The Gamification User Types Hexad Scale

Written by Gustavo Tondello. Infographics by Marim Ganaba.

Several studies have indicated the need for personalising gamified systems to users’ personalities. However, mapping user personality onto design elements is difficult. To address this problem, Marczewski developed the Gamification User Types Hexad framework, based on research on human motivation, player types, and practical design experience. He also suggested different game design elements that may support different user types. However, until now we were still lacking a standard assessment tool for user’s preferences based on the Hexad framework. There was also no empirical validation, yet, that associated Hexad user types and game design elements. A collaborative research project by the HCI Games Group, the Austrian Institute of Technology, and Gamified UK sought to accomplish these two goals: (1) create and validate a standard survey to assess an individual’s Hexad user type and (2) verify the association between the Hexad user types and the game design elements they are supposed to appeal to.

In case you are not familiar with the Hexad user types yet, please take a moment to watch this video or read the user types’ descriptions at Gamified UK.

Our research developed and validated a 24-item survey to assess an individual’s Hexad user type. Would you like to know your user type? Why don’t you take a minute to take the online survey at Gamified UK?

Gamified UK Gamification User Type HEXAD Test


Hexad User Types and Game Design Elements

We asked participants to rate how much they enjoy several game design elements and compared the answers with their Hexad user type to find out which game design elements are preferred by each user type. The following infographic summarises the results.

Hexad User Types and Personality

We also assessed participants’ personalities using the Big Five personality traits and compared the results with the Hexad user types. The following infographic shows the user types more likely to appear for people with higher scores in each of the five personality traits:

Using the Survey

Using the Hexad user types framework and the survey is more effective than asking users about design elements directly because the survey’s goal is to understand more about user psychology in a gamified context rather than just determining game elements they prefer. Furthermore, users are not necessarily gamers and might not be aware of their game preferences or be familiar with game design vocabulary. Therefore, our survey aims to use a common vocabulary.

There are several ways to use the Hexad model to personalise gameful applications. For example, designers would be able to screen their target audience using the suggested survey and choose the adequate design elements for each user. In research, the survey can be used to better understand user engagement and enjoyment in studies regarding gameful applications.

If you wish to use the Hexad user types survey, please read the original publication to be presented at CHI PLAY 2016, which contains details about the validation study and the survey items. Use of the scale is free for academic purposes. For commercial uses, please contact us. If you would like to join the HCI Games Group as a graduate student working on gamification and games user research, please also contact us.

The Gamification User Types Hexad Scale

3 thoughts on “The Gamification User Types Hexad Scale

  • July 12, 2019 at 11:52 AM


    I’m doing my master thesis at the HES-SO (University in Switzerland) on the gamification topic and I’m using the survey that you have done and empirically validated (2016 and 2019) in my study. I read both articles and I can’t find the way you calculated the score and determine the player type.

    In your article of 2019 there is just that sentence that said “After each completed survey, the website calculated the scores for each user type and presented the user with a chart of the results.” but there is no information about that algorithm in particular.

    I guess each item have a score (as displayed on this website: from -3 to 3. We calculated the score for each subscale. For example: if a person respond “somewhat agree”, “somewhat agree”, “agree” and “strongly agree” for the 4 item for player so the score is 1+1+2+3=7. And the dominant score become the player type of the respondant. But I’m not sure about that. By additionning the score, in my case, a respondent can have a maximum of 12 points (3+3+3+3). In your examples, the mean is near 20.

    So I would like to know if it was possible to get that algorithm that compute the score.

    Thank a lot in advance for your help and have a nice week-end!

    Dylan Montandon

    • July 20, 2019 at 3:38 PM

      Hi Dylan,
      Thank you for your interest in our research!
      In our paper, we assigned the values 1 to 7 to each Likert response option. So, when we added up the four items per user type, the final scores were between 4 and 28.
      You could also use Likert scores between -3 and 3, so the final scores for each user type would be between -12 and 12.
      But if you want to have results that are directly comparable to ours, just use the values from 1 to 7 and add them for each user type.
      Best regards,
      Gustavo Tondello.

      • July 22, 2019 at 4:06 AM

        Hi Gustavo,

        Thanks for your reply! It helps me a lot.

        Have a nice day,


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