TY - GEN
T1 - Adaptive approach for gamification optimization
AU - Codish, David
AU - Ravid, Gilad
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/29
Y1 - 2014/1/29
N2 - Gamification solutions today are mostly applied as a single strategy to products and processes (one size fits all approach), thus the engagement and playfulness levels achieved from them are sub-optimal and possibly even negative. Ensuring users are fully engaged in gamification requires that designers understand what motivates users and how different game elements, or combination of elements, address these needs. Measuring engagement through Gamification Analytics (GA) and more importantly being able to act based on this data and modify the implementation in a timely manner if needed, is an important capability that is mostly missing today, and is addresses in the framework proposed in this paper. Since different people are motivated differently, an ideal gamification implementation should be able to perform on-line GA and induce the above modifications, at the user level, taking into account his demographics and personality and creating a personalized gamification experience within the overall gamification solution. We additionally propose a cloud based, open-source database for sharing different game mechanics and dynamics structures.
AB - Gamification solutions today are mostly applied as a single strategy to products and processes (one size fits all approach), thus the engagement and playfulness levels achieved from them are sub-optimal and possibly even negative. Ensuring users are fully engaged in gamification requires that designers understand what motivates users and how different game elements, or combination of elements, address these needs. Measuring engagement through Gamification Analytics (GA) and more importantly being able to act based on this data and modify the implementation in a timely manner if needed, is an important capability that is mostly missing today, and is addresses in the framework proposed in this paper. Since different people are motivated differently, an ideal gamification implementation should be able to perform on-line GA and induce the above modifications, at the user level, taking into account his demographics and personality and creating a personalized gamification experience within the overall gamification solution. We additionally propose a cloud based, open-source database for sharing different game mechanics and dynamics structures.
KW - Adaptive Gamification
KW - Gamification
KW - Gamification Analytics
KW - Personality
UR - https://www.scopus.com/pages/publications/84980047994
U2 - 10.1109/UCC.2014.94
DO - 10.1109/UCC.2014.94
M3 - Conference contribution
AN - SCOPUS:84980047994
T3 - Proceedings - 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014
SP - 609
EP - 610
BT - Proceedings - 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014
PB - Institute of Electrical and Electronics Engineers
T2 - 7th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2014
Y2 - 8 December 2014 through 11 December 2014
ER -