Project Details

Personalized Gameful Design

People

Members

Lennart Nacke
Director of the HCI Games Group

Alberto Mora
Visiting Ph.D. Student, Gamification Elements

Rita Orji
Post Doctoral Fellow, Persuasive Games

Stuart Hallifax
Postdoctoral Researcher, Adaptive Gamification

Gustavo Fortes Tondello
Ph.D. Researcher, Personalization of Gameful Interactive Systems

Publications

HexArcade: Predicting Hexad User Types By Using Gameful Applications

@inproceedings{Altmeyer2020,
author = {Altmeyer, Maximilian and Tondello, Gustavo F. and Kr{\"{u}}ger, Antonio and Nacke, Lennart E.},
booktitle = {Proceedings of the the Annual Symposium on Computer-Human Interaction in Play (CHI PLAY 2020)},
doi = {10.1145/3410404.3414232},
isbn = {9781450380744},
keywords = {Gamification,Hexad,Personalization,Prediction},
title = {{HexArcade: Predicting Hexad User Types By Using Gameful Applications}},
year = {2020}
}

Personalization is essential for gameful systems. Past research showed that the Hexad user types model is particularly suitable for personalizing user experiences. The validated Hexad user types questionnaire is an effective tool for scientific purposes. However, it is less suitable in practice for personalizing gameful applications, because filling out a questionnaire potentially affects a person’s gameful experience and immersion within an interactive system negatively. Furthermore, studies investigating correlations between Hexad user types and preferences for gamification elements were survey-based (i.e., not based on user behaviour). In this paper, we improve upon both these aspects. In a user study (N=147), we show that gameful applications can be used to predict Hexad user types and that the interaction behaviour with gamification elements corresponds to a users’ Hexad type. Ultimately, participants perceived our gameful applications as more enjoyable and immersive than filling out the Hexad questionnaire.

Validation of User Preferences and Effects of Personalized Gamification on Task Performance

@article{Tondello2020a,
abstract = {Personalized gamification is the tailoring of gameful design elements to user preferences to improve engagement. However, studies of user preferences have so far relied on self-reported data only and few studies investigated the effects of personalized gameful systems on task performance. This study shows that personalized gamification works in practice as predicted by survey studies and leads to higher task performance. We asked 252 participants in two studies to interact with a customized (experimental) or a generic (control) online gameful application to classify images. In the customized version, they could select the game elements that they wanted to use for their experience. The results showed significant correlations between participants' choice of gameful design elements and their Hexad user type scores, which partly support existing user preference models based on self-reported preferences. On the other hand, user type scores were not correlated with participants' preferred game elements rated after interacting with the gameful system. These findings demonstrate that the Hexad user types are a viable model to create personalized gameful systems. However, it seems that there are other yet unknown factors that can influence user preferences, which should be considered together with the user type scores. Additionally, participants in the experimental condition classified more images and rated their experience of selecting the game elements they wanted to use higher than in the control, demonstrating that task performance improved with personalization. Nonetheless, other measures of task performance that were not explicitly incentivized by the game elements did not equally improve. This contribution shows that personalized gameful design creates systems that are more successful in helping users achieve their goals than generic systems. However, gameful designers should be aware that they must balance the game elements and how much they incentivize each user behavior, so that the business goals can be successfully promoted. Finally, we analyzed participants' qualitative answers about their experience with the generic and the customized gameful applications, extracting useful lessons for the designers of personalized gameful systems.},
author = {Tondello, Gustavo F and Nacke, Lennart E},
doi = {10.3389/fcomp.2020.00029},
keywords = {Hexad user types,adaptation,customization,gameful design,gamification,hexad user types,personalization},
pages = {29},
title = {{Validation of User Preferences and Effects of Personalized Gamification on Task Performance}},
volume = {2},
year = {2020}
}

Personalized gamification is the tailoring of gameful design elements to user preferences to improve engagement. However, studies of user preferences have so far relied on self-reported data only and few studies investigated the effects of personalized gameful systems on task performance. This study shows that personalized gamification works in practice as predicted by survey studies and leads to higher task performance. We asked 252 participants in two studies to interact with a customized (experimental) or a generic (control) online gameful application to classify images. In the customized version, they could select the game elements that they wanted to use for their experience. The results showed significant correlations between participants' choice of gameful design elements and their Hexad user type scores, which partly support existing user preference models based on self-reported preferences. On the other hand, user type scores were not correlated with participants' preferred game elements rated after interacting with the gameful system. These findings demonstrate that the Hexad user types are a viable model to create personalized gameful systems. However, it seems that there are other yet unknown factors that can influence user preferences, which should be considered together with the user type scores. Additionally, participants in the experimental condition classified more images and rated their experience of selecting the game elements they wanted to use higher than in the control, demonstrating that task performance improved with personalization. Nonetheless, other measures of task performance that were not explicitly incentivized by the game elements did not equally improve. This contribution shows that personalized gameful design creates systems that are more successful in helping users achieve their goals than generic systems. However, gameful designers should be aware that they must balance the game elements and how much they incentivize each user behavior, so that the business goals can be successfully promoted. Finally, we analyzed participants' qualitative answers about their experience with the generic and the customized gameful applications, extracting useful lessons for the designers of personalized gameful systems.

