scholarly journals The bayesian thinking, a pervasive computational thinking

2021 ◽  
Author(s):  
Miguel Zapata-Ros
Keyword(s):  
Graphical Models ◽  
Early Stage ◽  
Process Analysis ◽  
Computational Thinking ◽  
Digital Culture ◽  
Bayesian Probability ◽  
Substantial Part ◽  
Research Activity ◽  
K 12 ◽  
Almost All

In its simplest sense, computational thinking is considered as a series of specific skills that help programmers to do their homework, but that are also useful to people in their professional life and in their personal life as a way to organize the resolution on their problems, and of representing the reality that surrounds them.In a more elaborate scheme, this complex of skills constitutes a new literacy --- or the most substantial part of it --- and an inculturation to deal with a new culture, the digital culture in the knowledge society.We have seen how Bayesian probability is used in epidemiology models to determine models for the evolution of data on contagion and deaths in COVID and in natural language processing.We could also see it in a multitude of cases in the most varied scientific and process analysis fields. In this way, with the automation of Bayesian methods and the use of probabilistic graphical models, it is possible to identify patterns and anomalies in voluminous data sets in fields as diverse as linguistic corpus, astronomical maps, add functionalities to the practice of the magnetic resonance imaging, or to card, online or smartphone purchasing habits. In this new way of proceeding, big data analysis and Bayesian theory are associated.If we consider that Bayesian thinking, this way of proceeding, as one more and more relevant element of computational thinking, then to what has been said on previous occasions we must now add the idea of generalized computational thinking, which goes beyond education. It is no longer about aspects purely associated with ordinary professional or vital practice to deal with life and the world of work, as has been what we have called computational thinking until now, but as a preparation for basic research and research methodology in almost all disciplines. Because, thus defined, computational thinking is influencing research in almost all areas, both in the sciences and in the humanities. An instruction focused on this component of computational thinking, Bayesian thinking, of including it at an early stage, in Secondary (K-12), including the inverse probability formula, would allow, based on Merrill’s First principles of learning, and in particular in the activation principle, activate these learning as very valuable and very complex components in a later stage of professional or research activity, or in the training passed, undergraduate and postgraduate degrees, of these professions or that train for these activities and professions.

scholarly journals El pensamiento bayesiano, un pensamiento computacional omnipresente

2021 ◽  
Vol 21 (68) ◽  
Author(s):  
Miguel Zapata Ros ◽  
Yamil Buenaño Palacios
Keyword(s):  
Language Processing ◽  
Graphical Models ◽  
Process Analysis ◽  
Knowledge Society ◽  
Computational Thinking ◽  
Digital Culture ◽  
Bayesian Probability ◽  
Substantial Part ◽  
K 12 ◽  
Almost All

