Persuasive Design
Monitoring Player Motivation for Gamification
One of the big questions facing us as gamification designers is, āWhen will your player get bored of your gamification project, and how can you keep their interest as long as possible?ā Fortunately, there are ways to monitor player motivation so that you can respond to them accordingly. In their book, Gamification at Work: Designing Engaging Business Software, Janaki Kumar and Mario Herger report on software designer Amy Jo Kimās system for monitoring player motivation. Letās take a look at how that works now.
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User Research & Psychology
10 cognitive biases to avoid in User Research (and how to avoid them)
Cognitive biases have become quite popular in mainstream culture in the last decade, thanks to books like Thinking Fast and Slow and Predictably Irrational. Along with human centered approaches, it has also gained quite a lot of prominence in Experience/Business design. Since we have come to rely more and more on quantitative and qualitative research to take informed product/business decisions, itās also important to ensure that the data and its method of collection is not impaired by an ignorance of cognitive biases, so as to provide meaningful value to end customers.
Human Cognition
Psychology: Using Sensory for UX
There are many fields of psychology, and we can find many things relevant to user experience in each of them. But this article is focuses on sensory of human body and how we need to use them for greater user experience. As a UX person we need to understand how individuals perceive, understand, feel and act in a situation. There are five areas of PsychologyĀ Perception, Motivation, Cognition, Emotion, and Behavior.Ā Perception is the process of become aware of something through the senses. We see, hear, and feel the products we are using, sensation and perception are very closely connected. Our senses areĀ Vision, Hearing, Touch, Proprioception
Human, AI and UX
Individualized Recommendations: Usersā Expectations & Assumptions
Users appreciate personalized content suggestions and are willing to give up some of their privacy for quality recommendations, while accepting some inaccurate recommendations. Individualized recommendations can be based on machine learning or other artificial-intelligence techniques, explicit customization instructions from the user, or some combination of both.