Dynamic Personalization of Gameful Interactive Systems

@phdthesis{Tondello2019Thesis,
title = {Dynamic Personalization of Gameful Interactive Systems},
author = {Gustavo Fortes Tondello},
url = {http://hdl.handle.net/10012/14807},
year = {2019},
date = {2019-07-17},
address = {Waterloo, ON, Canada},
school = {University of Waterloo},type = {PhD Thesis},
pubstate = {published},
tppubtype = {phdthesis}
}

Gameful design, the process of creating a system with affordances for gameful experiences, can be used to increase user engagement and enjoyment of digital interactive systems. It can also be used to create applications for behaviour change in areas such as health, wellness, education, customer loyalty, and employee management. However, existing research suggests that the qualities of users, such as their personality traits, preferences, or identification with a task, can influence gamification outcomes. It is important to understand how to personalize gameful systems, given how user qualities shape the gameful experience. Current evidence suggests that personalized gameful systems can lead to increased user engagement and be more effective in helping users achieve their goals than generic ones. However, to create these kinds of systems, designers need a specific method to guide them in personalizing the gameful experience to their target audience. To address this need, this thesis proposes a novel method for personalized gameful design divided into three steps: (1) classification of user preferences, (2) classification and selection of gameful design elements, and (3) heuristic evaluation of the design. Regarding the classification of user preferences, this thesis evaluates and validates the Hexad Gamification User Types Scale, which scores a person in six user types: philanthropist, socialiser, free spirit, achiever, player, and disruptor. Results show that the scale’s structural validity is acceptable for gamification studies through reliability analysis and factor analysis. For classification and selection of gameful design elements, this thesis presents a conceptual framework based on participants’ self-reported preferences, which classifies elements in eight groups organized into three categories: individual motivations (immersion and progression), external motivations (risk/reward, customization, and incentives), and social motivations (socialization, altruism, and assistance). And to evaluate the design of gameful applications, this thesis introduces a set of 28 gameful design heuristics, which are based on motivational theories and gameful design methods and enable user experience professionals to conduct a heuristic evaluation of a gameful application. Furthermore, this thesis describes the design, implementation, and pilot evaluation of a software platform for the study of personalized gameful design. It integrates nine gameful design elements built around a main instrumental task, enabling researchers to observe and study the gameful experience of participants. The platform is flexible so the instrumental task can be changed, game elements can be added or removed, and the level and type of personalization or customization can be controlled. This allows researchers to generate different experimental conditions to study a broad range of research questions. Our personalized gameful design method provides practical tools and clear guidelines to help designers effectively build personalized gameful systems.

Empirical Validation of the Gamification User Types Hexad Scale in English and Spanish

@article{Tondello2018e,
abstract = {Gamification, the use of game elements in non-game systems, is now established as a relevant research field in human-computer interaction (HCI). Several empirical studies have shown that gameful interventions can increase engagement and generate desired behavioural outcomes in HCI applications. However, some inconclusive results indicate that we need a fuller understanding of the mechanisms and effects of gamification. The Gamification User Types Hexad scale allows us to parse different user motivations in participants‘ interactions with gameful applications, which are measured using a self-report questionnaire. Each user type represents a style of interaction with gameful applications, for example, if the interactions are more focused on achievements, socialization, or rewards. Thus, by scoring an individual in each one of the user types of the Hexad model, we can establish a profile of user preferences for gameful interactions. However, we still lack a substantial empirical validation of this scale. Therefore, we set out to validate the factor structure of the scale, in both English and Spanish, by conducting three studies, which also investigated the distribution of the Hexad‘s user types in the sample. Our findings support the structural validity of the scale, as well as suggesting opportunities for improvement. Furthermore, we demonstrate that some user types are more common than others and that gender and age correlate with a person‘s user types. Our work contributes to HCI research by further validating the utility of the Gamification User Types Hexad scale, potentially affording researchers a deeper understanding of the mechanisms and effects of gameful interventions.},
author = {Tondello, Gustavo F. and Mora, Alberto and Marczewski, Andrzej and Nacke, Lennart E.},
doi = {10.1016/j.ijhcs.2018.10.002},
issn = {10715819},
journal = {International Journal of Human-Computer Studies},
keywords = {Gameful Design,Gamification,Hexad,User Types},
publisher = {Elsevier},
title = {{Empirical Validation of the Gamification User Types Hexad Scale in English and Spanish}},
url = {https://doi.org/10.1016/j.ijhcs.2018.10.002},
year = {2019},
volume = {127},
pages = {95--111},
}

