A methodology for creating and validating psychological stories for conveying and measuring psychological traits

Neurocircuitry of Personality Traits and Intent in Decision-Making

Even though most personality features are moderately stable throughout life, changes can be observed, which influence one's behavioral patterns. A variety of subjective assessments can be performed to track these changes; however, the subjective characteristic of these assessments may lead to questions about intentions and values. The use of neuroimaging techniques may aid the investigation of personality traits through a more objective lens, overcoming the barriers imposed by confounders. Here, neurocircuits associated with changes in personality domains were investigated to address this issue. Cortical systems involved in traits such as extraversion and neuroticism were found to share multiple components, as did traits of agreeableness and conscientiousness, with these four features revolving around the activation and structural integrity of the medial prefrontal cortex (mPFC). The attribute of openness appears scattered throughout cortical and subcortical regions, being discussed here as a possible reflection of intent, at the same time modulating and being governed by other traits. Insights on how systems operate on personality may increase comprehension on factors acting on the evolution, development, and consolidation of personality traits through life, as in neurocognitive disorders.

How Personality and Communication Patterns Affect Online ad-hoc Teams Under Pressure

Critical, time-bounded, and high-stress tasks, like incident response, have often been solved by teams that are cohesive, adaptable, and prepared. Although a fair share of the literature has explored the effect of personality on various other types of teams and tasks, little is known about how it contributes to teamwork when teams of strangers have to cooperate ad-hoc, fast, and efficiently. This study explores the dynamics between 120 crowd participants paired into 60 virtual dyads and their collaboration outcome during the execution of a high-pressure, time-bound task. Results show that the personality trait of Openness to experience may impact team performance with teams with higher minimum levels of Openness more likely to defuse the bomb on time. An analysis of communication patterns suggests that winners made more use of action and response statements. The team role was linked to the individual's preference of certain communication patterns and related to their perception of the collaboration quality. Highly agreeable individuals seemed to cope better with losing, and individuals in teams heterogeneous in Conscientiousness seemed to feel better about collaboration quality. Our results also suggest there may be some impact of gender on performance. As this study was exploratory in nature, follow-on studies are needed to confirm these results. We discuss how these findings can help the development of AI systems to aid the formation and support of crowdsourced remote emergency teams.

Personality-Based Affective Adaptation Methods for Intelligent Systems

In this article, we propose using personality assessment as a way to adapt affective intelligent systems. This psychologically-grounded mechanism will divide users into groups that differ in their reactions to affective stimuli for which the behaviour of the system can be adjusted. In order to verify the hypotheses, we conducted an experiment on 206 people, which consisted of two proof-of-concept demonstrations: a “classical” stimuli presentation part, and affective games that provide a rich and controllable environment for complex emotional stimuli. Several significant links between personality traits and the psychophysiological signals (electrocardiogram (ECG), galvanic skin response (GSR)), which were gathered while using the BITalino (r)evolution kit platform, as well as between personality traits and reactions to complex stimulus environment, are promising results that indicate the potential of the proposed adaptation mechanism.

Adapting Learning Activity Selection to Emotional Stability and Competence

This paper investigates how humans adapt next learning activity selection (in particular the knowledge it assumes and the knowledge it teaches) to learner personality and competence to inspire an adaptive learning activity selection algorithm. First, the paper describes the investigation to produce validated materials for the main study, namely the creation and validation of learner competence statements. Next, through an empirical study, we investigate the impact on learning activity selection of learners' emotional stability and competence. Participants considered a fictional learner with a certain competence, emotional stability, recent and prior learning activities engaged in, and selected the next learning activity in terms of the knowledge it used and the knowledge it taught. Three algorithms were created to adapt the selection of learning activities' knowledge complexity to learners' personality and competence. Finally, we evaluated the algorithms through a study with teachers, resulting in an algorithm that selects learning activities with varying assumed and taught knowledge adapted to learner characteristics.