These are the slides of my Ph.D. thesis oral defence at the University of Waterloo on June 20, 2019.
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 the task, can influence gamification outcomes.
Given how user qualities shape the gameful experience, it is important to understand how to personalize gameful systems. 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 this kind of system, 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 method for personalized gameful design with three steps: (1) classification of user preferences, (2) classification and selection of gameful design elements, and (3) heuristic evaluation of the design.
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.
Several research studies have been showing that personalized gameful solutions can lead to higher engagement and performance. However, personalized gameful design faces two challenges: deciding how to select game elements and activities that are appealing to different users, and deciding how to adapt the experience to each user. In this talk, Gustavo reports on the latest research and his own experience designing personalized gameful solutions. To solve the first challenge (design), he will show how to use the classification of gameful design elements, the gameful design heuristics, and the user types models to create solutions that are appealing to different users. For the second challenge (adaptation), he will discuss strategies for customization (letting the user adjust their experience at will) or personalization (having the system automatically learn about the user and make adjustments).
Keynote presented at Gamification Europe 2020.
In gameful design, motivational affordances are often used to facilitate intrinsic and extrinsic motivations. This presentation details the 12 dimensions of motivational affordances according to the Gameful Design Heuristics by the HCI Games Group.
Introduction to Gameful Design Heuristics (CHI 2017)Gustavo Tondello
Part 1/2 of CHI 2017 course "Applying Gameful Design Heuristics". This course will supply attendees with our gameful design heuristics and train them in using the heuristics on an example application. Finally, at the end of the second unit, we
will be discussing how to generate design ideas with the heuristics.
A Theory of Gamification Principles Through Goal-Setting TheoryGustavo Tondello
Goal setting theory has been used for decades to explain how to motivate people to perform better in work related tasks, but more recently gamification has also gained attention as an alternative method to increase employee engagement and performance at work. However, despite goal setting and feedback being at the core of gameful implementations, there is a lack of literature explaining how gamification works through the lens of goal setting theory or suggesting how goal setting concepts and recommendations can be employed to improve gameful systems. Therefore, we present a conceptual framework that establishes a relationship between the goal setting concepts and gamification concepts and mechanisms. Next, we describe how this framework can help explain the mechanisms behind gamification and suggest potential improvements to current gameful design methods. Finally, we propose directions for future empirical research aimed to apply this conceptual framework in practice.
Do all users equally enjoy all game elements in gamification?
This talk presents the Hexad user types survey and the game elements correlated with each one of the six Hexad user types.
Presented at the ACM CHI PLAY 2016 Conference.
A Framework and Taxonomy of Videogame Playing Preferences (CHI PLAY 17)Gustavo Tondello
We propose a conceptual framework of player preferences based on two dimensions: game elements and game playing styles. To investigate these two concepts, we conducted an online survey of player preferences, which allowed us to create a taxonomy of nine groups of game elements and five groups of game playing styles. These two concepts are foundational to games, which means that our model can be used by designers to create games that are tailored to their target audience.
Graphics Interface 2019: Invited Speaker: Lennart Nacke - Game ThinkingLennart Nacke
In this talk, Lennart will explain how game thinking works as a problem-solving strategy and provide practical takeaways for designers who are interested in using game thinking in their UX process. He will also talk about his most recent research into gameful design, player types, and surveys and heuristics to assess gamification.
An Introduction to what gamification is. Examples of gamification applications, platforms, and methods.
I put these slides together for a lecture I've given at the University of Waterloo, July 2016.
Several research studies have been showing that personalized gameful solutions can lead to higher engagement and performance. However, personalized gameful design faces two challenges: deciding how to select game elements and activities that are appealing to different users, and deciding how to adapt the experience to each user. In this talk, Gustavo reports on the latest research and his own experience designing personalized gameful solutions. To solve the first challenge (design), he will show how to use the classification of gameful design elements, the gameful design heuristics, and the user types models to create solutions that are appealing to different users. For the second challenge (adaptation), he will discuss strategies for customization (letting the user adjust their experience at will) or personalization (having the system automatically learn about the user and make adjustments).
Keynote presented at Gamification Europe 2020.
In gameful design, motivational affordances are often used to facilitate intrinsic and extrinsic motivations. This presentation details the 12 dimensions of motivational affordances according to the Gameful Design Heuristics by the HCI Games Group.
Introduction to Gameful Design Heuristics (CHI 2017)Gustavo Tondello
Part 1/2 of CHI 2017 course "Applying Gameful Design Heuristics". This course will supply attendees with our gameful design heuristics and train them in using the heuristics on an example application. Finally, at the end of the second unit, we
will be discussing how to generate design ideas with the heuristics.
