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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 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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  1. 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

  2. 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

  3. 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

  4. AI course organization • Lectures • Exercises • Theoretical • Practical (laboratory) • Projects (homework) • Final evaluation include • Projects (40%) • Final exam (60%) • New web site

  5. 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

  6. AI course web site

  7. 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

  8. 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

  9. 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

  10. 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

  11. A* Search Algorithm

  12. Time Series Prediction

  13. Game: “The Balls”

  14. 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

  15. Official AI course site:http:||gislab.elfak.ni.ac.yu|vi Contacts: Leonid Stoimenov – leni@elfak.ni.ac.yu Vladan Mihajlovic – wlada@elfak.ni.ac.yu Aleksandar Milosavljevic – alexm@elfak.ni.ac.yu

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