Gamification, the use of game elements in non-game systems, is now established as a relevant research field in human-computer interaction (HCI). Several empirical studies have shown that gameful interventions can increase engagement and generate desired behavioural outcomes in HCI applications. However, some inconclusive results indicate that we need a fuller understanding of the mechanisms and effects of gamification. The Gamification User Types Hexad scale allows us to parse different user motivations in participants’ interactions with gameful applications, which are measured using a self-report questionnaire. Each user type represents a style of interaction with gameful applications, for example, if the interactions are more focused on achievements, socialization, or rewards. Thus, by scoring an individual in each one of the user types of the Hexad model, we can establish a profile of user preferences for gameful interactions. However, we still lack a substantial empirical validation of this scale. Therefore, we set out to validate the factor structure of the scale, in both English and Spanish, by conducting three studies, which also investigated the distribution of the Hexad's user types in the sample. Our findings support the structural validity of the scale, as well as suggesting opportunities for improvement. Furthermore, we demonstrate that some user types are more common than others and that gender and age correlate with a person's user types. Our work contributes to HCI research by further validating the utility of the Gamification User Types Hexad scale, potentially affording researchers a deeper understanding of the mechanisms and effects of gameful interventions.

Gameful Design Heuristics: A Gamification Inspection Tool

@inproceedings{Tondello2019a,
author = {Tondello, Gustavo F. and Kappen, Dennis L. and Ganaba, Marim and Nacke, Lennart E.},
booktitle = {{Human-Computer Interaction. Perspectives on Design. Proceedings of HCI International 2019. LNCS 11566}},
publisher = {Springer},
title = {{Gameful Design Heuristics: A Gamification Inspection Tool}},
year = {2019},
doi = {10.1007/978-3-030-22646-6_16}
}

Despite the emergence of many gameful design methodologies in the literature, there is a lack of methods to evaluate the resulting designs. Gameful design techniques aim to increase the user’s motivation to interact with a software, but there are presently no accepted guidelines on how to find out if this goal was achieved during the design phase of a project. This paper presents the Gameful Design Heuristics, a novel set of guidelines that facilitate a heuristic evaluation of gameful software, with a focus on the software’s potential to afford intrinsic and extrinsic motivation for the user. First, we reviewed several gameful design methods to identify the most frequently employed dimensions of motivational affordances. Then, we devised a set of 28 gamification heuristics that can be used to rapidly evaluate a gameful system. Finally, we conducted a summative empirical evaluation study with five user experience professionals, which demonstrated that our heuristics can help the evaluators find more motivational issues in interactive systems than they would without the heuristics. The suggested method fulfills the need for evaluation tools specific to gameful design, which could help evaluators assess the potential user experience of a gameful application in the early phases of a project.

The quest for a better tailoring of gameful design: An analysis of player type preferences

@inproceedings{Mora2019,
abstract = {Gameful systems are often developed using "one size fits all" approaches. However, it would be better to tailor the experience according to each participant's personal preferences. On that regard, player types and game design elements are the main personalization dimensions that have been studied in the literature, even though such studies often lack empirical validation, employing very small or local samples. This paper presents the results of an exploratory study that further investigates user types and preferences for different game design elements. Results show the relationships between gender and age among and between player types as well as how different game design elements influence the participants.},
author = {Mora, Alberto and Tondello, Gustavo F. and Calvet, Laura and Gonz{\'{a}}lez, Carina and Arnedo-Moreno, Joan and Nacke, Lennart E.},
booktitle = {Proceedings of the XX International Conference on Human Computer Interaction - Interacci{\'{o}}n '19},
publisher = {ACM},
title = {{The quest for a better tailoring of gameful design: An analysis of player type preferences}},
year = {2019},
doi = {10.1145/3335595.3335625}
}

Gameful systems are often developed using "one size fits all" approaches. However, it would be better to tailor the experience according to each participant’s personal preferences. On that regard, player types and game design elements are the main personalization dimensions that have been studied in the literature, even though such studies often lack empirical validation, employing very small or local samples. This paper presents the results of an exploratory study that further investigates user types and preferences for different game design elements. Results show the relationships between gender and age among and between player types as well as how different game design elements influence the participants.

