Balancing curriculum processes and content in a project centred curriculum - In pursuit of graduate attributes

Chemical engineering education is challenged around the world by demands and rapid changes encompassing a wide range of technical and social drivers. Graduates must be prepared for practice in increasingly diverse workplace environments in which generic or transferable attributes such as communication and teamwork together with technical excellence are mandated by prospective employers and society at large. If academe is to successfully deliver on these graduate attributes, effective curriculum design needs to include appropriate educational processes as well as course content. Conventional teacher centred approaches, stand-alone courses and retro-fitted remedial modules have not delivered the desired outcomes. Development of the broader spectrum of attributes is more likely when students are engaged with realistic and relevant experiences that demand the integration and practice of these attributes in contexts that the students find meaningful. This paper describes and evaluates The University of Queensland's Project Centred Curriculum in Chemical Engineering (PCC), a programme-wide approach to meeting these requirements. PCC strategically integrates project-based learning with more traditional instruction. Data collected shows improved levels of student attainment of generic skills with institutional and nationally benchmarked indicators showing significant increases in student perceptions of teaching quality, and overall satisfaction with the undergraduate experience. Endorsements from Australian academic, professional and industry bodies also support the approach as more effectively aligning engineering education with professional practice requirements.

Project-based assessment for graduate coursework in physics

Project-based assessment, in the form of take-home exams, was trialed in an honours/masters level electromagnetic theory course. This assessment formed an integral part of the learning experience of the students, and students felt that this was effective method of learning.

Design options for sample-based mortality surveillance

Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.

Improving learning in undergraduate control engineering courses using context-based learning models

Control Engineering is an essential part of university electrical engineering education. Normally, a control course requires considerable mathematical as well as engineering knowledge and is consequently regarded as a difficult course by many undergraduate students. From the academic point of view, how to help the students to improve their learning of the control engineering knowledge is therefore an important task which requires careful planning and innovative teaching methods. Traditionally, the didactic teaching approach has been used to teach the students the concepts needed to solve control problems. This approach is commonly adopted in many mathematics intensive courses; however it generally lacks reflection from the students to improve their learning. This paper addresses the practice of action learning and context-based learning models in teaching university control courses. This context-based approach has been practised in teaching several control engineering courses in a university with promising results, particularly in view of student learning performances.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

Using front-end and formative evaluation to design and test persuasive bird feeding warning signs

Wildlife feeding is a wide-spread and controversial practice that can pose serious threats to the safety of both wildlife and visitors. The design and effectiveness of warning signs in recreational areas varies considerably and is rarely the product of theoretical models or scientific research. This study uses front-end and formative evaluation to design and test the perceived effectiveness of warning signs relating to bird feeding. Stage One examined visitors' beliefs, attitudes and bird feeding behaviour and found significant differences between feeders and non-feeders. Stage Two involved designing and evaluating three signs that built on the beliefs, knowledge and mis/conceptions identified in Stage One. Respondents thought the sign that focused on the birds' health and safety would be the most persuasive, however, elements of the other two signs were also positively evaluated. The article concludes with recommendations for the wording of future bird feeding warning signs. (c) 2004 Elsevier Ltd. All rights reserved.

Problem-based learning: a case study in providing e-health education using the Internet

The current trend among many universities is to increase the number of courses available online. However, there are fundamental problems in transferring traditional education courses to virtual formats. Delivering current curricula in an online format does not assist in overcoming the negative effects on student motivation which are inherent in providing information passively. Using problem-based learning (PBL) online is a method by which computers can become a tool to encourage active learning among students. The delivery of curricula via goal-based scenarios allows students to learn at different rates and can successfully shift online learning from memorization to discovery. This paper reports on a Web-based e-health course that has been delivered via PBL for the past 12 months. Thirty distance-learning students undertook postgraduate courses in e-health delivered via the Internet (asynchronous communication). Data collected via online student surveys indicated that the PBL format was both flexible and interesting. PBL has the potential to increase the quality of the educational experience of students in online environments.