Transcript Tempus Project Site

Public Presentation
TEMPUS project (CD-JEP 16160/2001)
Innovation of Computer Science Curriculum
in Higher Education
Artificial Intelligence Course
Innovation in Teaching Methods
Leonid Stoimenov, Vladan Mihajlovic
Faculty of Electronic Engineering, University of Nis
Previous experience in AI course
The professor discourse in old fashion, using
chalk and blackboard
The lectures are ordinary and boring
The students listen the lecture without interest
in the teaching
The students take the notes as the reference
exam preparation
The students learn immediately before the
exam
The knowledge demonstrated on laboratory
exercises is not included in total score
How to improve learning process?
Make lectures interesting
Inspire the students to listen the classes
Motivate the students to learn during
the semester
Encourage the students to pass the
exam in first term
Increase the portion of the students
practice work in the course
AI course organization
Lectures
Exercises


Theoretical
Practical (laboratory)
Projects (homework)
Final evaluation include


Projects (40%)
Final exam (60%)
New web site
New AI course web site contents
Lecture notes
Practical problems and solution in LISP
Exam results
Information about project


List of proposed project
Information about finished projects
Links to literature and interesting AI
web sites
http:||gislab.elfak.ni.ac.yu|vi
AI course web site
Lectures
New topic that are actual in AI domain
are included in the course
The modern way of explain the old and
new topics covered
The students have the lecture notes in
advance
The students can participate actively in
teaching process and pose the questions
during the class
Exercises
Theoretical exercises



LISP – most important commands and
simple examples
AI algorithms and techniques
Implementation of some AI algorithms
Laboratory exercises



6 common AI exercises in applying
theoretical knowledge
The exercises are mandatory
The students work individually
First Projects
The first project




Same task for all
students (Victory,
Puzzle)
Implementation in
LISP
Checkpoints ones
a week (include
reports)
End date is strictly
defined
1
2
3
4
5
6
7
8
Second Project
Interpretation of AI algorithms and
techniques
Applying of AI algorithms and
techniques in other domains
Results:


Application
Project documentation
Rules:


No checkpoints and reports
Must be finished at the end of course
A* Search Algorithm
Time Series Prediction
Game: “The Balls”
Conclusions
The students motivation to attend
lectures is increased
The students participate actively in
teaching
The students learn more during the
semester
Learning theoretical principles and its
practical implementation in parallel
make lessons easier to understand
Analysis during last two years show that
80% of students pass the exam
immediately after course is finished
Official AI course site:
http:||gislab.elfak.ni.ac.yu|vi
Contacts:
Leonid Stoimenov – [email protected]
Vladan Mihajlovic – [email protected]
Aleksandar Milosavljevic – [email protected]