A Theory of Gamification Principles Through Goal-Setting TheoryGustavo Tondello
Goal setting theory has been used for decades to explain how to motivate people to perform better in work related tasks, but more recently gamification has also gained attention as an alternative method to increase employee engagement and performance at work. However, despite goal setting and feedback being at the core of gameful implementations, there is a lack of literature explaining how gamification works through the lens of goal setting theory or suggesting how goal setting concepts and recommendations can be employed to improve gameful systems. Therefore, we present a conceptual framework that establishes a relationship between the goal setting concepts and gamification concepts and mechanisms. Next, we describe how this framework can help explain the mechanisms behind gamification and suggest potential improvements to current gameful design methods. Finally, we propose directions for future empirical research aimed to apply this conceptual framework in practice.
Do all users equally enjoy all game elements in gamification?
This talk presents the Hexad user types survey and the game elements correlated with each one of the six Hexad user types.
Presented at the ACM CHI PLAY 2016 Conference.
A Framework and Taxonomy of Videogame Playing Preferences (CHI PLAY 17)Gustavo Tondello
We propose a conceptual framework of player preferences based on two dimensions: game elements and game playing styles. To investigate these two concepts, we conducted an online survey of player preferences, which allowed us to create a taxonomy of nine groups of game elements and five groups of game playing styles. These two concepts are foundational to games, which means that our model can be used by designers to create games that are tailored to their target audience.
Graphics Interface 2019: Invited Speaker: Lennart Nacke - Game ThinkingLennart Nacke
In this talk, Lennart will explain how game thinking works as a problem-solving strategy and provide practical takeaways for designers who are interested in using game thinking in their UX process. He will also talk about his most recent research into gameful design, player types, and surveys and heuristics to assess gamification.
An Introduction to what gamification is. Examples of gamification applications, platforms, and methods.
I put these slides together for a lecture I've given at the University of Waterloo, July 2016.
Games institute: University of California Visit: Game Thinking OverviewLennart Nacke
Game Thinking slides for a research visit from the University of California to the Game Insitute at the University of Waterloo to support international research connections and collaborations.
GAMES USER RESEARCH: Guest Lecture in UX Design Class at Wilfried Laurier Uni...Lennart Nacke
In this talk, I describe several games user research methods from the Oxford University Press book: Games User Research. I talk about UX maturity levels of game development companies and the game design iterative development cycle and where Game UX fits into that space. I finally present several games user research methods.
GAMIFIN 2019 Conference Keynote: How to fail at #gamification researchLennart Nacke
Lennart Nacke describes the many ways that failure is important and necessary for iterative design and development of gamification research. He outlines several ways that current gamification research can improve on experiments, execution, and publication of gamification studies. He touches on areas of game thinking, user experience, and design to tie all the examples of failure together into a call for honest design and research in gamification.
Gender Differences in Digital Literacy Games: Efficacy, Strategies, Experienc...ADVANCE-Purdue
In the use of digital technologies, it has been suggested that females are sometimes in a disadvantageous position compared to males due to their lack of confidence, interest and skills. This disadvantage manifests itself in lower levels of digital literacy. Theory of flow (Csikszentmihalyi & Csikszentmihalyi, 2000) and social cognitive theory (Bandura, 1986) suggest that the positive experiences individuals have in a gaming environment might increase interest in digital technologies, and improve skills and usage of digital technologies. The purpose of this paper was hence twofold: to understand gender differences in the process and outcomes of engaging with a game that challenges the participants’ skills and knowledge on digital literacy, and to test the efficacy of learning games in the context of digital literacy. We empirically studied 77 college seniors who were enrolled in a communication and technology class. Results showed no gender differences in terms of self-efficacy in using digital technologies, game performance or enjoyment of the digital literacy game. However, there were gender differences in participants’ description of their cognitive experiences, in the strategies they employed during gameplay, and their perceived learning outcomes. Results of this study challenged the literature in gender gap in observed digital literacy skills, and showed the significant differences in experiences and strategies employed by males and females to achieve similar scores. This study also proposed that helping females explore their cognitive game strategies may enhance sense of mastery and self-efficacy, and encourage females to engage in digital technologies in the future.
Introduction to Game Thinking (Fluxible 2018)Lennart Nacke
Game thinking is a problem-solving process that uses strategies from game design and gamification to help drive the design of user experiences in digital or non-digital applications. Incorporating game thinking into the UX process can 1) foster users’ intrinsic and extrinsic motivations to engage with a product or system, and 2) engage users in a learning and mastery process, in which they develop the abilities needed to accomplish their goals throughout their user journey.
Game Engines in Game Education: Thinking Inside the Tool Boox?Sebastian Deterding
Should apprentices of a craft master one tool, making themselves dependent on it? Or become fluent in many? Should they use pre-made parts? Or should they learn how to make everything from scratch, even if that doesn't reflect actual practice? These eternal questions of craft education have become relevant for game educators with the rise of game engines like Unity. This talk will reveal firsthand experiences and strategies used to deal with the opportunities and challenges of integrating game engines in game education. / My and Casey O'Donnell's talk at the GDC Education Summit 2016.
