Cognitive Science Department, Rensselaer Polytechnic Institute, Troy, New York, USA.
Behav Res Methods. 2015 Dec;47(4):945-965. doi: 10.3758/s13428-014-0547-y.
Studies of human performance in complex tasks using video games are an attractive prospect, but many existing games lack a comprehensive way to modify the game and track performance beyond basic levels of analysis. Meta-T provides experimenters a tool to study behavior in a dynamic task environment with time-stressed decision-making and strong perceptual-motor elements, offering a host of experimental manipulations with a robust and detailed logging system for all user events, system events, and screen objects. Its experimenter-friendly interface provides control over detailed parameters of the task environment without need for programming expertise. Support for eye-tracking and computational cognitive modeling extend the paradigm's scope.
使用视频游戏研究人类在复杂任务中的表现是一个很有吸引力的前景,但许多现有的游戏缺乏一种全面的方法来修改游戏并跟踪超出基本分析水平的性能。Meta-T 为实验者提供了一种工具,用于在具有时间紧迫决策和强烈感知运动元素的动态任务环境中研究行为,提供了许多实验操作,并具有强大而详细的日志系统,用于记录所有用户事件、系统事件和屏幕对象。其易于实验者使用的界面提供了对任务环境详细参数的控制,而无需编程专业知识。对眼动追踪和计算认知建模的支持扩展了该范例的范围。