Systemizers are better code-breakers: self-reported systemizing predicts code-breaking performance in expert hackers and naïve participants

Studies on hacking have typically focused on motivational aspects and general personality traits of the individuals who engage in hacking; little systematic research has been conducted on predispositions that may be associated not only with the choice to pursue a hacking career but also with performance in either naïve or expert populations. Here, we test the hypotheses that two traits that are typically enhanced in autism spectrum disorders—attention to detail and systemizing—may be positively related to both the choice of pursuing a career in information security and skilled performance in a prototypical hacking task (i.e., crypto-analysis or code-breaking). A group of naïve participants and of ethical hackers completed the Autism Spectrum Quotient, including an attention to detail scale, and the Systemizing Quotient (Baron-Cohen et al., 2001, 2003). They were also tested with behavioral tasks involving code-breaking and a control task involving security X-ray image interpretation. Hackers reported significantly higher systemizing and attention to detail than non-hackers. We found a positive relation between self-reported systemizing (but not attention to detail) and code-breaking skills in both hackers and non-hackers, whereas attention to detail (but not systemizing) was related with performance in the X-ray screening task in both groups, as previously reported with naïve participants (Rusconi et al., 2015). We discuss the theoretical and translational implications of our findings

Self-Efficacy and Engagement as Predictors of Student Programming Performance

Programming is a core subject introduced in the first year of an Undergraduate Computer Science programme. Since programming is a core subject, it is a major concern that high attrition and failure rates continue to be reported in such courses. Evidence from the literature suggests that programming is cognitively demanding, and the solutions proposed have had minimal impact on students in introductory programming courses. However, in the literature on learning theory, there is evidence suggesting that the self-efficacy beliefs of students affect their engagement, and that their engagement affects their performance. In the literature on introductory programming courses, there is a lack of research examining the effect of self-efficacy on engagement, and the effect of engagement on the programming performance of students. This leaves a gap in programming research that this research seeks to fill. Based on student engagement frameworks in the literature on learning theory, a conceptual model was developed. To operationalise and validate the conceptual model within the context of learning programming, a study consisting of focus group interviews and a survey on students in introductory programming courses is proposed. The results of the survey will be analysed using structural equation modelling (SEM) techniques

The Difference between Field Independent and Field Dependent Cognitive Styles regarding Translation Quality

Cognitive translation studies are one of the assorted fields under research in translation studies trying to deal with the complex cognitive process of translator while rendering. This study investigated the difference between field independent (FI) and field dependent (FD) English translation students in Iran concerning translation of an English literary text. 297 female and male undergraduate students at Islamic Azad University of Tehran participated in this study. The researcher administered two main tests in order, the piloted TOEFL test for homogenizing the participants in terms of English language proficiency and then GEFT test to recognize FI and FD students. Afterwards, FI and FD groups translated the same text. As a result of the statistical analysis it was signified that FI students outperformed the FD ones regarding translation of a literary text

Scrum como herramienta metodológica en el entrenamiento cooperativo de la programación: de la teoría a la práctica

El proceso de enseñanza y aprendizaje de la programación de computadoras no es una tarea fácil e impacta fuertemente en las asignaturas que tienen entre sus objetivos llevar adelante la práctica de la programación en carreras informáticas. Las dificultades del proceso es un problema recurrente que se evidencia en los últimos años a pesar de los esfuerzos de las instituciones nacionales por mejorar la calidad educativa en carreras universitarias. En este último sentido, se han puesto en práctica numerosas soluciones que no resultaron efectivas. La falta de motivación en los alumnos y las dificultades en el desarrollo de habilidades que deben adquirir, provocan que el aprendizaje y la práctica de la programación sea una de las causas de deserción en los primeros años de las carreras informáticas. El presente trabajo expone una experiencia metodológica que resalta la enseñanza y práctica cooperativa en el marco de trabajo propuesto por Scrum, con el objeto de promover acciones cooperativas y colaborativas en equipo y la adquisición de habilidades propias del programador en el desarrollo ágil de software. Se muestran resultados experimentales sobre dos asignaturas: Programación Numérica y Cálculo Numérico de la carrera Licenciatura en Análisis de Sistemas de la Universidad Nacional de Salta.Área: Tecnología en Educación.Red de Universidades con Carreras en Informática (RedUNCI

Scrum como herramienta metodológica en el entrenamiento cooperativo de la programación: de la teoría a la práctica

El proceso de enseñanza y aprendizaje de la programación de computadoras no es una tarea fácil e impacta fuertemente en las asignaturas que tienen entre sus objetivos llevar adelante la práctica de la programación en carreras informáticas. Las dificultades del proceso es un problema recurrente que se evidencia en los últimos años a pesar de los esfuerzos de las instituciones nacionales por mejorar la calidad educativa en carreras universitarias. En este último sentido, se han puesto en práctica numerosas soluciones que no resultaron efectivas. La falta de motivación en los alumnos y las dificultades en el desarrollo de habilidades que deben adquirir, provocan que el aprendizaje y la práctica de la programación sea una de las causas de deserción en los primeros años de las carreras informáticas. El presente trabajo expone una experiencia metodológica que resalta la enseñanza y práctica cooperativa en el marco de trabajo propuesto por Scrum, con el objeto de promover acciones cooperativas y colaborativas en equipo y la adquisición de habilidades propias del programador en el desarrollo ágil de software. Se muestran resultados experimentales sobre dos asignaturas: Programación Numérica y Cálculo Numérico de la carrera Licenciatura en Análisis de Sistemas de la Universidad Nacional de Salta.Área: Tecnología en Educación.Red de Universidades con Carreras en Informática (RedUNCI