Evaluation of heuristics for designing believability in games gameon2013Magnus Johansson
Presentation held at the GameOn 2013 conference in Brussels.
We introduce a specific focus for heuristic evaluations of games, where the interface can be excluded and the gameplay isolated.
The heuristics used in this article are based on heuristics sited as the most used heuristics of the game industry
Designing Data Driven Persuasive Games to Address Wicked Problems such as Cli...Adrian Gradinar
This research considers the increasing utilisation of games design as an approach to encouraging behavioural change through design. In particular it considers how to address issues that cannot be reduced to easily actionable personal goals such as climate change and are often termed ‘wicked problems’ by designers due to their innate complexity. This paper presents a research through design approach that focuses on rhetoric within the design of a mobile phone game - Cold Sun. Thus the aim is not to examine the utility or usability of the game but rather offer it as an example of a design approach we believe is desirable and productive for future practice. Cold Sun provides an example that illustrates how scientific and real world data can be integrated into game mechanics to enhance the rhetoric of the game by engaging the player at a more personal level. Thus Cold Sun allows players to effectively rehearse issues of climate change that will affect their plausible futures, and thus develop a greater understanding of some of these complex issues and consider ways to respond.
Cognitive Systems Institute Group Speaker Series talk by Franz Dill on "Gamification and Cognitive Systems; Opportunities for Enhancing and Defining Jobs." To listen to a replay of this talk, go to this page http://cognitive-science.info/community/weekly-update/ If you'd like to be added to the invitation for this weekly series call, please contact fodell@us.ibm.com
Controlling Adaptation in Affective Serious Gamesbbontchev
Managing the adaptation in affective serious
games is established mainly on the basis of player emotions.
Emotions can be recognized by analyzing physiological data and
facial expressions of the individual player. While physiological
data provide information about the measurement time, electrodermal
activity, pulse, temperature, neural activity, etc., facial
expressions are a source of data about the emotion extracted
from images. The presentation outlines s a general workflow of game
adaptation control in affective games applying emotional state,
game outcomes and efficiency, and playing style. It provides
preliminary results received by using clustering algorithms for
recognizing emotions from physiological data and by applying a
convolutional neural network using images to recognize
emotions from facial expressions.
I gave this talk at the 2015 Distance Teaching & Learning conference. The format was a 10 minute speed talk. It covers the basics of using gamification in formal learning environments, with an emphasis on classroom learning.
In the last few years, we have witnessed a true revolution in the video-game industry, as both traditional video-game platforms and emerging mobile games have become always connected to the Internet. This has contributed to widen the audience for video games (casual gamers) and to the appearance of new economic models (in-app purchases, free-to-play) that are gaining more and more importance in a sector traditionally monetized by expensive one-time purchases or subscriptions.
More importantly, this recent paradigm shift allows game developers to collect a huge amount of data in real time while maintaining an active relationship with the players. This has created a broad range of new challenges and opportunities for both data science research and business applications, as demonstrated by the quickly growing number of job openings for data scientists in game companies. To fully take advantage of this new scenario, it is paramount to develop adequate statistical and learning methods that model and predict player behavior, scale to large datasets and allow an intuitive visualization of the results.
In this talk, I will survey the state-of-the-art of Data Science in the mobile game industry. First, I will present a general summary of the main techniques to predict player behavior, concentrating on those learning methods that help to reduce user attrition, i.e. churn, which is decisive to increase player retention and raise revenues.
Then, I will discuss these techniques from the viewpoint of Game Data Science as a Service. The goal of Silicon Studio is to democratize Game Data Science. Hence, I will show how the proposed methods can make predictions in an operational business environment and easily adapt to different kinds of games and players—namely, to different data distributions. I will focus on flexible techniques that do not need previous manipulation of the data and are able to deal efficiently with the temporal dimension of the churn-prediction problem.
Game features of cognitive training (Michael P. Craven and Carlo Fabricatore)
Interactive Technologies and Games (ITAG) Conference 2016
Health, Disability and EducationDates: Wednesday 26 October 2016 - Thursday 27 October 2016 Location: The Council House, NG1 2DT
Games institute: University of California Visit: Game Thinking OverviewLennart Nacke
Game Thinking slides for a research visit from the University of California to the Game Insitute at the University of Waterloo to support international research connections and collaborations.
GAMES USER RESEARCH: Guest Lecture in UX Design Class at Wilfried Laurier Uni...Lennart Nacke
In this talk, I describe several games user research methods from the Oxford University Press book: Games User Research. I talk about UX maturity levels of game development companies and the game design iterative development cycle and where Game UX fits into that space. I finally present several games user research methods.
