Designing and Implementing Interactive, Collaborative Family Literacy Events

Shared experiences through school-hosted events, such as family literacy events, can afford opportunities to support and extend academic learning while fostering positive home–school relationships. This article describes the importance of developing primary-grade students’ literacy skills through a talent development lens and explains several ways to nurture students’ literacy skills and recognize potential, gifts, and talents during family literacy events. This article features one of the activities from the family literacy events, Environmental Print Bingo, a modification of I-Spy and Bingo which uses rich and varied environmental print resources. A description of this activity, necessary resources, and implementation tips are provided. Options for differentiating this learning activity to provide more challenge for gifted learners are suggested. Throughout the article, the application of a pedagogy for early childhood gifted education and Sternberg’s triarchic theory of intelligence as a framework are discussed; these approaches informed the design of all family literacy activities. A brief overview of nine additional family literacy event activities is also shared. Welcoming and involving families of English learners is an important consideration in many communities, and therefore, preparation tips and considerations for facilitators that will help maximize the participation of all families are included. Finally, reflections and helpful advice for implementing family literacy events in your school communities are presented, including advice for implementing online family literacy events. Ultimately, this article should help readers conceptualize, plan, and implement family literacy events in their school communities.

The Effects of Primary Students' Mathematics Self-efficacy and Beliefs about Intelligence on Their Mathematics Achievement: A Mixed-methods Intervention Study

<p>A mixed-methods quasi-experimental methodology was used to identify relationships between primary-school students' beliefs about intelligence, mathematics self-efficacy, and achievement, by investigating the effects of two interventions. One intervention aimed to strengthen students' mathematics self-efficacy, and the other aimed to develop in students' an incremental theory-of-intelligence – a belief that intelligence is malleable. In one group, teachers implemented both interventions with their students; in a second group, teachers implemented only the mathematics self-efficacy intervention, and the third (control) group were involved in no intervention. Year 4 and 5 students (n = 152) completed a questionnaire on three occasions, at intervals of about 7 months, to measure their theory-of-intelligence and their mathematics self-efficacy. Students made self-efficacy judgments in relation to specific number problems, which they were subsequently required to solve for the mathematics achievement measure. Both achievement and self-efficacy were then calibrated for each participant using the difficulty parameters for test items. Teachers completed questionnaires about their theory-of-intelligence and self-efficacy for teaching mathematics. Sub-samples of teachers and students were interviewed to develop a deeper understanding of what their questionnaire responses signified. The combined interventions had no significant effect on students' beliefs about the malleability of intelligence, mathematics self-efficacy, or achievement. In contrast, positive effects on students' mathematics self-efficacy and achievement were evident for students who experienced only the self-efficacy intervention. Teachers in this intervention group reported increased use of three strategies aimed at building students' mathematics self-efficacy: providing students with strategies for coping when learning became difficult; increasing their use of descriptive teacher-student feedback; and increasing their use of similar peers as models. For the self-efficacy intervention group, increases in students' mathematics achievement and self-efficacy appeared to be reciprocally related. The combined quantitative and qualitative evidence from the study showed that the complexity of some students' and teachers' beliefs about increasing intelligence was not reflected in their total scores on the theory-of-intelligence items used widely in earlier studies. In interviews, all students and most teachers described intelligence as malleable to varying degrees, which did not support previous dichotomous interpretations of theory-of-intelligence data. From students' definitions of intelligence, two related dimensions were established, one a fairly stable capacity for acquiring knowledge and skill in a given domain, and the second, the more malleable rate at which such knowledge and skill can be acquired. A variety of beliefs were expressed by students about which of these dimensions intelligence includes, and about how malleable the dimensions are. The findings raise questions about the value of advocating an incremental theory-of-intelligence for all students, regardless of their ability and how they conceptualise intelligence.</p>

The Effects of Primary Students' Mathematics Self-efficacy and Beliefs about Intelligence on Their Mathematics Achievement: A Mixed-methods Intervention Study

