In this paper, we present the development and validation of an instrument for measuring users' gameful experience while using a service. Either intentionally or unintentionally, systems and services are becoming increasingly gamified and having a gameful experience is progressively important for the user's overall experience of a service. Gamification refers to the transformation of technology to become more game-like, with the intention of evoking similar positive experiences and motivations that games do (the gameful experience) and affecting user behavior. In this study, we used a mixed-methods approach to develop an instrument for measuring the gameful experience. In a first qualitative study, we developed a model of the gameful experience using data from a questionnaire consisting of open-ended questions posed to users of Zombies, Run!, Duolingo, and Nike+ Run Club. In a second study, we developed the instrument and evaluated its dimensionality and psychometric properties using data from users of Zombies, Run! (N = 371). Based on the results of this second study, we further developed the instrument in a third study using data from users of Duolingo (N = 507), in which we repeated the assessment of dimensionality and psychometric properties, this time including confirmation of the model. As a result of this work, we devised GAMEFULQUEST, an instrument that can be used to model and measure an individual user's gameful experience in systems and services, which can be used for user-adapted gamification and for informing user-modeling research within a gamification context.

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Despite the popularity and extensive use of engaging users in crowdvoting, very little research has been conducted into the appropriateness of users as substitutes for experts when judging ideas. Accordingly, the purpose of this paper is to investigate the appropriateness of using users as a proxy for professional experts during the initial idea screening of new product/service ideas. In other words, are users' assessments during idea screening conformant with professional experts' assessments and are they reliable as a proxy for experts during idea screening? In a comparative study, two different approaches to outsourcing the screening of wireless ideas to users are examined, including assessment by two different user panels: (1) technically skilled users and (2) technically naïve users. These two approaches were compared with the assessments made by professional experts. The results showed no conformance between users and experts when comparing their absolute scores. However, during a relative comparison (the ranking of ideas), both user panels were conformant with the professional experts. A test of the user panels' ability to select the same top ideas as the professional experts was successful, indicating good conformance between the user panels and the professional experts. This paper's contribution is knowledge of how conformant external users are compared with professional expert judges during idea screening. The results indicate that companies can employ users during the initial screening process using criteria assessment to select the best ideas for further elaboration, something that would significantly reduce the number of ideas. The paper suggests an alternative design to crowdvoting, whereby the users assess the relevant criteria.

Abstract. The use of mobile smart devices for storing sensitive information and accessing online services is increasing. At the same time, methods for authenticating users into their devices and online services that are not only secure, but also privacy and user-friendly are needed. In this paper, we present our initial explorations of the use of lock pattern dynamics as a secure and user-friendly two-factor authentication method. We developed an application for the Android mobile platform to collect data on the way individuals draw lock patterns on a touchscreen. Using a Random Forest machine learning classifier this method achieves an average Equal Error Rate (EER) of approximately 10.39%, meaning that lock patterns biometrics can be used for identifying users towards their device, but could also pose a threat to privacy if the users' biometric information is handled outside their control.

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