Ferramentas Visuais para o Ensino de Machine Learning na Educação Básica

Ensinar Machine Learning (ML) em escolas ajuda a preparar estudantes para lidar com questões sociais, econômicas e éticas do século 21. Isso requer ferramentas apropriadas a cada idade que permitem que os estudantes criem uma concepção abrangente de ML e sua aplicação. Desse modo, apresentamos um mapeamento de ferramentas visuais emergentes que ajudam a ensinar conceitos de ML na Educação Básica e caracterizamos as ferramentas em relação ao suporte para o desenvolvimento e deployment de modelos de ML em contextos educacionais. Os resultados podem ajudar designers instrucionais e instrutores a selecionar ferramentas apropriadas a fim de contribuir para a democratização de competências em ML

A global assessment of actors and their roles in climate change adaptation

An assessment of the global progress in climate change adaptation is urgently needed. Despite a rising awareness that adaptation should involve diverse societal actors and a shared sense of responsibility, little is known about the types of actors, such as state and non-state, and their roles in different types of adaptation responses as well as in different regions. Based on a large n-structured analysis of case studies, we show that, although individuals or households are the most prominent actors implementing adaptation, they are the least involved in institutional responses, particularly in the global south. Governments are most often involved in planning and civil society in coordinating responses. Adaptation of individuals or households is documented especially in rural areas, and governments in urban areas. Overall, understanding of institutional, multi-actor and transformational adaptation is still limited. These findings contribute to debates around ‘social contracts’ for adaptation, that is, an agreement on the distribution of roles and responsibilities, and inform future adaptation governance

Determining factors of academic success of first year BSc Dietetics students

It is broadly acknowledged that a host of factors influence the academic success of students, but there currently is a paucity of literature about this issue in the field of health sciences, and none in specifically Dietetics, in South Africa, and very little globally. This constitutes a significant knowledge gap in the field of higher education, as determining which factors are most important in facilitating the success of Dietetics students in a South African context, will make a significant contribution to understanding and assisting such students. The aim of this article is to report on a study that identified the key factors of success of first year BSc Dietetics students at one South African university. The aim of the study was to inform the design of interventions that would improve the performance and throughput of these students. Quantitative analysis of success factors contained in the existing data of the university, qualitative focus group discussions on students’ perceptions and a questionnaire with a qualitative and quantitative section on success factors were used. In recruiting students for Dietetics, strict adherence to admission criteria is necessary and support should be given to students on an individual basis to ensure the highest quality of student intake and eventual output. This study showed that Dietetics students realised their own responsibility to ensure their academic success, but participants also provided important insights on what can be done by the staff, the department and university in order to improve the academic success. This information is useful to others in the higher education community and also in other programmes in health sciences. More research on the perception of staff regarding academic success factors is needed and various intervention strategies to improve success can then be investigated

A Representation Formalism for Supporting Reuse of Software Engineering Knowledge

To transfer innovative software technologies into practice and to continuously improve the software quality and productivity, software-related knowledge should be reused. Therefore, software organizations require support for collecting systematically experiences from their projects, packaging those experiences to build up software-related knowledge, and in validating and reusing knowledge in future software development projects. In this paper, the representation formalism REFSENO is presented for specifying domain-specific software engineering knowledge. Such knowledge is conceptualized explicitly in the form of software engineering ontologies as a means for the development and communication of structure models for an organization-wide experience base. Through clearly defined primitives and operations on the knowledge representation, REFSENO provides a means to operationalize such a repository based on the ontology definition. REFSENO supports the development of experience bases and pr ovides the means for checking the modeled domain knowledge for completeness and consistency. The representation formalism has been validated through the GQM planning ontology (GQM is an innovative technology for software engineering measurement) from which excerpts are presented in this paper to exemplify the primitives of REFSENO

Revelation de l'information, liquidite et couts de transaction implicites

SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : DO 2335 (6) / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc