Raciocínio informal e a discussão de questões sociocientíficas: o exemplo das células-tronco humanas

Pós-graduação em Educação para a Ciência - FC

Reasoning in science through representation

In this chapter we argue that our analysis of student reasoning through constructing representations points to a range of informal and formal reasoning processes. This suggests the need for researchers and teachers to shift from an exclusive focus on formal syllogistic reasoning as the main or only reasoning resource for science learning. First we review the literature to identify how informal reasoning is described, and relates to reasoning through representation, then examine one case of reasoning during a representational challenge, to argue that reasoning should be thought of as deliberative thinking that involves choices, leading to a justifiable claim. Two case studies from RILS units are then used to identify how reasoning through representation can occur at a number of points during a representational challenge, and finally to develop an indicative taxonomy of the different purposes of reasoning as part of the processes of science.

Raciocínio moral na tomada de decisões em relação a questões sociocientíficas: o exemplo do melhoramento genético humano

Nos últimos anos, os avanços nas Ciências Biológicas têm levado a sociedade a discutir diversas questões no campo da moral e da ética. Questões como engenharia genética, clonagem e pesquisas com células-tronco são questões chamadas de sociocientíficas por estarem na interface entre a ciência e a sociedade. Nesse trabalho buscamos entender como estudantes de Ensino Médio percebem e interpretam questões relacionadas à manipulação genética em seres humanos. Houve divisão de opiniões em relação à eugenia negativa, que se destina a remover características desfavoráveis das pessoas; mas a eugenia positiva, que busca melhoramento de características estéticas, foi rejeitada por todos os estudantes. As variações nas opiniões em relação ao assunto tratado podem ser, em grande medida, devidas às representações sociais dos estudantes.

O significado atribuído por licenciandos ao currículo de Biologia numa perspectiva CTSA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Young children's statistical reasoning : a tale of two contexts

This thesis explored the knowledge and reasoning of young children in solving novel statistical problems, and the influence of problem context and design on their solutions. It found that young children's statistical competencies are underestimated, and that problem design and context facilitated children's application of a wide range of knowledge and reasoning skills, none of which had been taught. A qualitative design-based research method, informed by the Models and Modeling perspective (Lesh & Doerr, 2003) underpinned the study. Data modelling activities incorporating picture story books were used to contextualise the problems. Children applied real-world understanding to problem solving, including attribute identification, categorisation and classification skills. Intuitive and metarepresentational knowledge together with inductive and probabilistic reasoning was used to make sense of data, and beginning awareness of statistical variation and informal inference was visible.

Automated Acquisition of Evolving Informal Descriptions

The Listener is an automated system that unintrusively performs knowledge acquisition from informal input. The Listener develops a coherent internal representation of a description from an initial set of disorganized, imprecise, incomplete, ambiguous, and possibly inconsistent statements. The Listener can produce a summary document from its internal representation to facilitate communication, review, and validation. A special purpose Listener, called the Requirements Apprentice (RA), has been implemented in the software requirements acquisition domain. Unlike most other requirements analysis tools, which start from a formal description language, the focus of the RA is on the transition between informal and formal specifications.

Deciding between theories of how reasoning develops is hard

Although Sloutsky agrees with our interpretation of our data, he argues that the totality of the evidence supports his claim that children make inductive generalisations on the basis of similarity. Here we take issue with his characterisation of the alternative hypotheses in his informal analysis of the data, and suggest that a thorough Bayesian analysis, although practically very difficult, is likely to result in a more finely balanced outcome than he suggests. (c) 2008 Elsevier B.V. All rights reserved.

A survey of formalisms for representing and reasoning with scientific knowledge

With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.