Recommender systems, virtual guidance and virtual self-help in mastering knowledge

1.

Subject title

Recommender systems, virtual guidance and virtual self-help in mastering knowledge

Системи за препорачување, виртуелно насочување и виртуелна самопомош при совладување на знаењето

2.

Code

m23_s_041

3.

Study program

Cloud Computing, Bioinformatics, Security, Cryptography and Coding, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Data science in computer science and engineering, Cloud Computing, Statistics and Data Analytics, IT management, Еducation with ICT, IT management,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Вангел Ајановски

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The purpose of the course is to get acquainted with advanced methods and technologies that enable virtual guidance in mastering knowledge, recommending topics of interest, recommendation of paths and self-help systems to prevent potential problems. In addition to the educational sphere, the subject is also useful for students from commercial spheres, especially in the direction of a better organization of human resources based on assessing knowledge. Competences expected to be acquired by the student after completing the subject: - Understanding methods and techniques for mapping knowledge - Understanding methods and techniques for assessing success and risk in mastering knowledge - Using data analysis technologies aimed at mapping knowledge, success and risk assessment - Using technologies for visualization of the knowledge space - Impose integrated mapping systems, visualization, navigation, recommendation, directing and self-help using finished technologies

11.

Subject content:

Topics processed within this subject: - Introduction to automated detection of interests and virtual guidance. - Methods for mapping areas, areas, topics and competencies in a sphere of interest. - Methods for assessing success in mastering knowledge. - Methods of detecting interest in mastering knowledge. - visualization and navigation through the space of knowledge. - Social navigation and collaborative definition of interests. - Methods for spatial self -orientation through the space of knowledge. - Methods for recommending paths of movement through the knowledge space. - Methods for recommending interesting areas and topics for user -friendly. - Assessment of quality mapping of the knowledge space. - Assessment of quality recommendations. - Guides through a career. - whistleblowers of problematic regions of the knowledge space, impact assessment. - Implementation of integrated systems for virtual conducting through knowledge, recommendation and self-help.

12.

Learning methods:

- Предавања и вежби со дискусии базирани на примери, анализа на различни достапни примери - Компјутерски потпомогнато учење - Електронско и учење на далечина - Групно истражување и развој - Користење на релевантни софтверски алатки - Изработка на проект и одбрана на проектот

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 30 + 15 + 90 + 15 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

30 hours

16.

Other forms of activities

16.1.

Project tasks

90 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

15 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

90 points

17.3.

Activities and learning

30 points

17.4.

Final exam

15 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

50% од активностите и првична верзија од проектот

20.

Language of instruction

македонски, англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature