User Profiling and Skills Recognition

Owned by Marios Meimaris
Last updated: Jun 27, 2017 by Nikola Tomasevic
2 min read



Target releaseMid-17 or later
User StorySWIK-1149
Document status

DRAFT

Date

1 June 2017

Document owner

Marios Meimaris

DesignerMarios Meimaris Kostis Pristouris George Papastefanatos
Developers

Marios Meimaris Kostis Pristouris Stavros Maroulis

Stakeholders

Marios Meimaris, George Papastefanatos, Kostis Pristouris

Abi James, Benjamin Wulff, Kurt Junghanns Mariano Rico

QA
Work Package deliverable

Summary

  • To provide the analytics module for the skills recognition and profiling of users based on their activity and preferences
  • To provide a model (i.e., ontology for modeling personal skills and competencies) and implementation for the User Profiling Module of SlideWiki
  • To implement a supervised classification method for enrichment of user profiles from data collected by the Student Information System
  • To reuse and extend open-source tools (Weak, Apache Mahout, Apache Spark MLib)

Background and goals

User Profiling is applied on two levels, static and dynamic. Thus, SlideWiki will follow a hybrid model for User Profiling.

Static data for user profiling include the user-related data that the user has provided through the creation and updating of his/her profile. These include:

  • Demographic data
    • Name
    • Age
    • Education
  • Educational and Research Interests
  • Affiliation
  • Participation in Groups

Dynamic data for user profiling include extracted and inferred data from user activity. These include:

  • Deck consumption statistics
    • Average time spent on reading/consuming decks
    • Number of presentations given
    • Usage of external sources, multimedia etc.
    • Themes and Domains of created decks (e.g. through semantic annotation and/or tagging)
  • Content creation
    • Average time spent on creating/editing content
    • Number of decks the user is participating as an owner/editor
    • Statistics on usage of the user's created decks from other users (i.e., reachability/popularity of created content)
    • Themes and Domains of created decks (e.g. through semantic annotation and/or tagging)

Assumptions

  • The user profiling module should interact with the activity tracking components in order to ensure that the needed data is produced (e.g. tracking of time spent on decks)


The following table lists static data (manually specified by the user), i.e. user demographic and contextual data, that could be relevant for other WP3 learning analytics as well.

NameDescription

Status

Extra infoComments
countryuser's countryactive

genderuser's genderinactive
Could be introduced on user profile creation
ageuser's age (e.g. 0-20, 21-30,31-40...)inactive
Could be introduced on user profile creation
educationuser's highest educationinactive
Could be introduced on user profile creation
disabilityboolean - whether user has any disabilityinactive

Could be introduced on user profile creation

Action Items

  • Extend User Data Model for User Profiling and Skills Recognition
  • Implement/Extend API routes in User Service for CRUD methods
  • Implement data ingestion controllers using user engagement data (i.e. from activity service) and static data (from user service and deck service)
  • Design and implement algorithms for skills extraction/recognition