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Comparing e-learning and blended learning for threat detection in airport security X-ray screening

机译:比较电子学习和混合学习以进行机场安全X射线检查中的威胁检测

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This study investigated the effectiveness of e-learning and blended learning for airport security officers (screeners) aimed at increasing their detection of novel prohibited items in X-ray images of passenger bags. 80 screeners from a large European airport conducted a simulated X-ray baggage screening task (SXBST). Based on hit- and false alarm rates, d-prime, age, gender and job experience, four equivalent screener groups were created. The first group (EL1) conducted six different e-learning modules. The second group (EL2) repeated the e-learning modules once with a predefined time interval of one week in-between. The third group (BL) participated in an asynchrony blended learning course where all participants first conducted the six e-learning modules followed by classroom training. The control group (CG) did neither conduct e-learning nor participate in the blended learning course. All four groups conducted the SXBST again after these interventions. Statistical analyses of the hit rates for novel prohibited items showed a significant main effect of group (EL1, EL2, BL, CG). Post-hoc tests showed that the increase of the hit rate for EL1 vs. CG, EL2 vs. CG and BL vs. CG was significant. Therefore, all interventions helped to increase the detection of novel prohibited items in X-ray images of passenger bags. Additionally, the hit rate for BL was significantly higher compared to EL1, which underlies the benefit of blended learning as a combination of classroom and online-training. The repetition of the e-learning modules (EL2) led to a marginally significant increase of the hit rate compared to EL1. The difference between EL2 and BL was not significant. This suggests that when training duration is controlled, the advantage of blended learning compared to e-learning vanishes. In addition, training did not impact false alarm rate as the main effect of group was not significant. Analysis of response times showed no speed-accuracy tradeoff but screeners needed significantly more time to analyze target-absent images than target-present images and this effect was independent of group. Overall, these findings suggest that e-learning as well as blended learning are effective to improve screeners' detection of novel prohibited items in X-ray images of passenger bags. Implications for X-ray image interpretation training for screeners are discussed.
机译:这项研究调查了电子学习和混合学习对机场安检人员(检查员)的有效性,旨在提高他们在旅客行李X射线图像中发现新颖的违禁物品的能力。来自欧洲大型机场的80位安检员进行了模拟X射线行李安检任务(SXBST)。根据命中率和误报率,d素数,年龄,性别和工作经验,创建了四个等效的筛选器组。第一组(EL1)进行了六个不同的电子学习模块。第二小组(EL2)以预定的间隔时间(一周之间)重复了一次电子学习模块。第三组(BL)参加了异步混合学习课程,所有参与者首先进行了六个电子学习模块,然后进行了课堂培训。对照组(CG)既不进行在线学习也不参与混合学习课程。在进行了这些干预之后,所有四个小组再次进行了SXBST。对新的违禁物品的命中率的统计分析表明,该组(EL1,EL2,BL,CG)具有显着的主要作用。事后测试表明,EL1对CG,EL2对CG和BL对CG的命中率的增加是显着的。因此,所有干预措施都有助于增加对乘客行李X射线图像中新的违禁物品的检测。此外,与EL1相比,BL的命中率要高得多,这奠定了课堂和在线培训相结合的混合学习的优势。与EL1相比,重复学习e-learning模块(EL2)导致命中率略有提高。 EL2和BL之间的差异不明显。这表明,当控制培训时间时,与电子学习相比,混合学习的优势就消失了。此外,训练对组的误报率没有影响,因为组的主要作用并不显着。响应时间的分析显示没有速度准确性的折衷,但是与目标图像相比,筛选器需要更多的时间来分析目标缺失的图像,并且这种效果与组无关。总体而言,这些发现表明,电子学习以及混合学习可以有效地提高筛查人员对乘客行李X射线图像中新的违禁物品的检测能力。讨论了对筛选人员进行X射线图像解释训练的意义。

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