En su acepción más sencilla se considera el pensamiento computacional como una serie de habilidades específicas que sirven a los programadores para hacer su tarea, pero que también son útiles a la gente en su vida profesional y en su vida personal como una forma de organizar la resolución de sus problemas, y de representar la realidad que hay en torno a ellos. En un esquema más elaborado este complejo de habilidades constituye una nueva alfabetización ---o la parte más sustancial de ella--- y una inculturación para manejarse en una nueva cultura, la cultura digital en la sociedad del conocimiento. Hemos visto cómo se usa la probabilidad bayesiana, en modelos de epidemiología, para determinar modelos de evolución de datos sobre contagio y fallecimientos en el COVID y en el procesamiento del lenguaje natural. Igualmente podríamos verlo en multitud de casos en los más variados campos científicos y de análisis de procesos. De esta forma, con la automatización de los métodos bayesianos y el uso de modelos gráficos probabilísticos es posible identificar patrones y anomalías en voluminosos conjuntos de datos en campos tan diversos como son los corpus lingüísticos, los mapas astronómicos, añadir funcionalidades a la práctica de la resonancia magnética, o a los hábitos de compra con tarjeta, online o smartphones. En esta nueva forma de proceder, se asocian el análisis de grandes datos y la teoría bayesiana. Si consideramos que el pensamiento bayesiano, esta forma de proceder, como un elemento más y relevante del pensamiento computacional, entonces a lo dicho en anteriores ocasiones hay que añadir ahora la idea de pensamiento computacional generalizado , que va más allá de la educación Ya no se trata de aspectos puramente asociados a la práctica profesional o vital ordinaria para manejarse por la vida y el mundo del trabajo, como ha sido lo que hemos llamado pensamiento computacional hasta ahora, sino como una preparación para la investigación básica y para metodología investigadora en casi todas las disciplinas. Porque, así definido, el pensamiento computacional está influyendo en la investigación en casi todas las áreas, tanto en las ciencias como en las humanidades. Una instrucción centrada en esta componente de pensamiento computacional, el pensamiento bayesiano, o que lo incluyese en una fase temprana, en Secundaria (K-12), incluyendo la fórmula de la probabilidad inversa, permitiría, basándonos en los First principles of learning de Merrill, y en particular en el principio de activación, activar estos aprendizajes como componentes muy valiosos y muy complejos en una etapa posterior de la actividad profesional o investigadora, o en la fase de formación, grados y postgrados, de estas profesiones o que capacitan para estas actividades y profesiones. In its simplest sense, computational thinking is considered as a series of specific skills that programmers use to do their homework. They are also useful to people in their professional and personal lives, as a way of organizing the resolution of their problems, and of representing the reality that surrounds them. In a more elaborate scheme, this complex of skills constitutes a new literacy --- or the most substantial part of it --- and an inculturation to deal with a new culture: digital culture in the knowledge society. We have seen how Bayesian Probability is used in epidemiology models to determine models of data evolution on contagion and deaths in COVID. We have also seen it in natural language processing. We could also see it in many cases in the most varied scientific and process analysis fields. In this way, with the automation of Bayesian methods and the use of probabilistic graphical models, it is possible to identify patterns and anomalies in voluminous data sets in fields. Fields as diverse as linguistic corpus, astronomical maps, adding functionalities to the practice of magnetic resonance imaging, or to the habits of buying with cards, online or smartphones. In this new way of proceeding, big data analysis and Bayesian theory are associated.. If we consider that Bayesian thinking (this way of proceeding) as one more element of computational thinking, then, to what has been said on previous occasions, we must now add the idea of ​​generalized computational thinking, which goes beyond education It is no longer about aspects purely associated with professional or vital practice to deal with life and the world of work, but as a preparation for basic research and for a research methodology in almost all disciplines. Thus defined, computational thinking is influencing research in almost all areas, both in the sciences and the humanities. An instruction focused on this component of computational thinking, or including it, at an early stage, in Secondary, would allow to activate these learnings as very valuable and very complex components at a later stage. In professional or research activity, in the training phase, undergraduate and postgraduate degrees, of these professions. Those that train for these activities and professions.

scholarly journals More confidently uncertain? Teaching learners to apply Bayesian methods to make sense of scientific phenomena

2020 ◽  
Author(s):  
Joshua Rosenberg
Keyword(s):  
Data Analysis ◽  
Learning Environments ◽  
Statistical Methods ◽  
Bayesian Methods ◽  
Science Learning ◽  
Early Stage ◽  
Computational Thinking ◽  
Modeling Data ◽  
Scientific Phenomena ◽  
K 12

While analyzing data is important learning in science domains, existing tools for those learning to work with data have key limitations, particularly concerning modeling data. This early-stage research is intended to begin a line of work on students’ data analysis that is not yet widely used in K-12 learning environments, Bayesian statistical methods, with implications for how learners use evidence in science learning environments and how computational thinking is related to working with data.

scholarly journals Hops (Humulus lupulus L.) as a Novel Multipurpose Crop for the Mediterranean Region of Europe: Challenges and Opportunities of Their Cultivation

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 484
Author(s):  
Francesco Rossini ◽  
Giuseppe Virga ◽  
Paolo Loreti ◽  
Nicolò Iacuzzi ◽  
Roberto Ruggeri ◽  
...  
Keyword(s):  
Humulus Lupulus ◽  
Specific Reference ◽  
Research Activity ◽  
Plant Parts ◽  
Craft Beer ◽  
Recent Success ◽  
Natural Medicine ◽  
Humulus Lupulus L ◽  
Challenges And Opportunities ◽  
Almost All

