Includes abstract. / Includes bibliographical references. / The unique knowledge that teachers possess Shulman called pedagogical content knowledge or PCK. In the following 25 years many scholars have conceptualised PCK, and only recently, with an international PCK Summit, have attempts been made to consolidate this field. South Africa’s primary and secondary public education system is continuously under scrutiny, as it continues to perform poorly in international benchmarking assessments. The need to understand what is happening in our classrooms, especially in science and mathematics, is now more important than ever. In response to this need, this study investigated the classroom practice of a dedicated and experienced science teacher over a period of three years, as she taught the organic chemistry section of the Grade 12 Physical Sciences syllabus. PCK was used as a lens to focus on how teacher knowledge manifests in practice.

Includes abstract. / Includes bibliographical references (leaves 82-86). / These studies aimed to investigate the sustainability conceptions held by engineering students and to assess their level of knowledge on sustainability concepts. The findings revealed that the level of knowledge is poor and engineering students had varying ideas on what sustainability is.

Bibliography: leaves 123-127.

Includes abstract. / Includes bibliographical references. / The case studies that make up this thesis cover the three largest academic development programmes at the University of Cape Town. A variety of statistical methods are used to estimate the effect of educational interventions in selected first- and second-year academic development courses on the academic performance of academic development students in these courses and through to graduation, relative to mainstream students. In general, research in this area in South Africa and internationally has been characterised by small sample sizes and a lack of statistical rigour. Few studies control for the range of independent variables that can affect students’ academic performance, in addition to the academic development programme or course, and the great majority ignore the sampleselection problem that arises in the selection of students for academic development and mainstream programmes. The theoretical rationale underpinning this thesis is informed by the postpositivist and evidence-based approaches to empirical investigation. Demographic, academic and other data for some 9000 students for the years 1999?2005 was obtained from the university’s data base and academic departments. Statistical techniques including multivariate analysis and propensity score matching are used in an attempt to finesse the problems associated with the use of non-experimental data as students are selected into different courses and programmes.

An integrated thermofluid modelling methodology for pulverised fuel fired utility-scale boilers that is computationally inexpensive, fast, and sufficiently accurate would be valuable in an industrial setting. Such a model would enable boiler operators to investigate a range of off-design operating conditions, which includes flexible operation. The aims of this study was: to develop a reduced order computational fluid dynamics (CFD) model of the furnace and radiative heat exchangers that captures all the important particulate effects while using a Eulerian-Eulerian (EE) approach; using the reduced order CFD model to generate a database of results that covers a wide range of operating conditions; to develop a data-driven surrogate model using machine learning techniques; to integrate the surrogate model with a 1-D process model of the complete boiler; and finally to demonstrate the use of the integrated model to investigate flexible operation and off-design operating conditions. The validity of the CFD modelling approach was demonstrated via application to a 2.165 [MWth] lab-scale swirl pulverised fuel burner, as well as to a 620 [MWe] utility-scale subcritical two-pass boiler, both operating at various loads. The results were compared to measured data and a detailed CFD model using the conventional Eulerian-Lagrangian (EL) approach. A computational speed enhancement of 30% was achieved. The data-driven surrogate model uses a mixture density network (MDN) to predict the heat transfer in the furnace and radiative heat exchangers, together with the uncertainty in the predicted values. The integrated model was validated against applicable measured data and then applied to a utility-scale case study boiler to investigate the optimal burner firing positions for low-load operation, as well as to investigate the effects of fuel quality on the overall boiler performance. It was shown that the integrated data-driven surrogate model and 1-D process model can predict the overall thermofluid response of the boiler and the uncertainties associated with it with good accuracy, whilst maintaining a low computational effort when compared to a conventional CFD model coupled to 1-D process model.