4582 research outputs found
Sort by
Delivering sustainability through construction and project management: principles, tools and practices
No full text
Report on the evaluation of one-to-one student and academic language and learning (ALL) adviser interactions
No full textTeaching individual students has been a core component of academic language and learning (ALL) work since its inception in Australia in the 1980s. In the first decades the success of one-to-one teaching was largely reported in terms of the level of usage by students, and the quality of the learning assumed by high levels of usage. A systematic approach to the evaluation of the effectiveness of one-to-one teaching has presented challenges for ALL practitioners for a number of reasons. First, ALL work is positioned and constructed in different ways in different universities and, for the most part, sits outside their mainstream teaching evaluation processes. In addition, one-to-one teaching is only one aspect of a complex, multifaceted role which usually includes resource development, teaching of groups and research. The commodification of university education and the concomitant emphasis on “customer service” has blurred the difference between teaching and service delivery adding further challenges to evaluating the one-to-one practice. The literature on evaluation from the broader context of education and on some current ALL evaluation practices and discussions among ALL practitioners have been explored for insights into evaluating one-to-one teaching. As well, a study was undertaken to identify the criteria that students use to judge the effectiveness of ALL one-to-one teaching. Based on the findings of the review and the study, a provisional framework for evaluating one-to-one practice has been developed and recommendations for its application suggested.
Collaboration between occupational therapists and teachers: Definitions, implementation and efficacy
No full textAn augmented penalty function method with penalty parameter updates for nonconvex optimization
No full textGiven an augmented Lagrangian scheme for a general optimization problem, we use an epsilon subgradient step for improving the dual function. This can be seen as an update for an augmented penalty method, which is more stable because it does not force the penalty parameter to tend to infinity. We establish for this update primal–dual convergence for our augmented penalty method. As illustration, we apply our method to the test-bed kissing number problem.
