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Heuristic Evaluation for Serious Immersive Games and M-instruction

机译:严重沉浸式游戏和M指令的启发式评估

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Two fast growing areas for technology-enhanced learning are serious games and mobile instruction (M-instruction or M-Learning). Serious games are ones that are meant to be more than just entertainment. They have a serious use to educate or promote other types of activity. Immersive Games frequently involve many players interacting in a shared rich and complex - perhaps web-based -mixed reality world, where their circumstances will be multi and varied. Their reality may be augmented and often self-composed, as in a user-defined avatar in a virtual world. M-instruction and M-Learning is learning on the move; much of modern computer use is via smart devices, pads, and laptops. People use these devices all over the place and thus it is a natural extension to want to use these devices where they are to learn. This presents a problem if we wish to evaluate the effectiveness of the pedagogic media they are using. We have no way of knowing their situation, circumstance, education background and motivation, or potentially of the customisation of the final software they are using. Getting to the end user itself may also be problematic; these are learning environments that people will dip into at opportune moments. If access to the end user is hard because of location and user self-personalisation, then one solution is to look at the software before it goes out. Heuristic Evaluation allows us to get User Interface (UI) and User Experience (UX) experts to reflect on the software before it is deployed. The effective use of heuristic evaluation with pedagogical software is extended here, with existing Heuristics Evaluation Methods that make the technique applicable to Serious Immersive Games and mobile instruction (M-instruction). We also consider how existing Heuristic Methods may be adopted. The result represents a new way of making this methodology applicable to this new developing area of learning technology.
机译:技术增强学习的两种快速增长的区域是严重的游戏和移动指令(M-CNARGRY或M-LEARNING)。严肃的比赛是那些意味着不仅仅是娱乐活动。他们有严重用来教育或促进其他类型的活动。沉浸式游戏经常涉及许多玩家在共享丰富和复杂的互动 - 也许是基于Web的粘贴现实世界,他们的情况将是多变的。他们的现实可以增强并经常自我组成,如虚拟世界中的用户定义的化身。 M-CNARGRY和M学习正在移动;现代计算机使用的大部分是通过智能设备,垫和笔记本电脑。人们在整个地方使用这些设备,因此想要使用这些设备来学习的自然扩展。如果我们希望评估他们正在使用的教学媒体的有效性,这提出了问题。我们无法了解他们的情况,环境,教育背景和动机,或者可能是他们正在使用的最终软件的定制。到达最终用户本身也可能是有问题的;这些是学习环境,人们将在适当的时刻倾向。如果由于位置和用户自我化而对最终用户的访问很难,那么一个解决方案就是在熄灭之前查看软件。启发式评估允许我们获取用户界面(UI)和用户体验(UX)专家在部署之前反映软件。在此扩展了与教学软件的启发式评估的有效利用,现有的启发式评估方法使得该技术适用于严重的沉浸式游戏和移动指令(M-CNARGE)。我们还考虑如何采用现有的启发式方法。结果代表了一种适用于这种学习技术新的发展领域的方法的新方法。

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