Performance aux tests d'intelligence : vers une inversion de l'effet Flynn ?

Des nombreuses études ont montré une augmentation des scores aux tests d'aptitudes à travers les générations (« effet Flynn »). Différentes hypothèses d'ordre biologique, social et/ou éducationnels ont été élaborées afin d'expliquer ce phénomène. L'objectif de cette recherche est d'examiner l'évolution des performances aux tests d'aptitudes sur la base d'étalonnages datant de 1991 et de 2002. Les résultats suggèrent une inversion non homogène de l'effet Flynn. La diminution concerne plus particulièrement les tests d'aptitudes scolaires, comme ceux évaluant le facteur verbal et numérique. Cette étude pourrait refléter un changement de l'importance accordée aux différentes aptitudes peu évaluées en orientation scolaire et professionnelle.

Deception-detection and machine intelligence in practical Turing tests

Deception-detection is the crux of Turing’s experiment to examine machine thinking conveyed through a capacity to respond with sustained and satisfactory answers to unrestricted questions put by a human interrogator. However, in 60 years to the month since the publication of Computing Machinery and Intelligence little agreement exists for a canonical format for Turing’s textual game of imitation, deception and machine intelligence. This research raises from the trapped mine of philosophical claims, counter-claims and rebuttals Turing’s own distinct five minutes question-answer imitation game, which he envisioned practicalised in two different ways: a) A two-participant, interrogator-witness viva voce, b) A three-participant, comparison of a machine with a human both questioned simultaneously by a human interrogator. Using Loebner’s 18th Prize for Artificial Intelligence contest, and Colby et al.’s 1972 transcript analysis paradigm, this research practicalised Turing’s imitation game with over 400 human participants and 13 machines across three original experiments. Results show that, at the current state of technology, a deception rate of 8.33% was achieved by machines in 60 human-machine simultaneous comparison tests. Results also show more than 1 in 3 Reviewers succumbed to hidden interlocutor misidentification after reading transcripts from experiment 2. Deception-detection is essential to uncover the increasing number of malfeasant programmes, such as CyberLover, developed to steal identity and financially defraud users in chatrooms across the Internet. Practicalising Turing’s two tests can assist in understanding natural dialogue and mitigate the risk from cybercrime.

Rumors of the death of emotional intelligence in organizational behavior are vastly exaggerated

In the first of two articles presenting the case for emotional intelligence in a point/counterpoint exchange, we present a brief summary of research in the field, and rebut arguments against the construct presented in this issue.We identify three streams of research: (1) a four-branch abilities test based on the model of emotional intelligence defined in Mayer and Salovey (1997); (2) self-report instruments based on the Mayer–Salovey model; and (3) commercially available tests that go beyond the Mayer–Salovey definition. In response to the criticisms of the construct, we argue that the protagonists have not distinguished adequately between the streams, and have inappropriately characterized emotional intelligence as a variant of social intelligence. More significantly, two of the critical authors assert incorrectly that emotional intelligence research is driven by a utopian political agenda, rather than scientific interest. We argue, on the contrary, that emotional intelligence research is grounded in recent scientific advances in the study of emotion; specifically regarding the role emotion plays in organizational behavior. We conclude that emotional intelligence is attracting deserved continuing research interest as an individual difference variable in organizational behavior related to the way members perceive, understand, and manage their emotions.

Emotional awareness and emotional intelligence in leadership teaching

Recent research has highlighted the importance of emotional awareness and emotional intelligence in organizations, and these topics are attracting increasing attention. In this article, the authors present the results of a preliminary classroom study in which emotion concepts were incorporated into an undergraduate leadership course. In the study, students completed self report and ability tests of emotional intelligence. The test results were compared with students' interest in emotions and their performance in the course assessment. Results showed that interest in and knowledge of emotional intelligence predicted team performance, whereas individual performance was related to emotional intelligence.

Brazilian Adaptation of the Woodcock-Johnson III Cognitive Tests

An adaptation of the standard battery of Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III) for Brazilian children and youth was investigated. The sample was composed of 1094 students (54 percent girls), ages 7-17, living in Sao Paulo state (91 percent). Items from Brazilian school books as well as from the WJ-III Spanish version (Bateria-R) were added to comprehension-knowledge tests. Brazilian words were adapted to the auditory tests according to syllabic division and stressed syllables. Items were examined through IRT and age differences through analysis of variance. Results indicated the need to remove items from all WJ-III subtests with the exception of the visual learning test. Analysis of Variance indicated significant age differences (p <= 0.001) for all tests. Thus, the importance of a Brazilian adaptation for the WJ-III was confirmed.

Cultural Intelligence (CQ) in Erasmus Mundus Students and Alumni: an exploratory study on the levels and antecedents of CQ

Erasmus Mundus Masters (EMM) are programs with a strong component of interculturality. Our study aimed at understanding the level of cultural intelligence (CQ) of EMM students and alumni, as well as some of the characteristics associated with higher levels of CQ. The study included 626 EMM students and alumni from 109 different countries that encompasses 6 continents. Ang and Van Dyne’s (2006) cultural intelligence scale was used; closed and open ended questions were used to describe the sample’s sociodemographic characteristics and experiences regarding interculturality. After validating and assessing the scale’s psychometric properties, relations between different variables were explored using Pearson’s correlation, ANOVA, t Tests, and GLM procedures. We then analysed the open ended responses to gain further insight on our results. Differences among respondents are mainly equated with international experience rather than nationality or training. Respondents’ open ended replies provided us with a deeper insight on why training seems to be so ineffective in developing CQ. This is a transversal study that uses self-reporting measures; also, questionnaires were conducted in English, which was not the mother tongue of most of the respondents. This work is consistent with the CQ literature, however we argue that training mentioned by respondents systematically fails to meet some of literature’s foremost conditions for effective CQ trainings and provide clues for the implementation of more successful initiatives. With an exceptionally diverse sample, this study contributes towards the understanding of mechanisms of developing CQ among EMM and international Students. Results can be useful for selection processes, training/development of CQ and reducing dropout/turnover.

