Leonid stoimenov vladan mihajlovic faculty of electronic engineering university of nis
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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.

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Leonid stoimenov vladan mihajlovic faculty of electronic engineering university of nis

Public Presentation TEMPUS project (CD-JEP 16160/2001) Innovation of Computer Science Curriculum in Higher EducationArtificial Intelligence CourseInnovation in Teaching Methods

Leonid Stoimenov, Vladan Mihajlovic

Faculty of Electronic Engineering, University of Nis


Previous experience in ai course
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
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
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
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



Lectures
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
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
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


Second project
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





Conclusions
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
Official AI course site:http:||gislab.elfak.ni.ac.yu|vi

Contacts:

Leonid Stoimenov – [email protected]

Vladan Mihajlovic – [email protected]

Aleksandar Milosavljevic – [email protected]


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