Aprendizagem significativa e supervisão: estudo exploratório de caracterização de um processo de mudança de práticas de um professor

Neste estudo aborda-se, de forma descritiva, o processo de mudança de práticas de um professor do ensino secundário, decorrente de uma relação de supervisão gerida pelo investigador. Essa mudança foi no sentido de um processo de ensino informado pela perspectiva construtivista, mais concretamente pela concepção de aprendizagem significativa tal como perspectivada por Ausubel. A elaboração do estudo envolveu várias fases que incluem a formação, a recolha e a análise de dados, a supervisão. A recolha de dados foi feita, por um lado, através de quatro inquéritos, dois para os alunos e dois para o professor, aplicados em dois momentos distintos: antes da mudança do processo de ensino/aprendizagem e após essa mudança e, por outro lado, através da gravação dos relatos do professor durante o processo de mudança. Antes do bloco de aulas relativo ao processo de mudança, professor e supervisor (investigador) abordaram conjuntamente a perspectiva construtivista e a aprendizagem significativa, e planificaram, também juntos, o bloco de aulas. O processo de supervisão foi enquadrado pelo modelo reflexivo. Os dados (dos inquéritos e das gravações) foram sujeitos a análise de conteúdo, tal como perspectivada por Bardin (1979). Verifica-se a existência de mudanças efectivas relacionadas com a melhoria da preparação das aulas, que tornou o professor mais reflexivo, e com a melhoria da relação pedagógica, que proporcionou aos alunos um papel mais activo no processo de ensino e aprendizagem. Conclui-se sobre a pertinência de repensar a formação contínua dos professores, de forma a incluir supervisores nas escolas que acompanhem os professores no sentido de melhorarem as suas práticas.

Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry

BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.