<p>A mixed-methods quasi-experimental methodology was used to identify relationships between primary-school students' beliefs about intelligence, mathematics self-efficacy, and achievement, by investigating the effects of two interventions. One intervention aimed to strengthen students' mathematics self-efficacy, and the other aimed to develop in students' an incremental theory-of-intelligence – a belief that intelligence is malleable. In one group, teachers implemented both interventions with their students; in a second group, teachers implemented only the mathematics self-efficacy intervention, and the third (control) group were involved in no intervention. Year 4 and 5 students (n = 152) completed a questionnaire on three occasions, at intervals of about 7 months, to measure their theory-of-intelligence and their mathematics self-efficacy. Students made self-efficacy judgments in relation to specific number problems, which they were subsequently required to solve for the mathematics achievement measure. Both achievement and self-efficacy were then calibrated for each participant using the difficulty parameters for test items. Teachers completed questionnaires about their theory-of-intelligence and self-efficacy for teaching mathematics. Sub-samples of teachers and students were interviewed to develop a deeper understanding of what their questionnaire responses signified. The combined interventions had no significant effect on students' beliefs about the malleability of intelligence, mathematics self-efficacy, or achievement. In contrast, positive effects on students' mathematics self-efficacy and achievement were evident for students who experienced only the self-efficacy intervention. Teachers in this intervention group reported increased use of three strategies aimed at building students' mathematics self-efficacy: providing students with strategies for coping when learning became difficult; increasing their use of descriptive teacher-student feedback; and increasing their use of similar peers as models. For the self-efficacy intervention group, increases in students' mathematics achievement and self-efficacy appeared to be reciprocally related. The combined quantitative and qualitative evidence from the study showed that the complexity of some students' and teachers' beliefs about increasing intelligence was not reflected in their total scores on the theory-of-intelligence items used widely in earlier studies. In interviews, all students and most teachers described intelligence as malleable to varying degrees, which did not support previous dichotomous interpretations of theory-of-intelligence data. From students' definitions of intelligence, two related dimensions were established, one a fairly stable capacity for acquiring knowledge and skill in a given domain, and the second, the more malleable rate at which such knowledge and skill can be acquired. A variety of beliefs were expressed by students about which of these dimensions intelligence includes, and about how malleable the dimensions are. The findings raise questions about the value of advocating an incremental theory-of-intelligence for all students, regardless of their ability and how they conceptualise intelligence.</p>

Celebrity worship and cognitive skills revisited: applying Cattell’s two-factor theory of intelligence in a cross-sectional study

Background Almost two decades of research produced mixed findings on the relationship between celebrity worship and cognitive skills. Several studies demonstrated that cognitive performance slightly decreases with higher levels of celebrity worship, while other studies found no association between these constructs. This study has two aims: (1) to extend previous research on the association between celebrity worship and cognitive skills by applying the two-factor theory of intelligence by Cattell on a relatively large sample of Hungarian adults, and (2) to investigate the explanatory power of celebrity worship and other relevant variables in cognitive performance. Methods A cross-sectional study design was used. Applying an online survey, a total of 1763 Hungarian adults (66.42% male, Mage = 37.22 years, SD = 11.38) completed two intelligence subtests designed to measure ability in vocabulary (Vocabulary Test) and digit symbol (Short Digit Symbol Test). Participants also completed the Celebrity Attitude Scale and the Rosenberg Self-esteem Scale. Subjective material wealth, current family income and general sociodemographics were also reported by participants. Results Linear regression models indicated that celebrity worship was associated with lower performance on the cognitive tests even after controlling for demographic variables, material wealth and self-esteem, although the explanatory power was limited. Conclusions These findings suggest that there is a direct association between celebrity worship and poorer performance on the cognitive tests that cannot be accounted for by demographic and socioeconomic factors.

Quest for I (Intelligence) in AI (Artificial Intelligence): A Non-Elusive Attempt

This chapter essentially makes a non-elusive attempt in quest of ‘I’ (Intelligence) in ‘AI’ (Artificial Intelligence). In the year 1950, Alan Turing proposed “the imitation game” which was a gaming problem to make a very fundamental question — “can a machine think?”. The said article of Turing did not provide any tool to measure intelligence but produced a philosophical argument on the issue of intelligence. In 1950, Claude Shannon published a landmark paper on computer chess and rang the bell of the computer era. Over the past decades, there have been huge attempts to define and measure intelligence across the fields of cognitive psychology and AI. We critically appreciate these definitions and evaluation approaches in quest of intelligence, which can mimic the cognitive abilities of human intelligence. We arrive at the Cattell-Horn-Carroll (C–H–C) concept, which is a three-stratum theory for intelligence. The C–H–C theory of intelligence can be crudely approximated by deep meta-learning approach to integrate the representation power of deep learning into meta-learning. Thus we can combine crystallized intelligence with fluid intelligence, as they complement each other for robust learning, reasoning, and problem-solving in a generalized setup which can be a benchmark for flexible AI and eventually general AI. In far-reaching future to search for human-like intelligence in general AI, we may explore neuromorphic computing which is essentially based on biological neurons.

General Theory of Intelligence

In this paper, the dependence of the properties of the brain, its structure, functions and the higher nervous activity derived from them on the physical properties of the universe is analyzed.

Exploring Minds: Modes of Modeling and Simulation in Artificial Intelligence

The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them.

