Evaluating the effectiveness of Didi ride-hailing security measures: An integration model

Security is one of the most critical factors influencing individuals’ mobility. Ensuring security along ride-hailing trips is also a fundamental challenge to service providers. After two cases of rape and homicide, Didi has rectified measures again to meet passengers’ need for security. However, there are few scientific findings concerning the impact of Didi rectified measures on personal perception of security. This study aims to explore critical latent factors that affect individuals’ intentions to use or reuse ride-hailing after the rectification of security measures. This paper examines individuals’ usage intentions by integrating and expanding both the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). Research results suggest that perceived security, security risk, and government credibility are correlated with the intentions to use or reuse ride-hailing. Importantly, perceived security and security risk both have a direct impact on behavioral intentions from a different perspective. In contrast, government credibility has an indirect effect. Hence, a mediating effect test is conducted. Government credibility could indirectly influence behavioral intention by affecting trust. Finally, this study verifies that the effectiveness of security measures could be evaluated and improved by studying the influence of latent factors on the intentions to use or reuse ride-hailing.     

Safe driving and road-crossing tasks: A particular case of successful transfer of learning

The current study examines whether crucial safe driving skills are associated with safe road-crossing skills as pedestrians. The main research question was whether skills that are acquired from the point of view of a driver are associated with the skills of pedestrians in different platforms or settings. Furthermore, the study examines whether task performance on one platform (driving) primes an operator for task performance on another (road-crossing as a pedestrian) or vice versa. Sixty people took part in this study and completed a demographic questionnaire, a Driving Behavior Questionnaire, a Pedestrian Behavior Scale and two computerized tests – a Hazard Perception Test for Drivers and a Hazard Perception Test for Pedestrians.We found that the better the participants detect hazards on the road as drivers, the better they detect hazards as pedestrians as well, and that most of the participants’ self-reported values regarding their driving and their road-crossing as pedestrians are correlated. The study revealed an association between years of seniority in driving and the number of driving hours per week, and some behavioral variables as pedestrians – meaning that exposure to the road as a driver may be related to safer behavior as a pedestrian.     

Urgent and non-urgent takeovers during conditional automated driving on public roads: The impact of different training programmes

Supplying training to drivers that teaches them about automated driving and requests to intervene may help them to build and maintain a mental representation of how automation works and thereby improve takeover performance. We aimed to investigate the effect of different types of training programmes about the functioning of automated driving on drivers’ takeover performance during real driving. Fifty-two participants were split into three groups for training sessions: paper (short notice), video (3-minute tutorial) and practice (short drive). After the training, participants experienced automated driving and both urgent and non-urgent requests to intervene in a Wizard-of-Oz vehicle on public roads. Participants’ takeover time, visual behaviour, mental workload, and flow levels during the requests to intervene were assessed. Our results indicated that in urgent circumstances, participants’ takeover response times were faster in the practice training condition compared to the other training conditions. Nevertheless, the practice training session did not present any other positive effect on drivers’ visual behaviour. This could indicate that prior training, particularly when reinforcing drivers' motor skills, improved their takeover response time at the latest motor stages rather than in the early sensory states. In addition, the analysis of in-vehicle videos revealed that participants’ attention was captured in the first place by the in-vehicle human-machine interface during the urgent request to intervene. This highlights the importance for designers to display information on the HMI in an appropriate way to optimise drivers’ situation awareness in critical situations.     

Cognitive Evaluation of Machine Learning Agents

Advances in applying statistical Machine Learning (ML) led to several claims of human-level or near-human performance in tasks such as image classification & speech recognition. Such claims are unscientific primarily for two reasons, (1) They incorrectly enforce the notion that task-specific performance can be treated as manifestation of General Intelligence and (2) They are not verifiable as currently there is no set benchmark for measuring human-like cognition in a machine learning agent. Moreover, ML agent’s performance is influenced by knowledge ingested in it by its human designers. Therefore, agent’s performance may not necessarily reflect its true cognition. In this paper, we propose a framework that draws parallels from human cognition to measure machine’s cognition. Human cognitive learning is quite well studied in developmental psychology with frameworks and metrics in place to measure actual learning. To either believe or refute the claims of human-level performance of machine learning agent, we need scientific methodology to measure its cognition. Our framework formalizes incremental implementation of human-like cognitive processes in ML agents with an implicit goal to measure it. The framework offers guiding principles for measuring, (1) Task-specific machine cognition and (2) General machine cognition that spans across tasks. The framework also provides guidelines for building domain-specific task taxonomies to cognitively profile tasks. We demonstrate application of the framework with a case study where two ML agents that perform Vision and NLP tasks are cognitively evaluated.     

