title: Enhancing teaching and learning of primary mathematics through the use of apps

authors: Calder, Nigel Stuart

abstract: The report begins with a brief traverse of the associated research field, leading to the specific aims and research design of the project. The outcomes are then discussed, with teacher decisions about their use of apps, and the framework and contributing themes, outlined initially. Discussion of the key themes, with exemplars and data from the project, are then considered, followed by the transitions in teacher practice and the ways that mathematical thinking emerged. The final section, the conclusions, considers the key findings, limitations, implications for practice, and suggestions for further research to further enrich the field. But first, the background literature that informed the project is examined.

text: Enhancing teaching and learning of primary mathematics through the use of apps The report begins with a brief traverse of the associated research field, leading to the specific aims and research design of the project. The outcomes are then discussed, with teacher decisions about their use of apps, and the framework and contributing themes, outlined initially. Discussion of the key themes, with exemplars and data from the project, are then considered, followed by the transitions in teacher practice and the ways that mathematical thinking emerged. The final section, the conclusions, considers the key findings, limitations, implications for practice, and suggestions for further research to further enrich the field. But first, the background literature that informed the project is examined.

year: 2017

title: Prediction of Oestrus in Dairy Cows: An Application of Machine Learning to Skewed Data

authors: Lynam, Adam David

subjects: machine learning

abstract: The Dairy industry requires accurate detection of oestrus(heat) in dairy cows to maximise output of the animals. Traditionally this is a process dependant on human observation and interpretation of the various signs of heat. Many areas of the dairy industry can be automated, however the detection of oestrus is an area that still requires human experts.
This thesis investigates the application of Machine Learning classification techniques, on dairy cow milking data provided by the Livestock Improvement Corporation, to predict oestrus. The usefulness of various ensemble learning algorithms such as Bagging and Boosting are explored as well as specific skewed data techniques.
An empirical study into the effectiveness of classifiers designed to target skewed data is included as a significant part of the investigation. Roughly Balanced Bagging and the novel Under Bagging classifiers are explored in considerable detail and found to perform quite favourably over the SMOTE technique for the datasets selected. This study uses non-dairy, commonplace, Machine Learning datasets; many of which are found in the UCI Machine Learning Repository.

text: Prediction of Oestrus in Dairy Cows: An Application of Machine Learning to Skewed Data The Dairy industry requires accurate detection of oestrus(heat) in dairy cows to maximise output of the animals. Traditionally this is a process dependant on human observation and interpretation of the various signs of heat. Many areas of the dairy industry can be automated, however the detection of oestrus is an area that still requires human experts.
This thesis investigates the application of Machine Learning classification techniques, on dairy cow milking data provided by the Livestock Improvement Corporation, to predict oestrus. The usefulness of various ensemble learning algorithms such as Bagging and Boosting are explored as well as specific skewed data techniques.
An empirical study into the effectiveness of classifiers designed to target skewed data is included as a significant part of the investigation. Roughly Balanced Bagging and the novel Under Bagging classifiers are explored in considerable detail and found to perform quite favourably over the SMOTE technique for the datasets selected. This study uses non-dairy, commonplace, Machine Learning datasets; many of which are found in the UCI Machine Learning Repository.

year: 2009

title: The concept of partnership and The Treaty of Waitangi: Three case studies

authors: Morrison, Sandy

subjects: Te Tiriti o Waitangi

abstract: There has been, and continues to be, considerable debate about the meaning and intent of different versions of the Treaty of Waitangi and about the extent of its relevance to contemporary New Zealand. It is in this context that a number of organisations and institutions in New Zealand, anxious to demonstrate their positive support for the creation of a just society, have attempted to restructure in ways that allow for a 'partnership' between Māori and Pākehā. With reference to three different case studies, I argue here that such restructuring, although generally very well intentioned and very welcome, should not be seen - as it frequently is - as an expression of the fulfilment of partnership obligations arising out of the Treaty of Waitangi. To treat organisational restructuring in this way, particularly where it does not provide both 'partners' with an equal right to determine the operational parameters and future direction of the organisation, is to misrepresent (often wholly unintentionally) the nature of the Treaty. Nevertheless, one way of resolving some of the debates concerning the meaning and intent of the Treaty of Waitangi might be to establish a principle of equal partnership in the governance and management of state institutions.

text: The concept of partnership and The Treaty of Waitangi: Three case studies There has been, and continues to be, considerable debate about the meaning and intent of different versions of the Treaty of Waitangi and about the extent of its relevance to contemporary New Zealand. It is in this context that a number of organisations and institutions in New Zealand, anxious to demonstrate their positive support for the creation of a just society, have attempted to restructure in ways that allow for a 'partnership' between Māori and Pākehā. With reference to three different case studies, I argue here that such restructuring, although generally very well intentioned and very welcome, should not be seen - as it frequently is - as an expression of the fulfilment of partnership obligations arising out of the Treaty of Waitangi. To treat organisational restructuring in this way, particularly where it does not provide both 'partners' with an equal right to determine the operational parameters and future direction of the organisation, is to misrepresent (often wholly unintentionally) the nature of the Treaty. Nevertheless, one way of resolving some of the debates concerning the meaning and intent of the Treaty of Waitangi might be to establish a principle of equal partnership in the governance and management of state institutions.

year: 2005