The ability model of emotional intelligence: Principles and updates

This article presents seven principles that have guided our thinking about emotional intelligence, some of them new. We have reformulated our original ability model here guided by these principles, clarified earlier statements of the model that were unclear, and revised portions of it in response to current research. In this revision, we also positioned emotional intelligence amidst other hot intelligences including personal and social intelligences, and examined the implications of the changes to the model. We discuss the present and future of the concept of emotional intelligence as a mental ability

Forecasting ability of a multi-renewal seismicity model for Italy

The inter-event time, IET, is sometimes used as a basis for prediction of large earthquakes. It is the case when theoretical analysis of prediction is possible. Quite recently a specific IET- model was suggested for dynamic probabilistic prediction of M > 5.5 events in Italy . In this study we analyze both some aspects of the statistical estimation of the model and its predictive ability. We find that more or less effective prediction is possible within 4 out of 34 seismotectonic zones where seismicity rate or clustering of events is relatively high. We show that, in the framework of the model, one can suggest a simple zone independent strategy, which practically optimizes the relative number of nonaccidental successes, or the Hanssen-Kuiper, HK, skill score. This quasi-optimal strategy declares alarm in a zone for the first 2.67 years just after the occurrence of each large event in the zone. The optimal HK skill score values are: 26% for the 3 most active zones and 2-10% for the 26 least active zones. However, the number of false alarm time intervals per one event in each of the zones is unusually high: 0.7 and 0.8-0.95 respectively. Both these theoretical estimations are important because any prospective testing of the model is unrealistic in most of the zones during a reasonable time. This particular analysis requires a discussion of the following issues of general interest: a specific approach to the analysis of predictions vs. the standard CSEP testing approach; prediction vs. forecasting; HK skill score vs. probability gain; the total forecast error diagram and connected false alarms.Comment: 21 pages, 3 figure

Emotional intelligence and hot and cool working memory capacity

Emotional Intelligence (EI) is the ability to perceive, use, understand and manage our emotions and the emotions of others. EI, measured through performance-based ability models, seems to favour performance on hot tasks. The aim of the present study is to analyse the relationship between EI, measured through its three main models, and performance on a hot (emotional) and cool (non-emotional) working memory task. 203 undergraduate students of psychology took part in the experiment. They completed an EI test for each of its three main models (performance-based ability model, self-report ability model and self-report mixed model) and a hot and cool working memory task. We found a better performance for higher EI participants, measured through the performance-based ability model instrument (but not with self-report instruments), in the hot working memory task. This result was obtained for the managing branch of the EI instrument. Similar evidence was not found when using the cool working memory task. Our study takes a step forward in the conceptualization of the EI construct within the domain of cognitive processes. They show that, at least when using hot stimuli, the managing branch of the performance-based ability model of EI is a better determinant measure for the working memory capacity than the self-report models.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Latent Process Model for Dementia and Psychometric Tests

We jointly model longitudinal values of a psychometric test and diagnosis of dementia. The model is based on a continuous-time latent process representing cognitive ability. The link between the latent process and the observations is modeled in two phases. Intermediate variables are noisy observations of the latent process; scores of the psychometric test and diagnosis of dementia are obtained by categorizing these intermediate variables. We propose maximum likelihood inference for this model and we propose algorithms for performing this task. We estimated the parameters of such a model using the data of the five-year follow-up of the PAQUID study. In particularThis analysis yielded interesting results about the effect of educational level on both latent cognitive ability and specific performance in the mini mental test examination. The predictive ability of the model is illustrated by predicting diagnosis of dementia at the eight-year follow-up of the PAQUID study bsed on the information of the first five years.Comment: 29 pages 3 figure

