Fuzzy rough sets: Survey and proposal of an enhanced knowledge representation model based on automatic noisy sample detection

Fuzzy Rough Set (FRS) theory, which has been emerged thanks to unifying Rough Set and Fuzzy Set ones, is a powerful mathematical tool for handling and processing real data of imprecise, incomplete, inconsistent and uncertain nature. It has drawn attention of many researchers, scientists and industrials in various domains over the last three decades. However, different studies have showed that its classical knowledge representation model has a main weakness linked to its sensitivity to data noise which decreases both its effectiveness and application scope. In this paper, we survey the current FRS paradigms developed to deal with this issue and propose a new FRS model based on the Automatic Noisy Sample Detection (ANSD-FRS) able to cope with noise influence in classification tasks. Besides, we study the principal properties of this new model and reformulate the most applied FRS concepts relying on its operators. Numerous experiments have been conducted to analyze the ANSD-FRS behavior compared to the commonly used FRS models reputed as the most noise-resistant paradigms. These experiment results have proved the performance and robustness of the ANSD-FRS in comparison with those renowned models.     

The role of structural consistency between categories and attributes in hierarchical category learning

This study investigated how consistency between categories and attributes determines attribute selection in hierarchical category learning. Participants learned six categories for which number and color were equally relevant attributes, followed by a transfer task, to test which attribute was used. Before that, half of them learned embedding higher-level categories for which numbers were likely to be used. Orthogonal to this factor, the hierarchical structure was made explicit for half of them by category labels. The results showed that participants used numbers in the prior learning, but that the use of numbers was inhibited in the subsequent six-category learning task. However, this inhibitory effect was reduced when the hierarchical structure was explicit. The pattern of results suggests that attribute selection is determined by structural consistency between categories and attributes, not by a prior use of an attribute.     

Testing a Military Family Stress Model

The current study examines a military family stress model, evaluating associations between deployment‐related stressors (i.e., deployment length/number, posttraumatic stress disorder [PTSD] symptoms) and parent, child, parenting, and dyadic adjustment among families in which a parent had previously deployed to Iraq or Afghanistan in the recent conflicts. Married families (N = 293) with at least one child between the ages of 4 and 12 were recruited from a Midwestern state. Service members were from the Reserve Component (National Guard or Reserves); fathers (N = 253) and/or mothers had deployed (N = 45) to the recent conflicts in the Middle East. Multiple‐method (observations of parenting and couple interactions; questionnaires) and multiple informant measures were gathered online and in the homes of participants, from parents, children, and teachers. Findings demonstrated associations between mothers’ and fathers’ PTSD symptoms and a latent variable of child adjustment comprising teacher, parent, and child report. Mothers’ but not fathers’ PTSD symptoms were also associated with dyadic adjustment and parenting practices; parenting practices were in turn associated with child adjustment. The results are discussed in terms of their implications for military family stress research and interventions to support and strengthen parents and families after deployment.     

Effect of individual thinking styles on item selection during study time allocation

The influence of individual differences on learners' study time allocation has been emphasised in recent studies; however, little is known about the role of individual thinking styles (analytical versus intuitive). In the present study, we explored the influence of individual thinking styles on learners' application of agenda‐based and habitual processes when selecting the first item during a study‐time allocation task. A 3‐item cognitive reflection test (CRT) was used to determine individuals' degree of cognitive reliance on intuitive versus analytical cognitive processing. Significant correlations between CRT scores and the choices of first item selection were observed in both Experiment 1a (study time was 5 seconds per triplet) and Experiment 1b (study time was 20 seconds per triplet). Furthermore, analytical decision makers constructed a value‐based agenda (prioritised high‐reward items), whereas intuitive decision makers relied more upon habitual responding (selected items from the leftmost of the array). The findings of Experiment 1a were replicated in Experiment 2 notwithstanding ruling out the possible effects from individual intelligence and working memory capacity. Overall, the individual thinking style plays an important role on learners' study time allocation and the predictive ability of CRT is reliable in learners' item selection strategy.     

Recruiter Evaluation of Candidates for Employment: Does Study Abroad Make a Difference?

This analog study investigated recruiters’ evaluation of candidates for employment in regard to whether study abroad experience advantaged some in being selected for certain positions. Results found that candidates who completed study abroad and a relevant internship were ranked highest, with preference given by recruiters to long‐term Western experiences. However, the data also suggested that recruiter assessments varied somewhat depending on recruiters’ study abroad experience and their own characteristics. Overall, the effect of study abroad on the evaluation of candidates was simply one part of a complex of considerations.     

Training self‐assessment and task‐selection skills to foster self‐regulated learning: Do trained skills transfer across domains?

Students' ability to accurately self‐assess their performance and select a suitable subsequent learning task in response is imperative for effective self‐regulated learning. Video modeling examples have proven effective for training self‐assessment and task‐selection skills, and—importantly—such training fostered self‐regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task‐selection rule or a more general heuristic task‐selection rule in biology would transfer to self‐regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task‐selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self‐regulated learning in math. Future research should investigate how to support transfer of task‐selection skills across domains.