RESUMO
Problem-based learning (PBL) is now an accepted component of many medical school programmes worldwide. Our university also follows the PBL `SPICES' model for MB ChB III. The assessment modalities used are the modified essay questions (MEQ); objective structured practical examination (OSPE); individualised process assessment (IPA) and tutorial continuous assessment (TUT). This study was done to compare the students' performances in individual assessment components with the final mark to determine the correlation between these parameters. Materials and methods. The study was retrospective; descriptive and analytical; based on the integrated marks of all the MB ChB III students at Walter Sisulu University (WSU) in 2007. Assessment marks were stratified according to blocks and different types of assessment (MEQ; TUT; OSPE; IPA). Regression analysis was used to compute and scrutinise these vis-a-vis their correspondence with the final marks for each block.Results. Three hundred and seventy-nine block assessment marks of 96 students from 4 blocks of MB ChB III were analysed and the correlation between the assessment components and final mark were compared. Regression analysis showed good correlation when analysing the assessment modality versus the final mark for the MEQs (r=0.93; 0.93; 0.94; 0.96); followed by OSPEs (r=0.71; 0.70; 0.76; 0.77) and IPAs (r=0.62; 0.51; 0.68; 0.77). However; correlation was not significant with the TUT. Conclusion. There was good correlation between the students' performance in the majority of assessment modalities and the final mark in the different blocks of the MB ChB III examination. There may be a need to make tutorial assessment methods more objective; partly by additional tutor training
Assuntos
Questões de Prova , África do Sul , UniversidadesRESUMO
The most suitable wavelength intervals were selected for the determination of 4 polycyclic aromatic hydrocarbons (PAHs; benzo[g,h,i]perylene, dibenzo[a,h]anthracene, pyrene, and triphenylene) in very complex mixtures of 11 PAHs: anthracene, benz[a]anthracene, benzo[a]pyrene, benzo[b]fluoranthene, benzo[g,h,i]perylene, benzo[k]fluoranthene, chrysene, dibenz[a,h]anthracene, phenanthrene, pyrene, and triphenylene. The multiple linear regression algorithm was applied to measurements made in several wavelength intervals previously selected on the basis of sensitivity and minimum number of interfering compounds. Of the different models obtained, those displaying minimum error propagation in the analytical result were selected. By applying the models proposed in this study, we precisely and accurately determined benzo[g,h,i]perylene, dibenz[a,h]anthracene, pyrene, and triphenylene in complex mixtures--a feat that could not be achieved by the use of constant-wavelength spectrofluorimetry in combination with second-derivative techniques.