* We conducted a research study to understand user preferences for different gameful design elements.
* The research was conducted between January and April/2017 and published/presented at CHI PLAY on October/2017.
* The results showed that user preferences can be classified in three categories and three groups of gameful design elements. Additionally, the results show that the user’s gender, age, gamification user types and personality traits are all related to their preferred gameful design elements.
* These findings extend our understanding of user preferences in gamification and will enable researchers and practitioners to design better tailored gameful systems in the future.
* More information: https://blog.gamefulbits.com/2017/10/30/elements-gameful-design-classified-user-preferences/
Research on gameplay motivations has shown that players have diverse personal preferences regarding how and what they play. Researchers have developed player type models to capture the diverse styles of play exhibited by different players. This information has been increasingly used in gamification to model user behaviour and design more engaging gameful systems. However, the applicability of these models in gamification has not been supported by empirical evidence yet.
Therefore, our research proposes a new conceptual framework for classifying gameful design elements based on participants’ self-reported preferences to understand user behaviour in gamification. While the HEXAD user types framework describes psychological characteristics of the users, this work proposes a novel way to organize gameful design elements.
Based on our investigation, we propose a classification of eight groups of gameful design elements classified into three categories:
I. Internal Motivations
This represents the user’s interest in their own experience within the system.
Immersion: The elements in this group are related to immersion and curiosity. It includes elements related with a narrative or story and elements related with exploration and unpredictability.
Progression: The elements in this group are related to progression and meaning. Thus, it represents the will to be involved in meaningful goals and to feel one is progressing towards achieving them.
II. External Motivations
This represents the user’s interest in earning external incentives and tailoring the system to them.
Incentive: All elements in this group correspond to incentives or rewards that the user might receive, such as
badges, achievements, collectible items, and rewards.
Risk/Reward: The elements in this group are related to challenges, gambling, and the rewards that come from winning. Thus, it represents the expectation of winning economically or socially valuable prizes both from challenges and lotteries.
Customization: The elements in this group are related to three different ways of customizing one’s own experience: (1) customizing the user’s avatar or experience, (2) automatic personalization, or (3) redeeming freely chosen goods with virtual currency or points.
III. Social Motivations
This represents the user’s interest in relatedness and social interactions.
Socialization: All elements in this group correspond to some form of social interaction, including both collaborative, competitive, and entirely social interactions.
Assistance: All elements in this group correspond to the user receiving some sort of aid for their progression, either from the system or from other users.
Altruism: All elements in this group correspond to diverse ways of making a useful contribution, either to the system or to other users, including sharing knowledge or goods, contributing to improve the system, and collaborating with other users.
This research also explained the typical characteristics of the users who are more likely to prefer each group and proposed different ways in which this framework can be used to inform gameful design, either by automatically profiling user preferences or by explicitly asking users about their preferences. These findings extend our understanding of user preferences in gamification and will enable researchers and practitioners to design better tailored gameful systems in the future.