User-centered design of the interface prototype of a business intelligence mobile application

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Emotional intelligence: On definitions, neuroscience, and marshmallows

In his timely article, Cherniss offers his vision for the future of "Emotional Intelligence" (EI). However, his goal of clarifying the concept by distinguishing definitions from models and his support for "Emotional and Social Competence" (ESC) models will, in our opinion, not make the field advance. To be upfront, we agree that emotions are important for effective decision-making, leadership, performance and the like; however, at this time, EI and ESC have not yet demonstrated incremental validity over and above IQ and personality tests in meta-analyses (Harms & Credé, 2009; Van Rooy & Viswesvaran, 2004). If there is a future for EI, we see it in the ability model of Mayer, Salovey and associates (e.g, Mayer, Caruso, & Salovey, 2000), which detractors and supporters agree holds the most promise (Antonakis, Ashkanasy, & Dasborough, 2009; Zeidner, Roberts, & Matthews, 2008). With their use of quasi-objective scoring measures, the ability model grounds EI in existing frameworks of intelligence, thus differentiating itself from ESC models and their self-rated trait inventories. In fact, we do not see the value of ESC models: They overlap too much with current personality models to offer anything new for science and practice (Zeidner, et al., 2008). In this commentary we raise three concerns we have with Cherniss's suggestions for ESC models: (1) there are important conceptual problems in both the definition of ESC and the distinction of ESC from EI; (2) Cherniss's interpretation of neuroscience findings as supporting the constructs of EI and ESC is outdated, and (3) his interpretation of the famous marshmallow experiment as indicating the existence of ESCs is flawed. Building on the promise of ability models, we conclude by providing suggestions to improve research in EI.

The ability model of emotional intelligence: Searching for valid measures

Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.

Predicting chick body mass by artificial intelligence-based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

Short-term storage and mental speed account for the relationship between working memory and fluid intelligence. 'El almacenamiento a corto plazo y la velocidad mental dan cuenta de la relaci??n entre memoria de trabajo e inteligencia fluida'

Resumen tomado de la publicaci??n

Adaptaci?? de l'escala verbal del Wechsler Intelligence Scale for Children (WISC) al catal??. 'Adaptaci??n de la escala verbal del Wechsler Intelligence Scale for Children (WISC) al catal??n'

Adaptar los tests de inteligencia WISC para poder evaluar as?? al individuo con respecto al grupo seg??n las habilidades valoradas en cada cultura. Reajustar el WISC a la cultura catalana; hasta ahora los tests eran castellanos y hace falta adaptarlos al entorno para que sean realmente efectivos. 413 ni??os de 16 escuelas escogidas al azar. Edad entre 6 y 12 a??os. An??lisis exhaustivo de la prueba de Wechsler y de la adaptaci??n TEA, revisi??n cr??tica y adaptaci??n catalana. Prueba piloto para cotejar la eficiencia. Correcci??n de la WISC creada a partir de las divergencias estad??sticas entre el standard y los resultados de la prueba piloto. Encuestas, Test de WISC original y adaptado, muestreo. Tablas, an??lisis estad??sticos de correlaci??n, an??lisis factorial, fiabilidad y baremos de tipificaci??n. Se ha conseguido obtener un test WISC mucho m??s adaptado a la realidad de Catalunya gracias a la eliminaci??n de errores y dificultades que generaban las versiones Wechsler y TEA anteriores.

Hidden interlocutor misidentification in practical Turing Tests

Based on insufficient evidence, and inadequate research, Floridi and his students report inaccuracies and draw false conclusions in their Minds and Machines evaluation, which this paper aims to clarify. Acting as invited judges, Floridi et al. participated in nine, of the ninety-six, Turing tests staged in the finals of the 18th Loebner Prize for Artificial Intelligence in October 2008. From the transcripts it appears that they used power over solidarity as an interrogation technique. As a result, they were fooled on several occasions into believing that a machine was a human and that a human was a machine. Worse still, they did not realise their mistake. This resulted in a combined correct identification rate of less than 56%. In their paper they assumed that they had made correct identifications when they in fact had been incorrect.

Some implications of a sample of practical Turing tests

A series of imitation games involving 3-participant (simultaneous comparison of two hidden entities) and 2-participant (direct interrogation of a hidden entity) were conducted at Bletchley Park on the 100th anniversary of Alan Turing’s birth: 23 June 2012. From the ongoing analysis of over 150 games involving (expert and non-expert, males and females, adults and child) judges, machines and hidden humans (foils for the machines), we present six particular conversations that took place between human judges and a hidden entity that produced unexpected results. From this sample we focus on features of Turing’s machine intelligence test that the mathematician/code breaker did not consider in his examination for machine thinking: the subjective nature of attributing intelligence to another mind.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.