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Assessment of driving expertise using multiple choice questions including static vs. animated presentation of driving scenarios

机译:使用多项选择题评估驾驶专业知识,包括静态和动态演示驾驶场景

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摘要

Novice drivers have a high collision risk compared to more experienced drivers. The optimization of driving assessment's validity should lead to a better identification of those examinees that need further training before solo driving. The aim of the present two studies was to find out whether the integration of animated traffic scenarios can enhance some quality aspects of selected multiple choice items of the official German driving test. For the first study, we developed a static version of a set of multiple choice questions each containing a computerized still picture of a traffic scenario and a dynamic version that included animated instead of still pictures of the same situations. Driving novices (n = 57) and experts (n = 63) were presented 22 items either in the static or in the dynamic version. Only the novices benefited from the dynamic presentation. Fifty novices and 50 experts participated in a second longitudinal study including three measurements with parallel tests of the dynamic testing materials at intervals of three to four months. The novices, who were currently attending driving school, improved over time whereas the experts' performance remained stable. The results indicate that animation has positive effects on some quality aspects of driving assessment, but the problem of low criterion validity has to be addressed by the means of further approaches.
机译:与经验丰富的驾驶员相比,新手驾驶员具有较高的碰撞风险。通过优化驾驶评估的有效性,可以更好地识别那些需要在单独驾驶之前接受进一步培训的应试者。当前两项研究的目的是找出动画交通场景的整合是否可以增强官方德国驾驶考试中多项选择项的质量。对于第一个研究,我们开发了一组多项选择题的静态版本,每个问题都包含交通场景的计算机化静态图片,以及动态版本,其中包含动画而不是相同情况的静态图片。静态或动态版本的驾驶新手(n = 57)和专家(n = 63)被介绍了22个项目。只有新手才能从动态演示中受益。 50名新手和50名专家参加了第二项纵向研究,其中包括三项测量,每三至四个月进行一次动态测试材料的平行测试。当前正在上驾驶学校的新手随着时间的推移而有所改善,而专家的表现保持稳定。结果表明,动画对驾驶评估的某些质量方面具有积极影响,但标准有效性低的问题必须通过进一步的方法来解决。

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