GAMIFIN 2019 Conference Keynote: How to fail at #gamification researchLennart Nacke
Lennart Nacke describes the many ways that failure is important and necessary for iterative design and development of gamification research. He outlines several ways that current gamification research can improve on experiments, execution, and publication of gamification studies. He touches on areas of game thinking, user experience, and design to tie all the examples of failure together into a call for honest design and research in gamification.
Gender Differences in Digital Literacy Games: Efficacy, Strategies, Experienc...ADVANCE-Purdue
In the use of digital technologies, it has been suggested that females are sometimes in a disadvantageous position compared to males due to their lack of confidence, interest and skills. This disadvantage manifests itself in lower levels of digital literacy. Theory of flow (Csikszentmihalyi & Csikszentmihalyi, 2000) and social cognitive theory (Bandura, 1986) suggest that the positive experiences individuals have in a gaming environment might increase interest in digital technologies, and improve skills and usage of digital technologies. The purpose of this paper was hence twofold: to understand gender differences in the process and outcomes of engaging with a game that challenges the participants’ skills and knowledge on digital literacy, and to test the efficacy of learning games in the context of digital literacy. We empirically studied 77 college seniors who were enrolled in a communication and technology class. Results showed no gender differences in terms of self-efficacy in using digital technologies, game performance or enjoyment of the digital literacy game. However, there were gender differences in participants’ description of their cognitive experiences, in the strategies they employed during gameplay, and their perceived learning outcomes. Results of this study challenged the literature in gender gap in observed digital literacy skills, and showed the significant differences in experiences and strategies employed by males and females to achieve similar scores. This study also proposed that helping females explore their cognitive game strategies may enhance sense of mastery and self-efficacy, and encourage females to engage in digital technologies in the future.
Introduction to Game Thinking (Fluxible 2018)Lennart Nacke
Game thinking is a problem-solving process that uses strategies from game design and gamification to help drive the design of user experiences in digital or non-digital applications. Incorporating game thinking into the UX process can 1) foster users’ intrinsic and extrinsic motivations to engage with a product or system, and 2) engage users in a learning and mastery process, in which they develop the abilities needed to accomplish their goals throughout their user journey.
Game Engines in Game Education: Thinking Inside the Tool Boox?Sebastian Deterding
Should apprentices of a craft master one tool, making themselves dependent on it? Or become fluent in many? Should they use pre-made parts? Or should they learn how to make everything from scratch, even if that doesn't reflect actual practice? These eternal questions of craft education have become relevant for game educators with the rise of game engines like Unity. This talk will reveal firsthand experiences and strategies used to deal with the opportunities and challenges of integrating game engines in game education. / My and Casey O'Donnell's talk at the GDC Education Summit 2016.
Evaluation of heuristics for designing believability in games gameon2013Magnus Johansson
Presentation held at the GameOn 2013 conference in Brussels.
We introduce a specific focus for heuristic evaluations of games, where the interface can be excluded and the gameplay isolated.
The heuristics used in this article are based on heuristics sited as the most used heuristics of the game industry
Designing Data Driven Persuasive Games to Address Wicked Problems such as Cli...Adrian Gradinar
This research considers the increasing utilisation of games design as an approach to encouraging behavioural change through design. In particular it considers how to address issues that cannot be reduced to easily actionable personal goals such as climate change and are often termed ‘wicked problems’ by designers due to their innate complexity. This paper presents a research through design approach that focuses on rhetoric within the design of a mobile phone game - Cold Sun. Thus the aim is not to examine the utility or usability of the game but rather offer it as an example of a design approach we believe is desirable and productive for future practice. Cold Sun provides an example that illustrates how scientific and real world data can be integrated into game mechanics to enhance the rhetoric of the game by engaging the player at a more personal level. Thus Cold Sun allows players to effectively rehearse issues of climate change that will affect their plausible futures, and thus develop a greater understanding of some of these complex issues and consider ways to respond.
Cognitive Systems Institute Group Speaker Series talk by Franz Dill on "Gamification and Cognitive Systems; Opportunities for Enhancing and Defining Jobs." To listen to a replay of this talk, go to this page http://cognitive-science.info/community/weekly-update/ If you'd like to be added to the invitation for this weekly series call, please contact fodell@us.ibm.com
Controlling Adaptation in Affective Serious Gamesbbontchev
Managing the adaptation in affective serious
games is established mainly on the basis of player emotions.
Emotions can be recognized by analyzing physiological data and
facial expressions of the individual player. While physiological
data provide information about the measurement time, electrodermal
activity, pulse, temperature, neural activity, etc., facial
expressions are a source of data about the emotion extracted
from images. The presentation outlines s a general workflow of game
adaptation control in affective games applying emotional state,
game outcomes and efficiency, and playing style. It provides
preliminary results received by using clustering algorithms for
recognizing emotions from physiological data and by applying a
convolutional neural network using images to recognize
emotions from facial expressions.
