485 resultados para Learning algorithms


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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.

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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.