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Read the text to answer the question.
A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.
The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.
Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.
Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts.
U.S. Department of Education, Office of Educational
Technology. (2023). Artificial Intelligence and the Future of
Teaching and Learning: Insights and Recommendations.
Washington, DC: U.S.
Read the text to answer the question.
A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.
The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.
Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.
Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts.
U.S. Department of Education, Office of Educational
Technology. (2023). Artificial Intelligence and the Future of
Teaching and Learning: Insights and Recommendations.
Washington, DC: U.S.
Read the text to answer the question.
A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.
The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.
Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.
Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts.
U.S. Department of Education, Office of Educational
Technology. (2023). Artificial Intelligence and the Future of
Teaching and Learning: Insights and Recommendations.
Washington, DC: U.S.
Read the text to answer the question.
A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.
The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.
Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.
Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts.
U.S. Department of Education, Office of Educational
Technology. (2023). Artificial Intelligence and the Future of
Teaching and Learning: Insights and Recommendations.
Washington, DC: U.S.
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Sendo assim, marque única alternativa correta que vai ao encontro daquilo que a professora Ana Clara pretende avaliar:
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I. Foco em Competências e Habilidades, a BNCC orienta os currículos não por conteúdos específicos, mas pelo desenvolvimento de 5 (cinco) competências gerais e competências específicas por área do conhecimento.
II. Formação Humana Integral, a Base se orienta por princípios éticos, políticos e estéticos, visando a formação integral dos estudantes, preparando-os para a construção de uma sociedade justa, democrática e inclusiva.
III. Estruturado por Áreas do Conhecimento, o Ensino Fundamental é organizado em 2 (duas) áreas do conhecimento: Linguagens e Ciências da Natureza, que englobam os componentes curriculares (disciplinas).
IV. Aprendizagem é progressiva, é definida de forma planejada conforme BNCC ao longo dos 9 anos de estudo denomina de Ensino Fundamental, ou seja, os anos iniciais (1º ao 5º ano) e anos finais (6º ao 9º ano), garantindo assim, a continuidade do percurso educativo deste Ensino Fundamental.
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Sobre a avaliação do ensino e da aprendizagem marque a única alternativa correta:
I. A literatura infantil é essencial para o desenvolvimento das crianças, oferecendo não apenas entretenimento como também lições sobre valores e comportamentos.
II. Seus principais objetivos incluem o entretenimento, educação, desenvolvimento emocional, estímulo à imaginação e construção do senso crítico.
III. Os gêneros da literatura infantil abrangem fábulas, contos de fadas, contos de mistério, lendas, poesia, fantasia, histórias de aventura, histórias de animais e biografias adaptadas.
IV. Lobato é o pai da literatura infantil brasileira, enquanto autoras como Ruth Rocha, Ana Maria Machado e Lygia Bojunga contribuíram com obras que marcaram o gênero no Brasil.
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I. Exercício da cidadania, alfabetização capacita as pessoas a entenderem seus direitos e deveres, a questionarem desigualdades e a participarem de debates sociais e políticos, o que é essencial para a construção de uma sociedade mais justa.
II. Inclusão social e combate à desigualdade é uma ferramenta crucial para reduzir a exclusão social, garantindo que indivíduos de grupos vulneráveis tenham acesso a informações, serviços públicos e oportunidades de trabalho.
III. Desenvolvimento pessoal e acesso ao conhecimento, ao aprender a ler e escrever, as pessoas adquirem habilidades que lhes permitem acessar um universo mais amplo de informações e conhecimentos, o que impulsiona o desenvolvimento individual e profissional.
IV. Fortalecimento da individualidade, o aluno ao se envolver com a família e com comunidades fora do contexto escolar a alfabetização ajuda a buscar conhecimentos tecnológicos se isolando da comunidade de um modo geral.
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