I gave this talk at the 2015 Distance Teaching & Learning conference. The format was a 10 minute speed talk. It covers the basics of using gamification in formal learning environments, with an emphasis on classroom learning.
In the last few years, we have witnessed a true revolution in the video-game industry, as both traditional video-game platforms and emerging mobile games have become always connected to the Internet. This has contributed to widen the audience for video games (casual gamers) and to the appearance of new economic models (in-app purchases, free-to-play) that are gaining more and more importance in a sector traditionally monetized by expensive one-time purchases or subscriptions.
More importantly, this recent paradigm shift allows game developers to collect a huge amount of data in real time while maintaining an active relationship with the players. This has created a broad range of new challenges and opportunities for both data science research and business applications, as demonstrated by the quickly growing number of job openings for data scientists in game companies. To fully take advantage of this new scenario, it is paramount to develop adequate statistical and learning methods that model and predict player behavior, scale to large datasets and allow an intuitive visualization of the results.
In this talk, I will survey the state-of-the-art of Data Science in the mobile game industry. First, I will present a general summary of the main techniques to predict player behavior, concentrating on those learning methods that help to reduce user attrition, i.e. churn, which is decisive to increase player retention and raise revenues.
Then, I will discuss these techniques from the viewpoint of Game Data Science as a Service. The goal of Silicon Studio is to democratize Game Data Science. Hence, I will show how the proposed methods can make predictions in an operational business environment and easily adapt to different kinds of games and players—namely, to different data distributions. I will focus on flexible techniques that do not need previous manipulation of the data and are able to deal efficiently with the temporal dimension of the churn-prediction problem.
Game features of cognitive training (Michael P. Craven and Carlo Fabricatore)
Interactive Technologies and Games (ITAG) Conference 2016
Health, Disability and EducationDates: Wednesday 26 October 2016 - Thursday 27 October 2016 Location: The Council House, NG1 2DT
Special Event Meetup on Gamification
Agenda:
5:45 - 6:00: Welcome & Networking
6:00 - 6:15: News and Introduction
6:15 – 7:15: Studies in Gameful Interaction Design and Games User Research + Q&A
7:15 - 7:30: Networking
GLAID: Designing a Game Learning Analytics Model to Analyze the Learning Process in Users with Cognitive Disabilities
Downtown: Serious Game designed and develop to teach young people with Down Syndrome to move around the city using the subway
We are using learnig analytics for evaluating the game and for knowing how the user is doing in the game
This work is part of the H2020 BEACONING project
Downtown is a game
Quiz applicationQuestionnaire Information1. I’m going to se.docxaudeleypearl
Quiz application
Questionnaire Information:
1. I’m going to select the quiz application, my project for my questionnaire and I’ve selected all age group people for that.
2. I need information from them about the interest of each age group and how much they are interested in that.
Questionnaire
1. Your Name:
___________________________________
2. Your age group:
1. 15-25
2. 25-35
3. 35-45
4. 45 above
3. What interests you the most?
1. Games
2. Politics
3. Movies
4. Sports
4. How many hours do you spend in self-study?
1. Below 2
2. 2-3
3. Above 3
5. Do you like playing quizzes or games on computer?
1. Yes
2. No
6. Rate your interest in quiz games out of 5:
1. Worst
2. Bad
3. Average
4. Good
5. Best
________________________________________________________________
7. How often you participate in a discussion:
1. Once a week
2. Twice
3. Thrice
4. Daily
8. What kind of topics you like to discuss in your conversation:
9. How many times you go to the gym for your physical fitness?
1. Once a week
2. Twice a week
3. Thrice a week
4. Daily
10. How important are the political issues in your life?
1. I don’t care about it
2. Slightly important
3. Definitely important
4. Very important
11. What sports do you like the most?
12. What is your favorite game in computer games?
__________________________________________________
13. What genre do you like the most in games?
1. RPG (role playing games)
2. FPS (First person shooting)
3. Strategy
4. Simulation
5. Fighting
6. Sports
14. Which is the most important thing about video games
1. Graphics
2. Game play
3. Sound
4. Customization
15. What is preferable in quiz game?
1. More options
2. Life lines
3. Difficult questions
16. How much have you spent on a game and what game?
1. 2 hours
2. 4 hours
3. 6 hours
4. above
17. Is education necessary for the intelligence or knowledge is enough?
1. Education
2. knowledge
18. Which color do you think is the best for the interactive screen for quiz game
________________________________________________________________
19. What services do you think should be in a quiz game or application?
____________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
20. Would you like to play a new game which tells you about the interest you have and then play quizzes according to your interests?