The General Motor Ability Hypothesis: An old idea revisited

While specific motor abilities have become a popular explanation for motor performance, the older, alternate notion of a general motor ability should be revisited. Current theories lack consensus, and most motor assessment tools continue to derive a single composite score to represent motor capacity. In addition, results from elegant statistical procedures such as higher order factor analyses, cluster analyses, and Item Response Theory support a more global motor ability. We propose a contemporary model of general motor ability as a unidimensional construct that is emergent and fluid over an individual’s lifespan, influenced by both biological and environmental factors. In this article, we address the implications of this model for theory, practice, assessment, and research. Based on our hypothesis and Item Response Theory, our Lifespan Motor Ability Scale can identify motor assessment tasks that are relevant and important across varied phases of lifespan development

The glass-forming ability of model metal-metalloid alloys

Bulk metallic glasses (BMGs) are amorphous alloys with desirable mechanical properties and processing capabilities. To date, the design of new BMGs has largely employed empirical rules and trial-and-error experimental approaches. Ab initio computational methods are currently prohibitively slow to be practically used in searching the vast space of possible atomic combinations for bulk glass formers. Here, we perform molecular dynamics simulations of a coarse-grained, anisotropic potential, which mimics interatomic covalent bonding, to measure the critical cooling rates for metal-metalloid alloys as a function of the atomic size ratio $\sigma_S/\sigma_L$ and number fraction $x_S$ of the metalloid species. We show that the regime in the space of $\sigma_S/\sigma_L$ and $x_S$ where well-mixed, optimal glass formers occur for patchy and LJ particle mixtures coincides with that for experimentally observed metal-metalloid glass formers. Our simple computational model provides the capability to perform combinatorial searches to identify novel glass-forming alloys.Comment: 6 pages, 5 figure

PERBEDAAN KEMAMPUAN KOGNITIF DAN KETERAMPILAN KOOPERATIF DALAM PEMBELAJARAN KOOPERATIF MODEL JIGSAW DAN COOPERATIV SCRIPT SISWA KELAS VIII MTS MUHAMMADIYAH 1 MALANG

Cooperative learning is a study which focused on cooperation among students to reach learning goal. Cooperative learning with Jigsaw Model and Cooperative Script were two cooperative learning model which had many characteristic similarity. The characteristic similarity became background of study. Statement of problems in the research was whether any different of cognitive ability and cooperative skill of students using cooperative learning with Jigsaw model and cooperative script. \ud The research had three purposes, the first was to find out whether any different of cognitive ability using jigsaw model and cooperative script. The second was to find out whether any different in students cooperative skill using Jigsaw model and cooperative script. The third was students perception to the cooperative learning. \ud The research used was quasi-experiment using two group research pretest and posttest design. Population were students of VIIIA, VIIIB, and VIIIC degree Islamic School (MTs) Muhammadiyah I Malang. Samples used were two class taken by random sampling technique. \ud They were VIIIB as cooperative learning jigsaw model class, VIIIC as cooperative learning cooperative script model class. Data collected were analyzed using normality and homogeneity test, data then analyzed by t-test differential test. \ud The research showed that there were difference among cognitive ability and cooperative skill of students taught by cooperative learning jigsaw model and cooperative script. It was proven from t-test with t-count = 2,16 > t-table = 2,04 for cognitive ability data. Cooperative skill data analysis found t-count 4,54>t-table = 2,04. Data analysis showed that cognitive ability and cooperative skill taught by jigsaw model was better than students taught by cooperative script. \ud Students responds about cooperative learning Jigsaw model with most answers were agree to the statement in the questionnaire with percentage 79%, and 75,27 % in cooperative script for agree answer

Evaluating Variable Length Markov Chain Models for Analysis of User Web Navigation Sessions

Markov models have been widely used to represent and analyse user web navigation data. In previous work we have proposed a method to dynamically extend the order of a Markov chain model and a complimentary method for assessing the predictive power of such a variable length Markov chain. Herein, we review these two methods and propose a novel method for measuring the ability of a variable length Markov model to summarise user web navigation sessions up to a given length. While the summarisation ability of a model is important to enable the identification of user navigation patterns, the ability to make predictions is important in order to foresee the next link choice of a user after following a given trail so as, for example, to personalise a web site. We present an extensive experimental evaluation providing strong evidence that prediction accuracy increases linearly with summarisation ability