Does change in ethical education influence core moral values? Towards history- and culture-aware morality model with application in automatic moral reasoning

In this study, we focus on ethical education as a means to improve artificial companion’s conceptualization of moral decision-making process in human users. In particular, we focus on automatically determining whether changes in ethical education influenced core moral values in humans throughout the century. We analyze ethics as taught in Japan before WWII and today to verify how much the pre-WWII moral attitudes have in common with those of contemporary Japanese, to what degree what is taught as ethics in school overlaps with the general population’s understanding of ethics, as well as to verify whether a major reform of the guidelines for teaching the school subject of “ethics” at school after 1946 has changed the way common people approach core moral questions (such as those concerning the sacredness of human life). We selected textbooks used in teaching ethics at school from between 1935 and 1937, and those used in junior high schools today (2019) and analyzed what emotional and moral associations such contents generated. The analysis was performed with an automatic moral and emotional reasoning agent and based on the largest available text corpus in Japanese as well as on the resources of a Japanese digital library. As a result, we found out that, despite changes in stereotypical view on Japan’s moral sentiments, especially due to historical events, past and contemporary Japanese share a similar moral evaluation of certain basic moral concepts, although there is a large discrepancy between how they perceive some actions to be beneficial to the society as a whole while at the same time being inconclusive when it comes to assessing the same action’s outcome on the individual performing them and in terms of emotional consequences. Some ethical categories, assessed positively before the war, while being associated with a nationalistic trend in education have also disappeared from the scope of interest of post- war society. The findings of this study support suggestions proposed by others that the development of personal AI systems requires supplementation with moral reasoning. Moreover, the paper builds upon this idea and further suggests that AI systems need to be aware of ethics not as a constant, but as a function with a correction on historical and cultural changes in moral reasoning.     

教与学的大脑：人际神经科学助推教育研究

如何从神经生理层面刻画教育活动的人际互动模式和动态性是教育神经科学面临的一个重要挑战。人际神经科学视角为其提供了可能的解决途径; 这一新兴的视角通过记录和分析进行同一认知活动时两人或多人大脑活动之间的关联, 来揭示大脑活动的群体模式。目前, 人际神经科学方法已被应用于教育研究, 例如监控教学过程、预测教学效果和识别教学影响因素, 相应的研究成果对教育活动具有重要启示。未来的研究者可以更多地关注不同学习水平的学生大脑的互动机制及人际神经科学方法应用于技能教学及线上教学评估的巨大潜力。     

感知易用性会影响网络游戏中虚拟商品的使用意愿么?——感知有用性和玩家神经质的作用

基于技术接受模型考察了网络游戏中虚拟商品感知易用性对其使用意愿的影响,以及感知有用性、玩家神经质在其中的作用。采用虚拟商品使用意愿问卷、感知易用性问卷、感知有用性问卷和大五人格量表神经质分量表对559名有过网络游戏经验的大学生进行调查。结果显示:(1)虚拟商品的感知易用性可显著正向预测使用意愿;感知有用性在两者间起中介作用;(2)虚拟商品感知有用性的中介作用受到玩家神经质的调节:对于低神经质的玩家,该间接效应显著;而对于高神经质的玩家,该间接效应不显著。     

Exploring the complex emotional relationships that influence children's participation rights in early childhood education settings

Early childhood educators engage in complex and emotional work in their professional role educating and caring for children aged from birth to five years. The aim of this paper is to promote autoethnography as a most suitable method of understanding the role emotions play in the actualisation of young children's participation rights in early childhood education services. The author is a practising educator and draws upon a specific auto-ethnographic account of practice, the story of Sarah, as the focus of this paper to explore the emotional intensity of relationships in early childhood education. Autoethnography is discussed as a method to sit alongside ‘traditional’ ethnographic research to provide a deep understanding of the role of the educator embracing and enacting a rights approach in their work and what influences their decision making. In conclusion the author suggests autoethnography is a useful reflexive tool for educators to consider the role of emotions as a catalyst for change to ensure the actualisation of children's participation rights in daily practice in early childhood education.     

青少年创伤后应激障碍症状与网络成瘾症状的关系：惩罚敏感性和孤独感的中介及性别的调节

汶川地震9.5年后,对汶川县和都江堰市767名中学生进行调查,考察惩罚敏感性和孤独感在创伤后应激障碍症状和网络成瘾症状之间的多重中介作用及性别差异。结果发现：（1）PTSD症状正向预测网络成瘾症状,并分别通过惩罚敏感性、孤独感的单独中介作用及两者的链式中介作用显著预测网络成瘾症状;（2）女性的PTSD症状显著正向预测网络成瘾症状,并分别通过惩罚敏感性和孤独感间接影响网络成瘾症状;男性的网络成瘾症状仅被PTSD症状正向预测。