title: Teacher-researcher relationships and collaborations in research.

authors: Cowie, Bronwen

subjects: collaborative research

abstract: To understand the complexity of the classroom in ways that might inform teaching research in needed that explains both why and how something works. Teacher-researcher collaboration is essential if this is to happen. Collaborative work can ensure that research builds on from what teachers know and can do. Researchers working with teachers to address their current concerns are more likely to generate insights into what teachers might do and where they might go next. Collaboration can contribute a warrant for relevance for research findings. At the same teachers deepen and enhance their own practice through engaging in the research process. This paper describes and discusses some approaches to collaboration that have enables researchers and teachers to access a diversity of ideas and expertise to their mutual benefit.

text: Teacher-researcher relationships and collaborations in research. To understand the complexity of the classroom in ways that might inform teaching research in needed that explains both why and how something works. Teacher-researcher collaboration is essential if this is to happen. Collaborative work can ensure that research builds on from what teachers know and can do. Researchers working with teachers to address their current concerns are more likely to generate insights into what teachers might do and where they might go next. Collaboration can contribute a warrant for relevance for research findings. At the same teachers deepen and enhance their own practice through engaging in the research process. This paper describes and discusses some approaches to collaboration that have enables researchers and teachers to access a diversity of ideas and expertise to their mutual benefit.

year: 2010

title: Understanding what machine learning produces - Part I: Representations and their comprehensibility

authors: Cunningham, Sally Jo

subjects: computer science

abstract: The aim of many machine learning users is to comprehend the structures that are inferred from a dataset, and such users may be far more interested in understanding the structure of their data than in predicting the outcome of new test data. Part I of this paper surveys representations based on decision trees, production rules and decision graphs that have been developed and used for machine learning. These representations have differing degrees of expressive power, and particular attention is paid to their comprehensibility for non-specialist users. The graphic form in which a structure is portrayed also has a strong effect on comprehensibility, and Part II of this paper develops knowledge visualization techniques that are particularly appropriate to help answer the questions that machine learning users typically ask about the structures produced.

text: Understanding what machine learning produces - Part I: Representations and their comprehensibility The aim of many machine learning users is to comprehend the structures that are inferred from a dataset, and such users may be far more interested in understanding the structure of their data than in predicting the outcome of new test data. Part I of this paper surveys representations based on decision trees, production rules and decision graphs that have been developed and used for machine learning. These representations have differing degrees of expressive power, and particular attention is paid to their comprehensibility for non-specialist users. The graphic form in which a structure is portrayed also has a strong effect on comprehensibility, and Part II of this paper develops knowledge visualization techniques that are particularly appropriate to help answer the questions that machine learning users typically ask about the structures produced.

year: 1996-10

title: Murau a te tini (Mourned by the multitudes) & Pounamu (Greenstone)

authors: Rewi, Poia

subjects: Māori poetry

abstract: A song and a poem by Poia Rewi.

text: Murau a te tini (Mourned by the multitudes) & Pounamu (Greenstone) A song and a poem by Poia Rewi.

year: 2000-10