Evaluating the impacts of using gamification in recommender system
Saba Dadsetan
Intelligent Systems Program University of Pittsburgh 20 April 2017
University of Pittsburgh
using gamification in recommender system Saba Dadsetan Intelligent - - PowerPoint PPT Presentation
University of Pittsburgh Evaluating the impacts of using gamification in recommender system Saba Dadsetan Intelligent Systems Program University of Pittsburgh 20 April 2017 Outline Introduction Open learner model Mastery grid (
Intelligent Systems Program University of Pittsburgh 20 April 2017
University of Pittsburgh
Open Learner Model (OLM)
Mastery Grid
Open Learner Model (OLM)
Mastery Grid
java programming
Recommender System
activity to user
Motivation
Open Learner Model (OLM)
Mastery Grid
java programming
Recommender System
activity to user
Motivation
in non-game context
system
encourage learners, it is not trivial to get desired effects and it will need a tremendous effort on establishing such a system. So, we need to create a framework with enough quality to attract learners. (Dominguez et al., 2013)
make you more productive, or make you a better person. However, it can add to an existing foundation that could help you get there, if you want it to.
Orientation and they categorized them into five group: Mastery-intrinsic, Mastery-extrinsic, Performance-approach, Performance-avoidance, and Avoidance (Auvinen, Hakulinen, and Malmi , 2015 )
Recommended Badges Example Badges Challenge Badges Coding Badges
INFSCI17Spring2018 CIS220Spring2018 IS0017Fall2017 Number of sessions
Median of number of activities in session
Median of time spent in a session (second)
Median of assessment activities done (challenges, coding exercises) in a session
Median of example lines clicked in a session
Topics covered
Total time they spend in Mastery grid
INFSCI17Spring2018 CIS220Spring2018 pcex_topics_covered
example_lines_actions
pcex_success_first_attempt
pcex_success_second_attempt
pcex_success_third_attempt
total_durationseconds
pcex_example_durationseconds