IV127 Adaptive Learning Seminar

Faculty of Informatics
Spring 2025
Extent and Intensity
0/2/0. 2 credit(s) (plus 1 for the colloquium). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. Mgr. Radek Pelánek, Ph.D. (lecturer)
Guaranteed by
doc. Mgr. Radek Pelánek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites (in Czech)
PROGRAM(N-UIZD) || PROGRAM(D-INF) || SOUHLAS
Předmět je určen primárně studentům programu Umělá inteligence a doktorandům. Je otevřen i dalším studentů, kteří mají alespoň základní znalosti z oblasti strojového učení. Těm je souhlas se zápisem udělován na základě osobní domluvy na úvodním semináři.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 38 fields of study the course is directly associated with, display
Course objectives
Students gain experience with data analysis and machine learning in the context of educational applications.
Learning outcomes
At the end of the course, students will be able to apply methods of data analysis and machine learning in the area of educational applications.
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
Project work, presentation, active participation.
Language of instruction
Czech
Further Comments
The course is taught each semester.
The course is taught: every week.
The course is also listed under the following terms Spring 2016, Autumn 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.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2025/IV127