Escala de perceção dos alunos sobre o feedback dos professores: construção e validação

O presente estudo procura testar as propriedades psicométricas de um questionário que avalia (a) perceção do aluno sobre o feedback do professor; a identificação escolar do aluno; as trajetórias escolares (factos e expectativas) e; a perceção do aluno sobre o seu envolvimento escolar. O questionário foi aplicado a 1089 alunos dos 6º, 7º, 9º e 10º anos de escolaridade (M=13.4, DP=1.7), sendo que 52% são do sexo feminino. A amostra é composta por alunos essencialmente de nacionalidade portuguesa (95.9%). A partir dos resultados da análise factorial e seguindo o racional teórico, chegou-se a uma estrutura composta por oito dimensões principais. O QFITE apresenta bons índices de consistência interna, com sete das oito principais dimensões a obterem valores entre .77 e .89. Assim, as análises psicométricas realizadas revelam valores satisfatórios, concluindo-se que o QFITE é um instrumento útil e adequado para avaliar a identificação escolar dos alunos, o envolvimento comportamental escolar, e as perceções dos alunos sobre o feedback do professor.

Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.

Elements of a methodology to assess the alignment of core-values in collaborative networks

Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.