“I don't fit into a single type”: A Trait Model and Scale of Game Playing Preferences

@inproceedings{Tondello2019b,
author = {Tondello, Gustavo F. and Arrambide, Karina and Ribeiro, Giovanni and Cen, Andrew and Nacke, Lennart E.},
booktitle = {Proceedings of INTERACT 2019, LNCS 11747},
publisher = {Springer},
title = {{“I don't fit into a single type”: A Trait Model and Scale of Game Playing Preferences}},
year = {2019},
doi = {10.1007/978-3-030-29384-0_23}
}

Player typology models classify different player motivations and behaviours. These models are necessary to design personalized games or to target specific audiences. However, many models lack validation and standard measurement instruments. Additionally, they rely on type theories, which split players into separate categories. Yet, personality research has lately favoured trait theories, which recognize that people's preferences are composed of a sum of different characteristics. Given these shortcomings of existing models, we developed a player traits model built on a detailed review and synthesis of the extant literature, which introduces five player traits: aesthetic orientation, narrative orientation, goal orientation, social orientation, and challenge orientation. Furthermore, we created and validated a 25-item measurement scale for the five player traits. This scale outputs a player profile, which describes participants' preferences for different game elements and game playing styles. Finally, we demonstrate that this is the first validated player preferences model and how it serves as an actionable tool for personalized game design.

Effect of personalized gameful design on student engagement

@inproceedings{Mora2018,
abstract = {Many recent studies of gamification applied to higher education have demonstrated a wide range of positive results. However, most of them fail to consider any personalization factor for the student experience, despite recent studies having shown that gameful systems may be more engaging when they are personalized to each user. Therefore, the goal of this work is to investigate if gameful learning experiences can better motivate and engage students if they are personalized. In this way, we present the design and analysis of a personalized gameful learning experience within a Computer Network Design course. The general purpose of this study is to determine whether a personalized gameful learning experience affects both the students' behavioral and emotional engagement. The results of a descriptive analysis reveal that personalization works better than generic approaches in all items regarding the behavioral and emotional engagement of the students, being a promising standpoint to further investigate in subsequent studies.},
author = {Mora, Alberto and Tondello, Gustavo F and Nacke, Lennart E and Arnedo-Moreno, Joan},
booktitle = {Proceedings of the IEEE Global Engineering Education Conference - EDUCON 2018},
keywords = {Hexad,gameful design,gamification,learning,personalization,preferences},
mendeley-groups = {HCI Games Group Publications},
publisher = {IEEE},
title = {{Effect of personalized gameful design on student engagement}},
year = {2018}
}

Many recent studies of gamification applied to higher education have demonstrated a wide range of positive results. However, most of them fail to consider any personalization factor for the student experience, despite recent studies having shown that gameful systems may be more engaging when they are personalized to each user. Therefore, the goal of this work is to investigate if gameful learning experiences can better motivate and engage students if they are personalized. In this way, we present the design and analysis of a personalized gameful learning experience within a Computer Network Design course. The general purpose of this study is to determine whether a personalized gameful learning experience affects both the students’ behavioral and emotional engagement. The results of a descriptive analysis reveal that personalization works better than generic approaches in all items regarding the behavioral and emotional engagement of the students, being a promising standpoint to further investigate in subsequent studies.

Personalizing Persuasive Strategies in Gameful Systems to Gamification User Types

@inproceedings{Orji2018a,
author = {Orji, Rita and Tondello, Gustavo F and Nacke, Lennart E},
booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI '18},
doi = {doi.org/10.1145/3173574.3174009},
publisher = {ACM},
keywords = {Hexad,Persuasive strategies,behaviour change,gameful design,gamification,personalization,risky health behavior},
title = {{Personalizing Persuasive Strategies in Gameful Systems to Gamification User Types}},
year = {2018}
}

Persuasive gameful systems are effective tools for motivating behaviour change. Research has shown that tailoring these systems to individuals can increase their efficacy; however, there is little knowledge on how to personalize them. We conducted a large-scale study of 543 participants to investigate how different gamification user types responded to ten persuasive strategies depicted in storyboards representing persuasive gameful health systems. Our results reveal that people’s gamification user types play significant roles in the perceived persuasiveness of different strategies. People scoring high in the ‘player’ user type tend to be motivated by competition, comparison, cooperation, and reward while ‘disruptors’ are likely to be demotivated by punishment, goal-setting, simulation, and self-monitoring. ‘Socialisers’ could be motivated using any of the strategies; they are the most responsive to persuasion overall. Finally, we contribute to CHI research and practice by offering design guidelines for tailoring persuasive gameful systems to each gamification user type.

