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A trace-based approach to identifying users' engagement and qualifying their engaged-behaviours in interactive systems: application to a social game

机译:一种基于痕迹的方法,用于识别用户在互动系统中的参与度并确定其参与度:在社交游戏中的应用

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Analysing and monitoring users' engaged-behaviours continuously and under ecologically valid conditions can reveal valuable information for designers and practitioners, allowing them to analyse, design and monitor the interactive mediated activity, and then to adapt and personalise it. An interactive mediated activity is a human activity supported by digital interactive technologies. While classical metric methods fall within quantitative approaches, this paper proposes a qualitative approach to identifying users' engagement and qualifying their engaged-behaviours from their traces of interaction. Traces of interaction represent the users' activities with an interactive environment. The basis of our approach is to transform low-level traces of interaction into meaningful information represented in higher-level traces. For this, our approach combines three theoretical frameworks: the Self-Determination Theory, the Activity Theory and the Trace Theory. Our approach has been implemented and tested in the context of the QUEJANT Projet. QUEJANT targets the development of a system allowing the actors of Social Gaming to analyse players' engagement from an analysis of their activity traces. In order to demonstrate the feasibility of our approach, we implemented the whole process in a prototype and applied it to 12 players' interaction data collected over four months. Based on these interaction data, we were able to identify engaged and non-engaged users and to qualify their types of engaged-behaviours. We also conducted a user study based on a validation of our results by experts. The high prediction rate obtained confirms the performance of our approach. We finally discuss the limitations of our approach, the potential fields of application and the implications for digital behavioural interventions.
机译:在生态有效的条件下连续分析和监视用户的参与行为可以为设计者和从业者揭示有价值的信息,使他们能够分析,设计和监视交互式介导的活动,然后对其进行适应和个性化。交互式媒介活动是数字交互式技术支持的人类活动。虽然经典的度量方法属于定量方法,但本文提出了一种定性方法,用于识别用户的参与度并从其交互痕迹中限定其参与行为。交互的痕迹代表了用户在交互环境中的活动。我们方法的基础是将交互的低级别跟踪转换为高级跟踪中表示的有意义的信息。为此,我们的方法结合了三个理论框架:自决理论,活动理论和痕量理论。我们的方法已经在QUEJANT Projet的环境中实施和测试。 QUEJANT的目标是开发一种系统,该系统可使Social Gaming的参与者从对他们的活动轨迹的分析中分析参与者的参与度。为了证明我们方法的可行性,我们在原型中实施了整个过程,并将其应用于四个月内收集的12个参与者的交互数据。基于这些交互数据,我们能够识别参与和未参与的用户,并确定其参与行为的类型。我们还根据专家对我们结果的验证进行了用户研究。获得的高预测率证实了我们方法的性能。最后,我们讨论了这种方法的局限性,潜在的应用领域以及对数字行为干预的影响。

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