1. Yes
2. No
Questionnaire Response Type:
1. Demographic = Open ended was the only way
2. Age group = Select options are easy over open ended
3. Already availing any service = yes/no is better suited because this is a conclusion question
4. Importance of education and knowledge = Select options are easy over open ended
5. Appearance of application = options can describe the answer here
6. Work and interest preference = options can describe the answer here
7. Necessity of application = yes/no ...
Downtown, A Subway Adventure: Using Learning Analytics to Improve the Develop...Ana Rus Cano Moreno
In this paper we analyze the process of designing and developing a Serious Game intended to train people with intellectual disabilities in moving around a city using the public transportation system. The first step in our investigation is to understand the cognitive, psychological and motor abilities of our users and their specific needs. Secondly, we translated the characteristics of the players into user requirements, with adapted mechanics to improve the understanding and to increase the probability for the user to be able to carry out the tasks to perform in the video game. Finally, due to the specific characteristics of our final users a Learning Analytics module has been included in the game to collect relevant information about how users are actually playing and to infer how the learning process of every user is occurring. We also discuss the next steps in our research and the future work related with it: design a range of experimental tests to verify the adequacy of the video game as a learning tool for this type of users
Learning Gamification Design – An Usability First Approach for the Enterprise...Michael Meder
Gamification or gameful design attempts to raise participation through the application of game design patterns and principles in non-game environments. It has successfully been applied but in many cases gamification fails due to different kind of design phase pitfalls. Several game and gamification design taxonomies and guides exists. But it is hard to select the right one for a specific application of gamification. One of the causes is probably the fact that engineers try to implement what experienced game designer should do.
% Außerdem ist nicht klar ob man einfach alle Erfahrungen und Erkenntnisse aus der Game Design welt übertragen kann.
We propose to apply data mining on user interaction data of gamified applications to extract insights to support and adapt the application of gamification. Therefore we started the Infoboard experiment -- a two phase gamification study of a cutting-edge enterprise information sharing system.
Artificial Intelligence applied in Games (AI for Enterprise Virtual User Group)Leonardo Moraes
Do you like games? Are you curious about Artificial Intelligence? And how about joining these two great topics?!
This talk will introduce some general AI concepts as well as a case study on Super Mario Maker game. Let's discuss and understand the step by step how to apply Artificial Intelligence in games, shall we?
Research Overview Mirjam P Eladhari August 2019Mirjam Eladhari
Slides for a presentation where I gave an overview of my research in August 2019. The talk is about how I have adressed two question that are at the core of my work:
Q1 How can we work to innovate in game design and technology?
Q2 How can we create play experiences that are individually meaningful?
In this talk we will introduce serious games as games which purpose is not only amusement and can be effectively used for educational or training purposes. This kind of games are also frequently named as educational games or even as game-like simulations. We will describe the general characteristics of serious games and how they are used in several domains (e.g. military, medicine), describing their main advantages (e.g. engagement, student motivation) and some of the shortcomings that prevent a wider generalization in educational settings (e.g. cost, deployment). We will also describe new emerging trends in the field of serious games such as gaming for solving scientific problems or how the application of learning analytics techniques can improve and simplify serious games application in different domains.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
2. Contributions
A. Personalized Gameful Design
1. Classification of user preferences
2. Selection of gameful design elements
3. Evaluation of the design
B. Platform for the Study of
Personalized Gameful Design
2
4. Personalized Gameful
Design
The tailoring
of the gameful design elements
by the providers to the users
based on knowledge about them,
to boost the achievement of the goals
of the gameful system.
4Gustavo F. Tondello. 2019. Dynamic Personalization of Gameful Interactive Systems. PhD Thesis, University of Waterloo.
5. Types of Personalization
5
User-initiated (customization) System-initiated
Access
Lotteries
Boss Battles
Because you recently completed a challenge:
Unlock restricted
areas of the system
You can earn
amazing rewards in
our lottery
Test your skills with
these highly difficult
tasks
6. Why Personalize Gameful Systems?
• Higher engagement, performance, enjoyment
• Boost the achievement of goals
• task completion rate, learning, health, employee engagement…
6
Education Health Fitness Nutrition
Training Customer
relations
Human
resources
Team
management
Image source: www.pexels.com
7. Why Personalize Gameful Systems?
“I feel like it did [influence my
enjoyment] because I felt like I
kind of created my own game
that was perfect for me and so
it felt like I was in control and
added to my enjoyment.”
9
Pilot study with N = 50 MTurk participants.
Gustavo F. Tondello. 2019. Dynamic Personalization of Gameful Interactive Systems. PhD Thesis, University of Waterloo.
9. 1. Classification of User Preferences
11
Classification
of User
Preferences
Selection of
Gameful
Design
Elements
Evaluation of
the Design
1 2 3
10. Gamification User Types Hexad
Do all users equally enjoy all game elements?
12Andrzej Marczewski. 2015. User Types. In Even Ninja Monkeys Like to Play: Gamification, Game Thinking & Motivational Design.