Towards Customizing Gameful Systems by Gameful Design Elements

@inproceedings{Tondello2018c,
abstract = {Recently, several researchers have suggested that personalized game-ful systems can be more effective than generic approaches. However, there is still scarce empirical evidence that the suggested factors for personalization, such as gender, age, user types, and personality traits, will be effective in im-proving user engagement and performance for personalized gameful systems. In this work-in-progress, we present a research plan for empirical evaluation of a customizable gameful system. Upon completion of this study, we expect to pro-vide empirical evidence that the participants' selection of gameful design ele-ments in a practical application will correspond to the theorized relationships suggested by prior survey-based research, and that the system can suggest the gameful design elements that users are more likely to enjoy. The results of this research will provide an actionable path for gamification designers to imple-ment personalized gameful systems and for researchers to develop recommen-dation algorithms for gamification.},
address = {Waterloo, ON, Canada},
author = {Tondello, Gustavo F and Nacke, Lennart E},
booktitle = {International Workshop on Personalizing in Persuasive Technologies (PPT'18)},
keywords = {customization,gameful design,gamification,personalization},
publisher = {CEUR-WS.org},
title = {{Towards Customizing Gameful Systems by Gameful Design Elements}},
url = {http://ceur-ws.org/Vol-2089/11{\_}Tondello.pdf},
year = {2018}
}

Recently, several researchers have suggested that personalized game-ful systems can be more effective than generic approaches. However, there is still scarce empirical evidence that the suggested factors for personalization, such as gender, age, user types, and personality traits, will be effective in im-proving user engagement and performance for personalized gameful systems. In this work-in-progress, we present a research plan for empirical evaluation of a customizable gameful system. Upon completion of this study, we expect to pro-vide empirical evidence that the participants’ selection of gameful design ele-ments in a practical application will correspond to the theorized relationships suggested by prior survey-based research, and that the system can suggest the gameful design elements that users are more likely to enjoy. The results of this research will provide an actionable path for gamification designers to imple-ment personalized gameful systems and for researchers to develop recommen-dation algorithms for gamification.

Towards a Trait Model of Video Game Preferences

@article{Tondello2018d,
abstract = {Typologies for understanding players' preferences towards different gameplay styles have gained popularity in research. However, attempts to model players' preferences are based on type models instead of trait models, contrary to the latest personality research. One such model, BrainHex, was designed as an interim model to enable investigations towards a definitive player trait model. However, it lacks empirical validation in support of its psychometric properties. The present work analysed a dataset with over 50,000 respondents to devise a player traits model based off the BrainHex scale. Results indicate three player traits: action, aesthetic, and goal orientation. Furthermore, we analysed the games listed by participants as examples of what they enjoy, to understand which factors influence player preferences. Results illustrate that the emergent player traits and participants' genders and attitudes towards story can partially explain player preferences towards certain games. Finally, we present the implications towards a definitive player traits model.},
author = {Tondello, Gustavo F. and Valtchanov, Deltcho and Reetz, Adrian and Wehbe, Rina R. and Orji, Rita and Nacke, Lennart E.},
doi = {10.1080/10447318.2018.1461765},
journal = {International Journal of Human-Computer Interaction},
keywords = {BrainHex,Games,Games User Research,Motivation,Player Traits,Player Typology,Scale Design},
title = {{Towards a Trait Model of Video Game Preferences}},
volume = {34},
number = {8},
pages = {732--748},
year = {2018}
}

Typologies for understanding players’ preferences toward different gameplay styles have gained popularity in research. However, attempts to model players’ preferences are based on type models instead of trait models, contrary to the latest personality research. One such model, BrainHex, was designed as an interim model to enable investigations toward a definitive player trait model. However, it lacks empirical validation in support of its psychometric properties. The present work analyzed a dataset with over 50,000 respondents to devise a player traits model based off the BrainHex scale. Results indicate three player traits: action, esthetic, and goal orientation. Furthermore, we analyzed the games listed by participants as examples of what they enjoy, to understand which factors influence player preferences. Results illustrate that the emergent player traits and participants’ genders and attitudes toward story can partially explain player preferences toward certain games. Finally, we present the implications toward a definitive player traits model.

Applying Gameful Design Heuristics

@inproceedings{Tondello2017,
abstract = {To evaluate gameful apps and games, we have recently developed a new set of guidelines for heuristic evaluation of gameful design in interactive systems, supporting the quickly growing gamification research area. Our set of 28 gamification heuristics allows rapid evaluation of a gameful system. This course will supply attendees with our gameful design heuristics and train them in using the heuristics on an example application (Duolingo). The course is structured into two 80-minute units, which will give the participants enough time to learn the new heuristics and apply them to the gamified application. Finally, at the end of the second unit, we will be discussing how to generate design ideas with the heuristics. The course instructors, Gustavo Tondello and Lennart Nacke, have both developed the gameful design heuristics and have experience in designing and evaluating gamified applications and teaching courses.},
address = {Denver, CO, USA},
author = {Tondello, Gustavo F and Nacke, Lennart E},
booktitle = {Proceeding of the 2017 ACM Conference on Human Factors in Computing Systems},
doi = {10.1145/3027063.3027116},
isbn = {9781450346566},
keywords = {Gameful Design,Gamification,Heuristics},
publisher = {ACM},
title = {{Applying Gameful Design Heuristics}},
year = {2017}
}

