research and development in the area of adaptive learning.
Syllabus
  • Presentation of research papers from research areas relevant to the Adaptive learning lab - educational data mining, machine learning, cognitive psychology. Development of educational systems, analysis of educational data, presentation and discussion of results.
Literature
  • Advances in intelligent tutoring systems. Edited by Roger Nkambou - Jacqueline Bourdeau - Riichiro Mizoguchi. Berlin: Springer, 2010, xxii, 508. ISBN 9783642143625. info
  • WOOLF, Beverly Park. Building intelligent interactive tutors : student-centered strategies for revolutionizing e-learning. Burlington, MA: Morgan Kaufmann Publishers, 2009, xii, 467. ISBN 9780123735942. info
Teaching methods
Student presentations, moderated discussion.
Assessment methods
Presentation, active participation.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/adaptivelearning/?a=seminar
The course is also listed under the following terms Spring 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2016, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2016/IV127