Gamified UK.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
11. Gamification User Types Hexad
24-item scale
(developed in collaboration with Andrzej Marczewski
and the Austrian Institute of Technology)
13
Image source: screenshots from https://gamified.uk/
G. F. Tondello, R. R. Wehbe, L. Diamond, M. Busch, A. Marczewski, L. E. Nacke. 2016. The Gamification User Types Hexad Scale. In
Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’16, 229–243.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
12. User Types Hexad: Validation
Four studies
1. Initial validation in English (N = 133)
2. Large-scale validation in English and Spanish (N = 556)
(data gently provided by Alberto Mora)
3. Large-scale validation in English and Spanish (N = 1,328)
(data gently provided by Andrzej Marczewski)
4. Validation of suggested improvements in English (N = 152)
(data collected in collaboration with Andrzej Marczewski)
14
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
[1] G. F. Tondello, R. R. Wehbe, L. Diamond, M. Busch, A. Marczewski, L. E. Nacke. 2016. The Gamification User Types Hexad Scale. In
Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’16, 229–243.
[2-4] G. F. Tondello, A. Mora, A. Marczewski, L. E. Nacke. 2019. Empirical Validation of the Gamification User Types Hexad Scale in
English and Spanish. International Journal of Human-Computer Studies 127, 95–111.
13. User Types Hexad: Validation
Analysis methods
• Exploratory Factor Analysis (EFA)
• Confirmatory Factor Analysis (CFA) with structural equation
modeling (SEM)
Results
The scale is generally consistent and reliable
[1] has already been cited 112 times
15
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
[1] G. F. Tondello, R. R. Wehbe, L. Diamond, M. Busch, A. Marczewski, L. E. Nacke. 2016. The Gamification User Types Hexad Scale. In
Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’16, 229–243.
[2-4] G. F. Tondello, A. Mora, A. Marczewski, L. E. Nacke. 2018. Empirical Validation of the Gamification User Types Hexad Scale in
English and Spanish. International Journal of Human-Computer Studies 127, 95–111.
14. 2. Selection of Gameful Design Elements
18
Classification
of User
Preferences
Selection of
Gameful
Design
Elements
Evaluation of
the Design
1 2 3
15. Groups of Gameful Design Elements
19
Individual
Motivations
Immersion
Progression
External
Motivations
Risk/Reward
Customization
Incentive
Social
Motivations
Socialization
Assistance
Altruism
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
Results of Principal Components Analysis (N = 196)
Image sources: www.pexels.com and Game-icons.net
Gustavo F. Tondello, Alberto Mora, and Lennart E. Nacke. 2017. Elements of Gameful Design Emerging from User Preferences. In Proceedings of the
2017 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’17, 129–142.
16. Groups of Gameful Design Elements
28
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Immersion
Progression
Customization
Incentive
Risk/Reward
Altruism
Socialization
Assistance
Note: Mean Likert scores (1–5) per group (N = 196)
Gustavo F. Tondello, Alberto Mora, and Lennart E. Nacke. 2017. Elements of Gameful Design Emerging from User Preferences. In
Proceedings of the 2017 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’17, 129–142.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
17. Preferences by Gender
29
Note: Mean differences per gender and group (N = 124 men, 53 women)
Gustavo F. Tondello, Alberto Mora, and Lennart E. Nacke. 2017. Elements of Gameful Design Emerging from User Preferences. In
Proceedings of the 2017 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’17, 129–142.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
0.2
-0.29
-0.08
-0.14
0.13
-0.11
-0.37
0.63
0.37
0.31
-0.25
0.23
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Socialization Assistance Immersion Customization Altruism Incentives
Men Women
18. Preferences by Hexad User Type
30
Note: Based on results from correlation analysis (N = 196)
Gustavo F. Tondello, Alberto Mora, and Lennart E. Nacke. 2017. Elements of Gameful Design Emerging from User Preferences. In
Proceedings of the 2017 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY ’17, 129–142.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
Participants who scored higher as… …tended to prefer these groups
Free Spirit Immersion
Philanthropist Immersion, Progression, Altruism
Achiever Socialization, Immersion, Risk/Reward,
Progression, Altruism
Socialiser Socialization, Assistance, Altruism
Player Socialization, Risk/Reward, Incentive
Disruptor Immersion, Risk/Reward
20. 3. Evaluation of the Design
32
Classification
of User
Preferences
Selection of
Gameful
Design
Elements
Evaluation of
the Design
1 2 3
21. Gameful
Design
Heuristics
33
G. F. Tondello, D. L. Kappen, E. D. Mekler, M. Ganaba, L. E. Nacke. 2016. Heuristic
Evaluation for Gameful Design. In Proceedings of CHI PLAY ’16 Extended Abstracts.
