Students' Intelligence Beliefs Across Subject Areas

2008 ◽  
Author(s):  
Brett D. Jones ◽  
C. N. Byrd ◽  
Danielle L. Lusk
2014 ◽  
Author(s):  
Carissa Romero ◽  
Allison Master ◽  
Dave Paunesku ◽  
James J. Gross ◽  
Carol S. Dweck
Keyword(s):  

Author(s):  
O. M. Korchazhkina

The article presents a methodological approach to studying iterative processes in the school course of geometry, by the example of constructing a Koch snowflake fractal curve and calculating a few characteristics of it. The interactive creative environment 1C:MathKit is chosen to visualize the method discussed. By performing repetitive constructions and algebraic calculations using ICT tools, students acquire a steady skill of work with geometric objects of various levels of complexity, comprehend the possibilities of mathematical interpretation of iterative processes in practice, and learn how to understand the dialectical unity between finite and infinite parameters of flat geometric figures. When students are getting familiar with such contradictory concepts and categories, that replenishes their experience of worldview comprehension of the subject areas they study through the concept of “big ideas”. The latter allows them to take a fresh look at the processes in the world around. The article is a matter of interest to schoolteachers of computer science and mathematics, as well as university scholars who teach the course “Concepts of modern natural sciences”.


Author(s):  
Boyd P. Holmes

Most information scientists appear to agree that the discipline absorbs, within its boundaries, all or part of certain other subject areas. Certain scholars, including Borko, Garrison, Rayward, James G. Williams and Martha E. Williams, have published, separately, what each of them considers those disciplines to be. My research, for which I present preliminary results in this paper, will. . .


Author(s):  
Aleksey Klokov ◽  
Evgenii Slobodyuk ◽  
Michael Charnine

The object of the research when writing the work was the body of text data collected together with the scientific advisor and the algorithms for processing the natural language of analysis. The stream of hypotheses has been tested against computer science scientific publications through a series of simulation experiments described in this dissertation. The subject of the research is algorithms and the results of the algorithms, aimed at predicting promising topics and terms that appear in the course of time in the scientific environment. The result of this work is a set of machine learning models, with the help of which experiments were carried out to identify promising terms and semantic relationships in the text corpus. The resulting models can be used for semantic processing and analysis of other subject areas.


2019 ◽  
Author(s):  
Jennifer Veilleux ◽  
Garrett Pollert ◽  
kayla skinner ◽  
Danielle Baker ◽  
Kaitlyn Chamberlain ◽  
...  

The beliefs people hold about emotion are clearly relevant for emotional processes, although the social psychological research on malleability or “lay” beliefs about emotion are rarely integrated with the clinical research on emotional schemas. In the current study, we examine a variety of beliefs about emotion (e.g., beliefs that emotions can be changed, beliefs that negative emotions are bad, beliefs that emotions should not be expressed, beliefs that emotions control behavior, beliefs that emotions last “forever”) along with other emotion belief measures and measures of psychopathology (general psychological distress, borderline personality), emotion dysregulation, interpersonal emotional attributions (emotional expressivity, interpersonal emotion regulation) and psychological flexibility (mindfulness, emotional intelligence). In a combined sample of undergraduates (n = 162) and adults from Mechanical Turk (n = 197), we found that beliefs about the longevity and uniqueness of emotions were unique predictors of psychopathology, even after controlling for age and gender. We also found that after controlling for symptoms of psychopathology, beliefs about longevity and that negative emotions are bad predicted greater emotion dysregulation and lower mindfulness. Beliefs that emotions should be kept to the self and a preference of logic over emotion predicted less emotional expressivity, interpersonal emotion regulation, and emotional intelligence. Beliefs that emotions control behavior also predicted lower mindfulness. Finally, when asked whether they think their beliefs change during strong emotions, people who said their beliefs change (about two-thirds of the sample) reported higher symptoms of psychopathology, higher emotion dysregulation, higher use of interpersonal regulation strategies and lower mindfulness.


Author(s):  
K. Maystrenko ◽  
A. Budilov ◽  
D. Afanasev

Goal. Identify trends and prospects for the development of radar in terms of the use of convolutional neural networks for target detection. Materials and methods. Analysis of relevant printed materials related to the subject areas of radar and convolutional neural networks. Results. The transition to convolutional neural networks in the field of radar is considered. A review of papers on the use of convolutional neural networks in pattern recognition problems, in particular, in the radar problem, is carried out. Hardware costs for the implementation of convolutional neural networks are analyzed. Conclusion. The conclusion is made about the need to create a methodology for selecting a network topology depending on the parameters of the radar task.


Keyword(s):  

Best of Five MCQs for the Gastroenterology SCE is the first revision guide designed specifically for this new high-stakes exam. It contains 210 best of five questions with explanatory answers, each accurately reflecting the layout of questions in the exam. The book is divided into seven subject areas, covering all the main themes of the exam, and providing a thorough assessment of the candidate's gastroenterological knowledge. Where relevant, questions are illustrated with full colour photographs including endoscopic, radiological and histology images. Uniquely, the explanatory answers include references to guidelines and other sources to enable candidates' further reading and study.


2001 ◽  
Vol 22 (2) ◽  
pp. 60
Author(s):  
Susan Walker ◽  
Peter Higgs
Keyword(s):  

Author(s):  
Alessandro Muscio ◽  
Sotaro Shibayama ◽  
Laura Ramaciotti

AbstractThis paper investigates how the characteristics of university laboratories influence the propensity of Ph.D. students to entrepreneurship, and thus, contribute to the transfer of academic knowledge to society. As determinants of Ph.D. entrepreneurship, we focus on the lab scientific and social capital as well as on the business experience that Ph.D. students acquire during their training period. The empirical exercise is based on questionnaire survey data of 5266 Ph.D. students in Italian universities in all subject areas. First, we find that 6.7% of the Ph.D. graduates engage in startup activities, and thus, Ph.D. training seems to contribute to knowledge transfer through entrepreneurship. Second, Ph.D. entrepreneurship is driven by business experience, in the forms of industry collaboration and industrially applicable research projects, during their training period. Third, the lab scientific capital is negatively associated with Ph.D. entrepreneurship, suggesting a conflict between scientific excellence and entrepreneurship, but this effect is mitigated if students acquire business experience. Fourth, the lab social capital increases the chance of startup when students have business experience. We further investigate the effects of lab environment by distinguishing between startups that are based on university research and startups that are not, finding different determinants.


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