How the SP System May Promote Sustainability in Energy Consumption in IT Systems

The SP System (SPS), referring to the SP Theory of Intelligence and its realisation as the SP Computer Model, has the potential to reduce demands for energy from IT, especially in AI applications and in the processing of big data, in addition to reductions in CO2 emissions when the energy comes from the burning of fossil fuels. The biological foundations of the SPS suggest that with further development, the SPS may approach the extraordinarily low (20 W)energy demands of the human brain. Some of these savings may arise in the SPS because, like people, the SPS may learn usable knowledge from a single exposure or experience. As a comparison, deep neural networks (DNNs) need many repetitions, with much consumption of energy, for the learning of one concept. Another potential saving with the SPS is that like people, it can incorporate old learning in new. This contrasts with DNNs where new learning wipes out old learning (‘catastrophic forgetting’). Other ways in which the mature SPS is likely to prove relatively parsimonious in its demands for energy arise from the central role of information compression (IC) in the organisation and workings of the system: by making data smaller, there is less to process; because the efficiency of searching for matches between patterns can be improved by exploiting probabilities that arise from the intimate connection between IC and probabilities; and because, with SPS-derived ’Model-Based Codings’ of data, there can be substantial reductions in the demand for energy in transmitting data from one place to another.

Russian Law Enforcement Intelligence-Gathering Legislation: Problems and Ways to Address Them, Taking into Account the Experience of Some CIS Countries

Introduction: law enforcement practice and scientific research in the field of the theory of intelligence-gathering activities prove that current Russian intelligence-gathering legislation contains quite a few legal gaps and contradictions. The article provides a scientific analysis of a number of problematic issues concerning legal regulation of intelligence-gathering activities conducted in the Russian Federation, with an emphasis on the functioning of operational units of the penal system of the Russian Federation. Aim: to work out proposals to improve national intelligence-gathering legislation by reviewing intelligence-gathering legislation of CIS countries, analyzing the works of scientists on the theory of intelligence-gathering activities and regulatory framework for the work of operational units. Methods: comparative legal method, theoretical methods of formal and dialectical logic, specific scientific methods: legal-dogmatic method, interpretation of legal norms. Results: the article considers the inconsistency between the purpose of intelligence-gathering activities enacted in law and both the law enforcement practice and its legally defined tasks, the absence of a number of significant tasks, as well as the grounds for conducting intelligence-gathering activities by operational units of the penal system, the lack of legal regulation of the content of intelligence-gathering activities and their procedure. To prove the existence of these shortcomings, we analyze the most common intelligence-gathering measures such as questioning and inquiries. Having studied intelligence-gathering laws of several CIS countries we found some norms regulating intelligence-gathering activities in the penitentiary system, the use of which, in our opinion, is possible in Russian context. Based on this, we make proposals to improve legal regulation of intelligence-gathering activities, in particular, by disclosing the concept of each intelligence-gathering activity in the norms of intelligence-gathering law. Conclusions: the article develops and substantiates proposals for improving Russia’s intelligence-gathering law and concludes that it is necessary to transform fundamentally the legislative regulation of intelligence-gathering activities in Russia by adopting the appropriate code. Key words: intelligence-gathering activities; intelligence-gathering measures; shortcomings; problems; intelligence-gathering law; theory of intelligence-gathering activities; intelligence-gathering code.

Russian Law Enforcement Intelligence-Gathering Legislation: Problems and Ways to Address Them, Taking into Account the Experience of Some CIS Countries

Introduction: law enforcement practice and scientific research in the field of the theory of intelligence-gathering activities prove that current Russian intelligencegathering legislation contains quite a few legal gaps and contradictions. The article provides a scientific analysis of a number of problematic issues concerning legal regulation of intelligence-gathering activities conducted in the Russian Federation, with an emphasis on the functioning of operational units of the penal system of the Russian Federation. Aim:to work out proposals to improve national intelligence-gathering legislation by reviewingintelligence-gathering legislation of CIS countries, analyzing the works of scientists on the theory of intelligence-gathering activities and regulatory framework for the work of operational units. Methods: comparative legal method, theoretical methods of formal and dialectical logic, specific scientific methods: legal-dogmatic method, interpretation of legal norms. Results: the article considers the inconsistency between the purpose of intelligence-gathering activities enacted in law and both the law enforcement practice and its legally defined tasks, the absence of a number of significant tasks, as well as the grounds for conducting intelligence-gathering activities by operational units of the penal system, the lack of legal regulation of the content of intelligence-gathering activities and their procedure. To prove the existence of these shortcomings, we analyze the most common intelligence-gathering measures such as questioning and inquiries. Having studied intelligence-gathering laws of several CIS countries we found some norms regulating intelligence-gathering activities in the penitentiary system, the use of which, in our opinion, is possible in Russian context. Based on this, we make proposals to improve legal regulation of intelligence-gathering activities, in particular, by disclosing the concept of each intelligence-gathering activity in the norms of intelligence-gathering law. Conclusions: the article develops and substantiates proposals for improving Russia’sintelligence-gathering law and concludes that it is necessary to transform fundamentally the legislative regulation of intelligence-gathering activities in Russia by adopting the appropriate code. Keywords: intelligence-gathering activities; intelligence-gathering measures; shortcomings; problems; intelligence-gathering law; theory of intelligence-gathering activities; intelligence-gathering code.