To evaluate gameful apps and games, we have recently developed a new set of guidelines for heuristic evaluation of gameful design in interactive systems, supporting the quickly growing gamification research area. Our set of 28 gamification heuristics allows rapid evaluation of a gameful system. This course will supply attendees with our gameful design heuristics and train them in using the heuristics on an example application (Duolingo). The course is structured into two 80-minute units, which will give the participants enough time to learn the new heuristics and apply them to the gamified application. Finally, at the end of the second unit, we will be discussing how to generate design ideas with the heuristics. The course instructors, Gustavo Tondello and Lennart Nacke, have both developed the gameful design heuristics and have experience in designing and evaluating gamified applications and teaching courses.

Elements of Gameful Design Emerging from User Preferences

@inproceedings{Tondello2017c,
abstract = {Several studies have developed models to explain player preferences. These models have been developed for digital games; however, they have been frequently applied in gameful design (i.e., designing non-game applications with game elements) without empirical validation of their fit to this different context. It is not clear if users experience game elements embedded in applications similarly to how players experience them in games. Consequently, we still lack a conceptual framework of design elements built specifically for a gamification context. To fill this gap, we propose a classification of eight groups of gameful design elements produced from an exploratory factor analysis based on participants' self-reported preferences. We describe the characteristics of the users who are more likely to enjoy each group of design elements in terms of their gender, age, gamification user type, and personality traits. Our main contribution is providing an overview of which design elements work best for what demographic clusters and how we can apply this knowledge to design effective gameful systems.},
address = {Amsterdam, Netherlands},
author = {Tondello, Gustavo F. and Mora, Alberto and Nacke, Lennart E.},
booktitle = {Proceedings of the 2017 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY '17},
doi = {10.1145/3116595.3116627},
isbn = {9781450348980},
keywords = {Game Design Elements,Gameful Design,Games User Research,Gamification,Types,User},
publisher = {ACM},
title = {{Elements of Gameful Design Emerging from User Preferences}},
year = {2017}
}

Several studies have developed models to explain player preferences. These models have been developed for digital games; however, they have been frequently applied in gameful design (i.e., designing non-game applications with game elements) without empirical validation of their fit to this different context. It is not clear if users experience game elements embedded in applications similarly to how players experience them in games. Consequently, we still lack a conceptual framework of design elements built specifically for a gamification context. To fill this gap, we propose a classification of eight groups of gameful design elements produced from an exploratory factor analysis based on participants’ self-reported preferences. We describe the characteristics of the users who are more likely to enjoy each group of design elements in terms of their gender, age, gamification user type, and personality traits. Our main contribution is providing an overview of which design elements work best for what demographic clusters and how we can apply this knowledge to design effective gameful systems.

Gamified and Persuasive Systems as Behavior Change Agents for Health and Wellness

@article{Kappen2017b,
author = {Kappen, Dennis L. and Orji, Rita},
doi = {10.1145/3123750},
issn = {15284972},
journal = {XRDS: Crossroads, The ACM Magazine for Students},
mendeley-groups = {HCI Games Group Publications},
number = {1},
pages = {52--55},
title = {{Gamified and Persuasive Systems as Behavior Change Agents for Health and Wellness}},
url = {http://dl.acm.org/citation.cfm?doid=3140569.3123750},
volume = {24},
year = {2017}
}

Recommender Systems for Personalized Gamification

@inproceedings{Tondello2017a,
abstract = {Gamification has been used in a variety of application domains to promote behaviour change. Nevertheless, the mechanisms behind it are still not fully understood. Recent empirical results have shown that personalized approaches can potentially achieve better results than generic approaches. However, we still lack a general framework for building personalized gameful applications. To address this gap, we present a novel general framework for personalized gameful applications using recommender systems (i.e., software tools and technologies to recommend suggestions to users that they might enjoy). This framework contributes to understanding and building effective persuasive and gameful applications by describing the different building blocks of a recommender system (users, items, and transactions) in a personalized gamification context.},
address = {Bratislava, Slovakia},
author = {Tondello, Gustavo F. and Orji, Rita and Nacke, Lennart E.},
booktitle = {Proceedings of UMAP'17 Adjunct},
doi = {10.1145/3099023.3099114},
isbn = {9781450350679},
keywords = {Gamification,Personalization,Recommender Systems},
publisher = {ACM},
title = {{Recommender Systems for Personalized Gamification}},
year = {2017}
}

Gamification has been used in a variety of application domains to promote behaviour change. Nevertheless, the mechanisms behind it are still not fully understood. Recent empirical results have shown that personalized approaches can potentially achieve better results than generic approaches. However, we still lack a general framework for building personalized gameful applications. To address this gap, we present a novel general framework for personalized gameful applications using recommender systems (i.e., software tools and technologies to recommend suggestions to users that they might enjoy). This framework contributes to understanding and building effective persuasive and gameful applications by describing the different building blocks of a recommender system (users, items, and transactions) in a personalized gamification context.

