Development of the Personalized Recommender System COsys for Career Orientation

556 views
471 views

Published on

Published in: Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
556
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Development of the Personalized Recommender System COsys for Career Orientation

  1. 1. “Do you think that the young students possess the listed competencies?” (to the managers) “Do you think that you possess the listed competencies?” (to the students) The suggested competencies for voting:  technical – available technical skills, including skills for programming and skills for working with hardware devices;  functional – abilities for performing of concrete engineering activities related to the job position,  social – competences related to the human behavior and effective communication and socialization,  global – abilities for working in multicultural team,  meta – ability for knowing how to learn, how to adapt, how to assess Classes Description Content-based It recommends resources that a user has read or has liked in the past Collaborative- based It recommends resources that are read and liked by users with similar profiles compared to the current user Demographic- based It recommends resources that are read and liked by users with similar demographic profiles Knowledge- based It recommends knowledge in a given domain Learning path- based It recommends knowledge formed in learning paths Social societies- based The recommendations are produced as consequences of social relations and communications of a user Hybrid It includes two or more from the above mentioned techniques COsys modules Registration - creation of an account in COsys system and an individual student profile preparation Competences Analysis - proposes a quiz and makes an analysis about the existing student’s competences Recommender - generates recommendations with a suitable learning path to this student Market Information - includes search engine and the possibility for looking of available job positions Access to Information Resources - connects a student to the information resources –how a CV to be written, how a motivational letter to be constructed or what are the steps for interview preparation Learning Sources - suggests two types of learning sources that could improve student knowledge in a given domain 0 10 20 30 40 50 60 70 80 90 Adaptivity Willingnesstowork Ethic Efficiency Computerskills Leadershipskills Mathematicalskills Socialskills Motivation Professionalskills Communication Criticalthinking Officeskills Entrepreneurship Sellingskills Creativity Technicalskills Clientservicing Self-management Foreignlanguages Employers Students Browser Web server Dispatcher Controllers Action View Active record Recommendable Resque RDBMS SQLite Redis WEBrick Ruby Gem app like/dislike Changes in like/dislike status DDeevveellooppmmeenntt ooff tthhee PPeerrssoonnaalliizzeedd RReeccoommmmeennddeerr SSyysstteemm CCOOssyyss ffoorr CCaarreeeerr OOrriieennttaattiioonn AAIIMM to present the developed COsys as a personal and social-oriented learning environment forcing students to perform self-analysis of their current competences and to learn by recommendations MMEETTHHOODDOOLLOOGGYY (1) development of survey tools for analysis of the most important and critical competences for every individual student (2) detailed exploration and analysis of the needed competences of an employee for successful realization, (3) COsys functionality description and design (4) examination of existing algorithms for recommendation generation (5) system implementation through Ruby on Rails, WEbrick web server, SQLite RDBMS, Redis digital repository. Survey tools 1 Competences analysis 2 Conclusion: As it can be seen different institutions in our society are looking for highly qualified and well trained staff ready to perform specialized technical work. One step for achieving that is ensuring a communication gate between employees and employers. We assert that the presented work has the ability to support career development of students and their personal progress in lifelong learning aspect. Functionality 3Recommender algorithms 4 Implementation 5 For contacts: Malinka Ivanova, m_ivanova@tu-sofia.bg Tsvetelina Atanasova, atanasova.tsvetelina@gmail.com

×