G. F. Tondello, D. L. Kappen, M. Ganaba, L. E. Nacke. 2019. Gameful Design
Heuristics: A Gamification Inspection Tool. In Proceedings of HCI International 2019.
Infographic by Dennis Kappen and Marim Ganaba
Heuristics
General design principle or
guidelines
Heuristic Evaluation
Use of said principles to identify
design problems
Gameful Design Heuristics
Set of guidelines for heuristic
evaluation of gameful
applications
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
22. Gameful Design Heuristics
How to conduct a heuristic evaluation of a gameful system
1. Familiarize yourself with the application
2. Use the heuristics checklist
3. For each heuristic:
a. Familiarize yourself with the heuristic
b. Think about the supporting questions in relation to the app
c. If you identify any issue in the app related to the heuristic, write it down
4. Finally, count the number of issues identified for each category to
identify those with more issues
34
Gustavo F. Tondello, Dennis L. Kappen, Elisa D. Mekler, Marim Ganaba, and Lennart E. Nacke. 2016. Heuristic Evaluation for Gameful Design.
In Proceedings of CHI PLAY ’16 Extended Abstracts, 315–323.
G. F. Tondello, D. L. Kappen, M. Ganaba, L. E. Nacke. 2019. Gameful Design Heuristics: A Gamification Inspection Tool. In Proceedings of HCI
International 2019.
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
23. Usefulness of this evaluation method
35
1. Classification of User Preferences 2. Selection of Gameful Design Elements 3. Evaluation of the Design
Note: N = 2 without heuristics. N = 3 with heuristics for Habitica, 1 for Termling.
G. F. Tondello, D. L. Kappen, M. Ganaba, L. E. Nacke. 2019. Gameful Design Heuristics: A Gamification Inspection Tool. In Proceedings of HCI
International 2019.
Results
• Gameful design heuristics help evaluators who are not familiar with gamification to
evaluate a system as well as a gamification expert who does not use the heuristics
• Gameful design heuristics improves the ability of gamification experts to perform an
heuristic evaluation
7 8
13
24
0
5
10
15
20
25
30
Habitica Termling
Number of motivational issues found
Without Heuristics
With Heuristics
28. Frequency of Element Selection
36
30 30
23 23
20
16 16
6
0
5
10
15
20
25
30
35
40
Progress
Feedback
Levels Power-ups Leaderboards Chance Badges Unlockable
Content
Challenges Moderating
Role
40
Pilot study with N = 50 MTurk participants.
Gustavo F. Tondello. 2019. Dynamic Personalization of Gameful Interactive Systems. PhD Thesis, University of Waterloo.
29. Rating of the Experience
34
36
42
39 39
9 8
6 5
11
7
1 2 3
0
0
5
10
15
20
25
30
35
40
45
Overall experience Element selection Satisfaction Preference matching Enjoyment
Positive Neutral Negative
41
Pilot study with N = 50 MTurk participants.
Gustavo F. Tondello. 2019. Dynamic Personalization of Gameful Interactive Systems. PhD Thesis, University of Waterloo.
31. Personalized Gameful
Design
43Gustavo F. Tondello. 2019. Dynamic Personalization of Gameful Interactive Systems. PhD Thesis, University of Waterloo.
The tailoring
of the gameful design elements
by the providers to the users
based on knowledge about them,
to boost the achievement of the goals
of the gameful system.
35. Open Research Questions
Do user preferences vary by context or country?
Do users’ behaviours correspond to their self-reported
preferences?
Do different designs of gameful elements influence user
preferences?
What other evaluation methods can be devised?
47
36. Empirical Studies of Personalized
Gameful Systems
Personalized vs Generic systems
Partial vs Full Personalization
Personalization vs Customization
48
37. Friend invite
Social discovery
Trading
Access
Lotteries
Boss Battles
Because you recently completed a challenge: Because you recently joined a team:
Unlock restricted
areas of the system
You can earn
amazing rewards in
our lottery
Test your skills with
this highly difficult
tasks
Invite your friends
to work with you
Find other users
with similar
interests
Exchange your
spare items with
other users
Recommender Systems for
Personalized Gamification
49
Models of user types
and design elements
Recommendation
algorithms
Machine learning
38. What else can we personalize?
Activities
Game
Elements
Persuasive
Strategies
Difficulty Rewards
50Image source: www.pexels.com
39. Questions and Discussion
51
Dynamic Personalization of
Gameful Interactive Systems
Gustavo Fortes Tondello
Acknowledgments:
This research was supported by:
• The National Council for Scientific and Technological Development – Brazil (CNPq)
• University of Waterloo (Cheriton School of Computer Science, Games Institute, HCI Games Group)
• NSERC (grants RGPIN-418622-2012; RGPIN-2018-06576)
• SSHRC (grant 895-2011-1014, IMMERSe)
• Mitacs (grant IT07255)
• CFI (grant 35819)
• NSERC CREATE SWaGUR