title: Technology and science education

authors: Jones, Alister

abstract: The incorporation of technology into the school curriculum is part of a worldwide trend in education. The way in which technology is incorporated depends on which country the reform is initiated in. The New Zealand Curriculum Framework (Ministry of Education, 1993a) includes science and technology as distinct learning areas. This chapter considers the view of technology expressed in both science in the New Zealand Curriculum (Ministry of Education, 1993b) and in Technology in the New Zealand Curriculum (Ministry of Education, 1995).
The chapter is divided into four sections. Firstly, the concept of technology in the science curriculum is identified and discussed; secondly, the use of some types of technological application to enhance the learning of science outcomes is considered; thirdly, the technology curriculum itself is discussed in order to highlight the concept of technology underpinning this statement so that comparisons can be made with the concept employed in the science curriculum, and finally the introduction of technology outcomes by science teachers in a science environment is explored.

text: Technology and science education The incorporation of technology into the school curriculum is part of a worldwide trend in education. The way in which technology is incorporated depends on which country the reform is initiated in. The New Zealand Curriculum Framework (Ministry of Education, 1993a) includes science and technology as distinct learning areas. This chapter considers the view of technology expressed in both science in the New Zealand Curriculum (Ministry of Education, 1993b) and in Technology in the New Zealand Curriculum (Ministry of Education, 1995).
The chapter is divided into four sections. Firstly, the concept of technology in the science curriculum is identified and discussed; secondly, the use of some types of technological application to enhance the learning of science outcomes is considered; thirdly, the technology curriculum itself is discussed in order to highlight the concept of technology underpinning this statement so that comparisons can be made with the concept employed in the science curriculum, and finally the introduction of technology outcomes by science teachers in a science environment is explored.

year: 1997

title: Using finite mixtures to robustify statistical models

authors: Rohan, Maheswaran

subjects: Robust Statistics

abstract: This thesis is concerned with robust estimation of the parameters of statistical models. Although robust estimation is a very good idea, it has some shortcomings when seen from the statistical modelling point of view. For example, there are no easily applicable principles for creating robust estimates in new situations. In this thesis, we are trying to introduce a unified method to obtain the robustified statistics for various situations such as the linear model and the generalized linear model. We wish to modify the maximum likelihood estimation procedure, which is very sensitive to the outliers. In order to reduce the effect on these estimates by outliers, we add an additional component, which would be of no interest but would contain all outliers, to the regular component forming a finite mixture. In fact, we use the finite mixture model to obtain a ``robustified'' estimate for a model parameter $\theta$, where the finite mixture form is being used as a mathematical tool to have a tractable form of analysis rather than being used as a serious model for the data. We employ the EM algorithm to obtain the our proposed robustified estimates for the parameters. Our estimates are compared with some other estimates defined in the robust statistics literature. This thesis examines the robustness of the proposed estimates using the concept of influence function. The estimates are defined iteratively, so that the implicit differentiation method of Jorgensen is used to obtain the influence functions of the estimates. We give example plots of these influence functions which are bounded. In this thesis, we give mathematical results for all cases and we use well known real data sets to investigate our method. The statistical software R is used for all investigation. Finally, we hope that this method may give a unified approach for making parameter estimation in statistical models more robust.

text: Using finite mixtures to robustify statistical models This thesis is concerned with robust estimation of the parameters of statistical models. Although robust estimation is a very good idea, it has some shortcomings when seen from the statistical modelling point of view. For example, there are no easily applicable principles for creating robust estimates in new situations. In this thesis, we are trying to introduce a unified method to obtain the robustified statistics for various situations such as the linear model and the generalized linear model. We wish to modify the maximum likelihood estimation procedure, which is very sensitive to the outliers. In order to reduce the effect on these estimates by outliers, we add an additional component, which would be of no interest but would contain all outliers, to the regular component forming a finite mixture. In fact, we use the finite mixture model to obtain a ``robustified'' estimate for a model parameter $\theta$, where the finite mixture form is being used as a mathematical tool to have a tractable form of analysis rather than being used as a serious model for the data. We employ the EM algorithm to obtain the our proposed robustified estimates for the parameters. Our estimates are compared with some other estimates defined in the robust statistics literature. This thesis examines the robustness of the proposed estimates using the concept of influence function. The estimates are defined iteratively, so that the implicit differentiation method of Jorgensen is used to obtain the influence functions of the estimates. We give example plots of these influence functions which are bounded. In this thesis, we give mathematical results for all cases and we use well known real data sets to investigate our method. The statistical software R is used for all investigation. Finally, we hope that this method may give a unified approach for making parameter estimation in statistical models more robust.

year: 2011

title: ‘Doctoring’ our own: Confessions of a Māori doctoral supervisor

authors: Hohepa, Margie Kahukura

subjects: Māori doctoral student

abstract: There is very little literature, empirically based or otherwise, on the supervision of Māori doctoral students (Fitzgerald, 2005; Pope, 2008; Kidman, 2007; Smith, 2007). There is even less relating to Māori supervisors working with Māori doctoral students (Kidinan, 2007), let alone Māori supervisors working with non- Māori students. While the relatively large corpus of literature on doctoral supervision may be of some assistance to Māori supervisors, there is also a dearth of studies that focus on the pedagogical aspects. Research undertaken by Elizabeth McKinley and her co-researchers (McKinley, Grant, Middleton, Irwin & Williams, 2009) will now help to fill the literature gap on the teaching and learning process of supervision as it pertains to Māori.

text: ‘Doctoring’ our own: Confessions of a Māori doctoral supervisor There is very little literature, empirically based or otherwise, on the supervision of Māori doctoral students (Fitzgerald, 2005; Pope, 2008; Kidman, 2007; Smith, 2007). There is even less relating to Māori supervisors working with Māori doctoral students (Kidinan, 2007), let alone Māori supervisors working with non- Māori students. While the relatively large corpus of literature on doctoral supervision may be of some assistance to Māori supervisors, there is also a dearth of studies that focus on the pedagogical aspects. Research undertaken by Elizabeth McKinley and her co-researchers (McKinley, Grant, Middleton, Irwin & Williams, 2009) will now help to fill the literature gap on the teaching and learning process of supervision as it pertains to Māori.

year: 2010