Scrum como herramienta metodológica en el entrenamiento cooperativo de la programación: de la teoría a la práctica

El proceso de enseñanza y aprendizaje de la programación de computadoras no es una tarea fácil e impacta fuertemente en las asignaturas que tienen entre sus objetivos llevar adelante la práctica de la programación en carreras informáticas. Las dificultades del proceso es un problema recurrente que se evidencia en los últimos años a pesar de los esfuerzos de las instituciones nacionales por mejorar la calidad educativa en carreras universitarias. En este último sentido, se han puesto en práctica numerosas soluciones que no resultaron efectivas. La falta de motivación en los alumnos y las dificultades en el desarrollo de habilidades que deben adquirir, provocan que el aprendizaje y la práctica de la programación sea una de las causas de deserción en los primeros años de las carreras informáticas. El presente trabajo expone una experiencia metodológica que resalta la enseñanza y práctica cooperativa en el marco de trabajo propuesto por Scrum, con el objeto de promover acciones cooperativas y colaborativas en equipo y la adquisición de habilidades propias del programador en el desarrollo ágil de software. Se muestran resultados experimentales sobre dos asignaturas: Programación Numérica y Cálculo Numérico de la carrera Licenciatura en Análisis de Sistemas de la Universidad Nacional de Salta.Área: Tecnología en Educación.Red de Universidades con Carreras en Informática (RedUNCI

Les facteurs contribuant à la réussite dans les cours d'introduction en programmation.

This study looked at the reasons why Vanier College students in computer programming are encountering difficulties in their learning process, Factors such as prior academic background, prior computer experience, mother tongue, and learning styles were examined to see how they play a role in students' success in programming courses. The initial research hypotheses were the following : Computer science students using understanding and integrating succeed better than students using following coding, or problem solving. Students using problem solving succeed better than those who use participating and enculturation. Students who use coding perform better than those who prefer participating ans enculturation. In addition, this study hoped to examine whether there is a gender difference in how students learn programming.||Résumé :||La présente étude a examiné les raisons pour lesquelles les étudiants en informatique du Collège Vanier rencontrent des difficultés dans leurs études en programmation. Les facteurs tel que le niveau des études précédentes, l'expérience en informatique, la langue maternelle e les méthodes d'apprentissage ont été considérés pour voir quel rôle ces facteurs jouent pour promouvoir la réussite dans les cours de programmation.Les hypothèses initiales de recherche ont été formulées comme suit : 1. Les étudiants en informatique utilisant la compréhension et l'intégration réussissent mieux que ceux utilisant «suivre», le codage ou la résolution des problèmes. 2, Les étudiants utilisant la résolution des problèmes réussissent mieux que ceux qui utilisent la participation dans la culture informatique. 3, Les étudiants utilisant le codage réussissent mieux que ceux qui utilisent la participation dans la culture informatique

An Exploration of Traditional and Data Driven Predictors of Programming Performance

This thesis investigates factors that can be used to predict the success or failure of students taking an introductory programming course. Four studies were performed to explore how aspects of the teaching context, static factors based upon traditional learning theories, and data-driven metrics derived from aspects of programming behaviour were related to programming performance. In the first study, a systematic review into the worldwide outcomes of programming courses revealed an average pass rate of 67.7\%. This was found to have not significantly changed over time, or to have differed based upon aspects of the teaching context, such as the programming language taught to students. The second study showed that many of the factors based upon traditional learning theories, such as learning styles, are context dependent, and fail to consistently predict programming performance when they are applied across different teaching contexts. The third study explored data-driven metrics derived from the programming behaviour of students. Analysing data logged from students using the BlueJ IDE, 10 new data-driven metrics were identified and validated on three independently gathered datasets. Weaker students were found to make a greater percentage of successive errors, and spend a greater percentage of their lab time resolving errors than stronger students. The Robust Relative algorithm was developed to hybridize four of the strongest data-driven metrics into a performance predictor. The novel relative scoring of students based upon how their resolve times for different types of errors compared to the resolve times of their peers, resulted in a predictor which could explain a large proportion of the variance in the performance of three independent cohorts, $R^2$ = 42.19\%, 43.65\% and 44.17\% - almost double the variance which could be explained by Jadud's Error Quotient metric. The fourth study situated the findings of this thesis within the wider literature, by applying meta-analysis techniques to statistically synthesise fifty years of conflicting research, such that the most important factors for learning programming could be identified. 482 results describing the effects of 116 factors on programming performance were synthesised and consolidated to form a six class theoretical framework. The results showed that the strongest predictors identified over the past fifty years are data-driven metrics based upon programming behaviour. Several of the traditional predictors were also found to be influential, suggesting that both a certain level of scientific maturity and self-concept are necessary for programming. Two thirds of the weakest predictors were based upon demographic and psychological factors, suggesting that age, gender, self-perceived abilities, learning styles, and personality traits have no relevance for programming performance. This thesis argues that factors based upon traditional learning theories struggle to consistently predict programming performance across different teaching contexts because they were not intended to be applied for this purpose. In contrast, the main advantage of using data-driven approaches to derive metrics based upon students' programming processes, is that these metrics are directly based upon the programming behaviours of students, and therefore can encapsulate such changes in their programming knowledge over time. Researchers should continue to explore data-driven predictors in the future