Individualised Resources: Definition and Efficiency in the Russian EFL Classroom
In order to plan lessons that include effective instructional strategies, it is critical for teachers to be aware of student aptitudes, personality variables, learning strategies, interests, aspirations, and talents. This paper presents a way for Russian teachers to improve their students’ speaking abilities when learning foreign languages, called individualised resources, which are based on the concept of individualisation. Individualised resources are designed to help students to actively participate in the learning process, contribute to their productivity of learning and compensate for missing abilities when mastering foreign languages. In order to verify the effectiveness of this educational tool, qualitative and quantitative indicators were applied to a classroom-based study. Research findings illustrate how the approach enhanced the students’ speaking abilities in terms of purposefulness, richness of speech content and logical progression of speech. The results presented in the article indicate that this type of training may be sufficient to shape speaking skills when teaching English.
The paper presents a study of mechanisms of choice in a real life situation of local authorities elections. We have hypothesized that the quality of choice process as reflected through subjective evaluations might differ depending on some personality variables and, in turn, predict the satisfaction with choice and other outcome variables. The dependent variable was the decision whether to go voting at all. This assumption has been proven in a study on non-psychology college students (N=174) tested three times: a week before regional elections, a week after, and several months later. We used the measures of quality of choice and a number of personality inventories (assessing subjective alienation, purpose in life, locus of control, hardiness, causality orientations and some other variables).
As predicted, the qualitative parameters of choice process have been associated with personality variables, and, in turn, predicted the evaluation of outcomes. Cluster analysis (Ward’s method) has split the sample into two distinctive groups by the quality of choice: involved (autonomous) vs. noninvolved (spontaneous) one. Both groups revealed notable differences by personality variables.
Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies.
Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.
Institutions affect investment decisions, including investments in human capital. Hence institutions are relevant for the allocation of talent. Good market-supporting institutions attract talent to productive value-creating activities, whereas poor ones raise the appeal of rent-seeking. We propose a theoretical model that predicts that more talented individuals are particularly sensitive in their career choices to the quality of institutions, and test these predictions on a sample of around 95 countries of the world. We find a strong positive association between the quality of institutions and graduation of college and university students in science, and an even stronger negative correlation with graduation in law. Our findings are robust to various specifications of empirical models, including smaller samples of former colonies and transition countries. The quality of human capital makes the distinction between educational choices under strong and weak institutions particularly sharp. We show that the allocation of talent is an important link between institutions and growth.