939 resultados para Bayesian Learning
Resumo:
Marketing communications as a discipline has changed significantly in both theory and practice over the past decade. But has our teaching of IMC kept pace with the discipline changes? The purpose of this paper is to explore how far the evolving concepts of IMC are reaching university learners. By doing this, the paper offers an approach to assessing how well marketing curricula are fulfilling their purpose. The course outlines (syllabi) for all IMC courses in 30 universities in Australia and five universities in New Zealand were analyzed. The findings suggest that most of what is taught in the units is not IMC. It is not directed by the key constructs of IMC, nor by the research informing the discipline. Rather, it appears to have evolved little from traditional promotion management units and is close in content and structure to many introductory advertising courses. This paper suggests several possible explanations for this, including: (1) a tacit rejection of IMC as a valid concept; (2) a lack of information about what IMC is and what it is not; and (3) a scarcity of teaching and learning materials that are clearly focused on key constructs and research issues of IMC.
Resumo:
Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.
Resumo:
Linear algebra provides theory and technology that are the cornerstones of a range of cutting edge mathematical applications, from designing computer games to complex industrial problems, as well as more traditional applications in statistics and mathematical modelling. Once past introductions to matrices and vectors, the challenges of balancing theory, applications and computational work across mathematical and statistical topics and problems are considerable, particularly given the diversity of abilities and interests in typical cohorts. This paper considers two such cohorts in a second level linear algebra course in different years. The course objectives and materials were almost the same, but some changes were made in the assessment package. In addition to considering effects of these changes, the links with achievement in first year courses are analysed, together with achievement in a following computational mathematics course. Some results that may initially appear surprising provide insight into the components of student learning in linear algebra.