Towards Personality-driven Persuasive Health Games and Gamified Systems

@inproceedings{Orji2017,
abstract = {Persuasive games and gamified systems are effective tools for motivating behavior change using various persuasive strategies. Research has shown that tailoring these systems can increase their efficacy. However, there is little knowledge on how game-based persuasive systems can be tailored to individuals of various personality traits. To advance research in this area, we conducted a large-scale study of 660 participants to investigate how different personalities respond to various persuasive strategies that are used in persuasive health games and gamified systems. Our results reveal that people's personality traits play a significant role in the perceived persuasiveness of different strategies. Conscientious people tend to be motivated by goal setting, simulation, self-monitoring and feedback; people who are more open to experience are more likely to be demotivated by rewards, competition, comparison, and cooperation. We contribute to the CHI community by offering design guidelines for tailoring persuasive games and gamified designs to a particular group of personalities.},
author = {Orji, Rita and Nacke, Lennart E. and DiMarco, Chrysanne},
booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
doi = {10.1145/3025453.3025577},
isbn = {9781450346559},
publisher = {ACM},
title = {{Towards Personality-driven Persuasive Health Games and Gamified Systems}},
year = {2017}
}

Persuasive games and gamified systems are effective tools for motivating behavior change using various persuasive strategies. Research has shown that tailoring these systems can increase their efficacy. However, there is little knowledge on how game-based persuasive systems can be tailored to individuals of various personality traits. To advance research in this area, we conducted a large-scale study of 660 participants to investigate how different personalities respond to various persuasive strategies that are used in persuasive health games and gamified systems. Our results reveal that people’s personality traits play a significant role in the perceived persuasiveness of different strategies. Conscientious people tend to be motivated by goal setting, simulation, self-monitoring and feedback; people who are more open to experience are more likely to be demotivated by rewards, competition, comparison, and cooperation. We contribute to the CHI community by offering design guidelines for tailoring persuasive games and gamified designs to a particular group of personalities.

Heuristic Evaluation for Gameful Design

@inproceedings{Tondello2016a,
Abstract = {Despite the emergence of many gameful design methods in the literature, there is a lack of evaluation methods specific to gameful design. To address this gap, we present a new set of guidelines for heuristic evaluation of gameful design in interactive systems. First, we review several gameful design methods to identify the dimensions of motivational affordances most often employed. Then, we present a set of 28 gamification heuristics aimed at enabling experts to rapidly evaluate a gameful system. The resulting heuristics are a new method to evaluate user experience in gameful interactive systems.},
Address = {Austin, TX, USA},
Author = {G. F. Tondello, D. L. Kappen, E. D. Mekler, M. Ganaba, and L. E. Nacke},
Booktitle = {Proceedings of the 2016 annual symposium on computer-human interaction in play extended abstracts - chi play ea '16},
Doi = {10.1145/2968120.2987729},
File = {::},
Img = {http://hcigames.com/wp-content/uploads/2016/08/ratings.png},
Keywords = {Heuristic Evaluation, Gamification, Gameful Design},
Publisher = {ACM},
Title = {Heuristic Evaluation for Gameful Design},
Url = {https://hcigames.com/download/heuristic-evaluation-for-gameful-design},
Year = {2016},

Despite the emergence of many gameful design methods in the literature, there is a lack of evaluation methods specific to gameful design. To address this gap, we present a new set of guidelines for heuristic evaluation of gameful design in interactive systems. First, we review several gameful design methods to identify the dimensions of motivational affordances most often employed. Then, we present a set of 28 gamification heuristics aimed at enabling experts to rapidly evaluate a gameful system. The resulting heuristics are a new method to evaluate user experience in gameful interactive systems.

