Personality and performance on digit span tests in online and offline settings.

This paper describes two studies examining links between personality and performance on a cognitive test in online and laboratory settings. Study 1 was completed online. 345 participants passively recruited through a personality assessment website completed a Five Factor Model personality inventory derived from the International Personality Item Pool. They then completed an online text-based digit span test. This required participants to repeat increasingly longer strings of digits, either in the same order (forward) or in the opposite of the presentation order (reverse). Conventional digit span tasks ask participants to respond verbally; in this instance they responded by typing the digits. Agreeableness and Openness to Experience each had small but significant associations with forward and reverse digit span. In a second, laboratory based, study, 103 participants completed paper versions of the IPIP Five Factor inventory, the NEO-FFI, and a battery of cognitive tests including the WAIS 4 digit span test. In this instance, Agreeableness and Openness to Experience were not significantly correlated with digit span measures. Taken together, these studies suggest that personality characteristics may influence performance on an online cognitive test. This effect was not seen in an offline version of the study. The paper will consider potential implications for online testing, for equivalence of online and offline methods, and for links between personality and performance on this cognitive test.

The Data of Things: Strategies, Patterns and Practice of Cloud-based Participatory Sensing

The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.