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

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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

  • 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


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]


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