Multi-Criteria Decision Analysis (MCDA) requires a critical step, namely to elicit individual preferences. On the basis of learning theories, we formalize preference construction as learning about facts and values, and as a process; we also conceptualize an online preference elicitation survey that offers learning loops to increase factual learning and support preference construction. Another originality is gamification. Game elements (a narrative and non-player characters as motivational affordance) keep respondents engaged in the demanding task of weight elicitation. Our tool enables broad public participation in MCDA, allowing reliable online preference elicitation. The survey concept was tested with 107 students and a control treatment. Quantitative and qualitative data indicate that the concept works. Participants’ factual knowledge increased. The survey helped students to learn about their own preferences concerning the importance of objectives. The practical implication is that weighting can be reliably elicited by online surveys. Participants reported a positive experience; further ways to improve it are thoroughly discussed.

多标准决策分析（MCDA）需要一个关键步骤，即引发个人偏好。在学习理论的基础上，我们将偏好建构形式化为对事实和价值的学习，并作为一个过程。我们还将在线偏好激发调查的概念化，该调查提供学习循环以增加事实学习并支持偏好构建。另一个独创性是游戏化。游戏元素（叙事和非玩家角色作为激励能力）使受访者参与到要求重的减肥任务中。我们的工具可让公众广泛参与MCDA，从而实现可靠的在线偏好获取。调查概念由107名学生和对照组进行了测试。定量和定性数据表明该概念有效。参加者的事实知识有所增加。这项调查帮助学生了解自己对目标重要性的偏好。实际的含义是可以通过在线调查可靠地得出权重。与会者报告了积极的经验；进一步讨论了改进它的其他方法。