The common hop (Humulus lupulus L.) is a dioecious perennial climbing plant, mainly known for the use of its female inflorescences (cones or, simply, “hops”) in the brewing industry. However, the very first interest towards hops was due to its medicinal properties. Actually, the variety of compounds present in almost all plant parts were (and still are) used to treat or prevent several ailments and metabolic disorders, from insomnia to menopausal symptoms as well as obesity and even cancer. Although hops are predominantly grown for hopping beer, the increasing interest in natural medicine is widening new interesting perspectives for this crop. Moreover, the recent success of the craft beer sector all over the world, made the cultivated hop come out from its traditional growing areas. Particularly, in Europe this resulted in a movement towards southern countries such as Italy, which added itself to the already existing hop industry in Portugal and Spain. In these relatively new environments, a complete knowledge and expertise of hop growing practices is lacking. Overall, while many studies were conducted globally on phytochemistry, bioactivity, and the genetics of hops, results from public research activity on basic hop agronomy are very few and discontinuous as well. The objective of this article is to provide an overview of possible uses, phenology, and agronomic aspects of hops, with specific reference to the difficulties and opportunities this crop is experiencing in the new growing areas, under both conventional and organic farming. The present review aims to fill a void still existing for this topic in the literature and to give directions for farmers that want to face the cultivation of such a challenging crop.

Computational thinking in K-12 education. An insight through meta-analysis

2021 ◽  
pp. 1-26
Author(s):  
José Miguel Merino-Armero ◽  
José Antonio González-Calero ◽  
Ramón Cózar-Gutiérrez
Keyword(s):  
Meta Analysis ◽  
Computational Thinking ◽  
K 12

Preparing Special Education Preservice Teachers to Teach Computational Thinking and Computer Science in Mathematics

2021 ◽  
pp. 088840642199237
Author(s):  
Emily C. Bouck ◽  
Phil Sands ◽  
Holly Long ◽  
Aman Yadav
Keyword(s):  
Special Education ◽  
Preservice Teachers ◽  
Computer Science ◽  
Students With Disabilities ◽  
Special Education Teachers ◽  
Computational Thinking ◽  
Lesson Plans ◽  
Methods Course ◽  
Mathematics Methods ◽  
K 12

Increasingly in K–12 schools, students are gaining access to computational thinking (CT) and computer science (CS). This access, however, is not always extended to students with disabilities. One way to increase CT and CS (CT/CS) exposure for students with disabilities is through preparing special education teachers to do so. In this study, researchers explore exposing special education preservice teachers to the ideas of CT/CS in the context of a mathematics methods course for students with disabilities or those at risk of disability. Through analyzing lesson plans and reflections from 31 preservice special education teachers, the researchers learned that overall emerging promise exists with regard to the limited exposure of preservice special education teachers to CT/CS in mathematics. Specifically, preservice teachers demonstrated the ability to include CT/CS in math lesson plans and showed understanding of how CT/CS might enhance instruction with students with disabilities via reflections on these lessons. The researchers, however, also found a need for increased experiences and opportunities for preservice special education teachers with CT/CS to more positively impact access for students with disabilities.

Characteristics and attitudes of family planners in Khartoum, Sudan

1982 ◽  
Vol 14 (1) ◽  
pp. 7-16 ◽  
Author(s):  
M. A. Khalifa
Keyword(s):  
Family Planning ◽  
Birth Control ◽  
Early Stage ◽  
Significant Proportion ◽  
Large Family ◽  
Capital City ◽  
Age Group ◽  
African Countries ◽  
The Mean ◽  
Almost All

SummaryIn a survey of 1475 urban Moslem wives in the age group 15–49 living in the capital city of the Sudan, knowledge of birth control was reported by almost all respondents while a significant proportion had used contraception at least once. The mean age of the users was 32·8 years, their duration of marriage was 15·1 years and their mean number of surviving children was 4·6. Those who had never used contraception had a higher mean age, a longer duration of marriage and more surviving children. Most of the users had an urban residential background and belonged to the high socioeconomic class. They held favourable attitudes to family planning. Although they thought that having a large family (more than five children) was not desirable, their mean preferred family size was no different from that of the never users.The results indicate that contraception is used for the purpose of spacing births rather than limiting their ultimate number. At this early stage of contraceptive adoption in Sudan, the characteristics of the pioneer acceptors are similar to those observed in other African countries.

