FI:IV127 Adaptive Learning Sem. - Course Information
IV127 Adaptive Learning Seminar
Faculty of InformaticsAutumn 2023
- 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. 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 - Timetable
- Wed 12:00–13:50 A220
- Prerequisites (in Czech)
- SOUHLAS
Studenti programu Umělá inteligence dostávají souhlas v podstatě automaticky. Ostatním je souhlas udělen 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 37 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
- Study Materials
The course is taught each semester.
- Enrolment Statistics (Autumn 2023, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2023/IV127