The Gamification User Types Hexad Scale

@inproceedings{Tondello2016,
abstract = {Several studies have indicated the need for personalizing gamified systems to users' personalities. However, mapping user personality onto design elements is difficult. Hexad is a gamification user types model that attempts this mapping but lacks a standard procedure to assess user preferences. Therefore, we created a 24-items survey response scale to score users' preferences towards the six different motivations in the Hexad framework. We used internal and test-retest reliability analysis, as well as factor analysis, to validate this new scale. Further analysis revealed significant associations of the Hexad user types with the Big Five personality traits. In addition, a correlation analysis confirmed the framework's validity as a measure of user preference towards different game design elements. This scale instrument contributes to games user research because it enables accurate measures of user preference in gamification.},
address = {Austin, TX, USA},
author = {Tondello, Gustavo F. and Wehbe, Rina R. and Diamond, Lisa and Busch, Marc and Marczewski, Andrzej and Nacke, Lennart E.},
booktitle = {Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY '16},
doi = {10.1145/2967934.2968082},
file = {:C$\backslash$:/Users/Gustavo/Google Drive/HCI Games Group Documents/Projects and Papers/Gamification player types/Hexad Validation Paper/The Gamification User Types Hexad Scale-Camera Ready.pdf:pdf},
keywords = {Gameful Design,Gamification,Hexad,User Types},
mendeley-groups = {HCI Games Group Publications},
publisher = {ACM},
title = {{The Gamification User Types Hexad Scale}},
year = {2016}
}

Several studies have indicated the need for personalizing gamified systems to users' personalities. However, mapping user personality onto design elements is difficult. Hexad is a gamification user types model that attempts this mapping but lacks a standard procedure to assess user preferences. Therefore, we created a 24-items survey response scale to score users' preferences towards the six different motivations in the Hexad framework. We used internal and test-retest reliability analysis, as well as factor analysis, to validate this new scale. Further analysis revealed significant associations of the Hexad user types with the Big Five personality traits. In addition, a correlation analysis confirmed the framework's validity as a measure of user preference towards different game design elements. This scale instrument contributes to games user research because it enables accurate measures of user preference in gamification.

The HEXAD Gamification User Types Questionnaire : Background and Development Process

@inproceedings{Diamond2015,
Abstract = {The HEXAD gamification user types are attempting a segmentation of users based on their receptivity to varying gamification strategies. The underlying model is based on research on human motivation, player types, and years of practical design experiences. This model presents the first typology to classify users of gamified systems, enabling clustering them based on intrinsic and extrinsic motivational factors. The HEXAD model is comprised of the following six gamification user types: Socializers, Free Spirits, Achievers, Philanthropists, Players, and Disruptors. We have developed a questionnaire to assess how a user is represented by the different gamification user types. The following paper will present the development process of the questionnaire. Application venues will be discussed.},
Address = {London, UK},
Author = {L. Diamond, G. F. Tondello, A. Marczewski, L. E. Nacke, and M. Tscheligi},
Booktitle = {Workshop on personalization in serious and persuasive games and gamified interactions},
File = {::},
Img = {http://hcigames.com/wp-content/uploads/2015/10/Gamification-User-Types-Hexad-150.png},
Keywords = {Gamification,Intrinsic and Extrinsic Motivation,Personalization,Questionnaire,User Segmentation/Classification/Typology},
Title = {The HEXAD Gamification User Types Questionnaire : Background and Development Process},
Url = {https://hcigames.com/download/the-hexad-gamification-user-types-questionnaire-background-and-development-process},
Year = {2015},

The HEXAD gamification user types are attempting a segmentation of users based on their receptivity to varying gamification strategies. The underlying model is based on research on human motivation, player types, and years of practical design experiences. This model presents the first typology to classify users of gamified systems, enabling clustering them based on intrinsic and extrinsic motivational factors. The HEXAD model is comprised of the following six gamification user types: Socializers, Free Spirits, Achievers, Philanthropists, Players, and Disruptors. We have developed a questionnaire to assess how a user is represented by the different gamification user types. The following paper will present the development process of the questionnaire. Application venues will be discussed.

Towards a Personalized Playful Digital Wellness Assistant

@inproceedings{Tondello2015b,
Abstract = {Positive effects of using digital games to improve personal health have been studied, but it remains unclear which game design techniques are most successful at motivating and changing long-term behaviour to improve wellbeing. To inform the design of gamified and effective personal healthcare, we will develop design guidelines and tools for gameful health and wellbeing applications, personalized to the needs and challenges of each individual user.},
Address = {London, UK},
Author = {G. F. Tondello, R. R. Wehbe, and L. E. Nacke},
Booktitle = {Workshop on personalization in serious and persuasive games and gamified interactions},
File = {::},
Img = {http://hcigames.com/wp-content/uploads/2015/10/squash-793062_640.jpg},
Keywords = {Adaptive Systems,Health Games,Personal Assistant,Personalization,Persuasive Technologies,Wellness},
Title = {Towards a Personalized Playful Digital Wellness Assistant},
Url = {https://hcigames.com/download/towards-a-personalized-playful-digital-wellness-assistant},
Year = {2015},

Positive effects of using digital games to improve personal health have been studied, but it remains unclear which game design techniques are most successful at motivating and changing long-term behaviour to improve wellbeing. To inform the design of gamified and effective personal healthcare, we will develop design guidelines and tools for gameful health and wellbeing applications, personalized to the needs and challenges of each individual user.