scholarly journals Computational Thinking, Between Papert and Wing

2021 ◽  
Author(s):  
Michael Lodi ◽  
Simone Martini
Keyword(s):  
Science Education ◽  
Computer Science ◽  
Computer Science Education ◽  
Computational Thinking ◽  
School Curriculum ◽  
Common Theme ◽  
Technical Content ◽  
Technical Competencies ◽  
K 12 ◽  
Affective Involvement

AbstractThe pervasiveness of Computer Science (CS) in today’s digital society and the extensive use of computational methods in other sciences call for its introduction in the school curriculum. Hence, Computer Science Education is becoming more and more relevant. In CS K-12 education, computational thinking (CT) is one of the abused buzzwords: different stakeholders (media, educators, politicians) give it different meanings, some more oriented to CS, others more linked to its interdisciplinary value. The expression was introduced by two leading researchers, Jeannette Wing (in 2006) and Seymour Papert (much early, in 1980), each of them stressing different aspects of a common theme. This paper will use a historical approach to review, discuss, and put in context these first two educational and epistemological approaches to CT. We will relate them to today’s context and evaluate what aspects are still relevant for CS K-12 education. Of the two, particular interest is devoted to “Papert’s CT,” which is the lesser-known and the lesser-studied. We will conclude that “Wing’s CT” and “Papert’s CT,” when correctly understood, are both relevant to today’s computer science education. From Wing, we should retain computer science’s centrality, CT being the (scientific and cultural) substratum of the technical competencies. Under this interpretation, CT is a lens and a set of categories for understanding the algorithmic fabric of today’s world. From Papert, we should retain the constructionist idea that only a social and affective involvement of students into the technical content will make programming an interdisciplinary tool for learning (also) other disciplines. We will also discuss the often quoted (and often unverified) claim that CT automatically “transfers” to other broad 21st century skills. Our analysis will be relevant for educators and scholars to recognize and avoid misconceptions and build on the two core roots of CT.

scholarly journals Trends and Decomposition of Wheat Production in Western Maharashtra

2020 ◽  
pp. 69-78
Author(s):  
P. P. Baviskar ◽  
U. T. Dangore ◽  
A. D. Dhunde ◽  
U. P. Gaware ◽  
A. G. Kadu
Keyword(s):  
Decomposition Analysis ◽  
Parametric Models ◽  
Production Performance ◽  
Wheat Crop ◽  
Secondary Source ◽  
Research Activity ◽  
Wheat Production ◽  
Area Effect ◽  
Relative Contribution ◽  
Almost All

The study was aimed to investigate the production performance of wheat in western Maharashtra. The data of 20 years regarding area, production and productivity of wheat was made available through the secondary source for all the districts of the western Maharashtra region. The study period of 1996-97 to 2015-16 was split into two sub periods i.e. period-I (1996-97 to 2005-2006), period-II (2006-07 to 2015-16) and overall period. The growth rates were calculated using the exponential function. The instability in area, production, and productivity was measured with a coefficient of variation (CV) and Cuddy Della Valle’s Instability index. The relative contribution of area and yield to change in output was estimated by Minhas decomposition model. The district-wise analysis was carried out which resulted that, during the period-I and period-II, almost all districts in the western Maharashtra region registered negative growth including the region as a whole. The area and productivity showed stability in wheat crop in almost all the districts of western Maharashtra region. In the western Maharashtra region, among all the parametric models fitted to the area, production and productivity of wheat crop, the maximum R2 was observed in the case of cubic model in all the districts of Western Maharashtra region with the region as a whole. The region as a whole recorded 59 per cent which marked as the highest R2 in productivity as compared to area and production. The decomposition analysis for western Maharashtra region depicted the largest area effect on wheat production. It was also observed that for both periods the area effect was more pronounced than the yield effect and interaction effect. Hence, there is need for policy maker to formulate development-oriented policies and the researchers to design an investigative research activity for promoting a sustainable wheat production system in the region for expansion of area under wheat cultivation.

Sign in / Sign up

Export Citation Format

Share Document