The course will be centered around analyzing educational data using AI methods and methodological and system-focused perspectives on designing AI systems for education.
The course will start with an introduction to data mining techniques (e.g., prediction, structure discovery, visualization, and relationship mining) relevant to analyzing educational data. We will then continue with topics on personalization in AI in educational technologies (e.g., learner modeling and knowledge tracing, self-improving AIED systems) while showcasing example applications in areas such as content curation, automatic assessment and dialog-based tutoring. Finally, we will cover ethical challenges associated with using AI in student facing settings.
Face-to-face meetings will be held every fortnight, although students will be expected to work individually on weekly tasks (e.g., discussing relevant literature, working on problems, preparing seminar presentations).
Students will be expected to:
This is a research driven, hands-on class. Your participation is important.
The final assessment will be a combination of:
No written exams! Our focus is on learning and continuous evaluation.
Lectures: Thu 13:15-15:00 (ML H44)
Exercise Sessions: Thu 15:15-16:00 (ML H44)
Discussion forum: Moodle
Textbooks: We will not follow any particular textbook. We will draw material from a number of research papers.
Lecture/Discussion | Date | Topic | Course Materials | Events |
1 | 22.09.22 | Introduction | ||
2 | 29.09.22 | Discussion Forum Activity | ||
3 | 06.10.22 | Educational Data Mining (Part 1) (Prediction + Unsupervised structure discovery) |
Assignment 1.1 Released | |
4 | 13.10.22 | Work on Assignment 1.1 + Discussion Forum Activity | ||
5 | 20.10.22 | Educational Data Mining (Part 2) (Correlation Mining + Causal Relationship Mining) |
Assignment 1.2 Released | |
6 | 27.10.22 | Work on Assignment 1.2 + Discussion Forum Activity | ||
7 | 03.11.22 | AIED Applications (Content Curation + Dialog Tutoring) |
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8 | 10.11.22 | Discussion Forum Activity | ||
9 | 17.11.22 | Personalization (Part 1) (Learner Modeling and Knowledge Tracing) |
Assignment 2.1 Released | |
10 | 24.11.22 | Work on Assignment 2.1 + Discussion Forum Activity | ||
11 | 01.12.22 | Personalization (Part 2) (Self-Improving AIED) |
Assignment 2.2 Released | |
12 | 08.12.22 | Work on Assignment 2.2 + Discussion Forum Activity | ||
13 | 15.12.22 | Ethical Issues in AIED |
For discussions, you can do any two of:
Please see Moodle for more details.
Presentation for 20 minutes followed by a 10-minute question answers/discussion. Please see Moodle for more details.
You can ask questions on Moodle. Please post questions there, so others can see them and share in the discussion. If you have questions which are not of general interest, please don’t hesitate to contact us directly.
Lecturers | Mrinmaya Sachan, Tanmay Sinha |
Teaching Assistants | Kumar Shridhar, Jakub Macina, Sankalan Pal Chowdhury, Peng Cui |