title: Exploring curriculum implications of multimodal literacy in a New Zealand early childhood setting

authors: Haggerty, Maggie

subjects: early childhood curriculum

abstract: Calls to broaden notions of 'literacy' from a focus on print-based and verbal literacies to the incorporation of a range of modes of communication and representation are increasing. This paper uses case study data from 3- and 4-year-olds in a New Zealand kindergarten to explore the affordances offered by different literacies to facilitate communication and learning, and the interplay among literacies. The focus includes verbal, visual and spatial-motoric literacy modes. Several key ideas are discussed: first, that the affordances offered by particular modes may make them better suited to some tasks than others and convey meaning in different ways; second, that use of different modes in combination enhances children's communication and learning; third, that boundaries between traditional and non-traditional literacy modes seem to be permeable; and fourth, that pedagogical discussions with parents can contribute greatly to teachers' understanding of children's favoured literacy modes. Implications include the need for early years teachers to take a broad view of literacies as modes of communication, conceptualisation and meaning-making, so that teachers can notice, support and expand children's favoured modes.

text: Exploring curriculum implications of multimodal literacy in a New Zealand early childhood setting Calls to broaden notions of 'literacy' from a focus on print-based and verbal literacies to the incorporation of a range of modes of communication and representation are increasing. This paper uses case study data from 3- and 4-year-olds in a New Zealand kindergarten to explore the affordances offered by different literacies to facilitate communication and learning, and the interplay among literacies. The focus includes verbal, visual and spatial-motoric literacy modes. Several key ideas are discussed: first, that the affordances offered by particular modes may make them better suited to some tasks than others and convey meaning in different ways; second, that use of different modes in combination enhances children's communication and learning; third, that boundaries between traditional and non-traditional literacy modes seem to be permeable; and fourth, that pedagogical discussions with parents can contribute greatly to teachers' understanding of children's favoured literacy modes. Implications include the need for early years teachers to take a broad view of literacies as modes of communication, conceptualisation and meaning-making, so that teachers can notice, support and expand children's favoured modes.

year: 2010

title: Random Relational Rules

authors: Pfahringer, Bernhard

subjects: computer science

abstract: Exhaustive search in relational learning is generally infeasible, therefore some form of heuristic search is usually employed, such as in FOIL[1]. On the other hand, so-called stochastic discrimination provides a framework for combining arbitrary numbers of weak classifiers (in this case randomly generated relational rules) in a way where accuracy improves with additional rules, even after maximal accuracy on the training data has been reached. [2] The weak classifiers must have a slightly higher probability of covering instances of their target class than of other classes. As the rules are also independent and identically distributed, the Central Limit theorem applies and as the number of weak classifiers/rules grows, coverages for different classes resemble well-separated normal distributions. Stochastic discrimination is closely related to other ensemble methods like Bagging, Boosting, or Random forests, all of which have been tried in relational learning [3, 4, 5].

text: Random Relational Rules Exhaustive search in relational learning is generally infeasible, therefore some form of heuristic search is usually employed, such as in FOIL[1]. On the other hand, so-called stochastic discrimination provides a framework for combining arbitrary numbers of weak classifiers (in this case randomly generated relational rules) in a way where accuracy improves with additional rules, even after maximal accuracy on the training data has been reached. [2] The weak classifiers must have a slightly higher probability of covering instances of their target class than of other classes. As the rules are also independent and identically distributed, the Central Limit theorem applies and as the number of weak classifiers/rules grows, coverages for different classes resemble well-separated normal distributions. Stochastic discrimination is closely related to other ensemble methods like Bagging, Boosting, or Random forests, all of which have been tried in relational learning [3, 4, 5].

year: 2006

title: Indigenous children and youth: The case of marae courts in Aotearoa/New Zealand

authors: Toki, Valmaine

abstract: Marae2-based Courts are an initiative of the Judiciary that builds on existing programmes for offenders such as Te Whanau Awhina, and informed by the Koori Courts in Australia.3 This is the first time that a New Zealand court has conducted criminal cases on a Marae within the jurisdiction of the Youth Court. Most offenders referred to the programme are Maori4 and the process incorporates Maori tikanga (Maori customs).

text: Indigenous children and youth: The case of marae courts in Aotearoa/New Zealand Marae2-based Courts are an initiative of the Judiciary that builds on existing programmes for offenders such as Te Whanau Awhina, and informed by the Koori Courts in Australia.3 This is the first time that a New Zealand court has conducted criminal cases on a Marae within the jurisdiction of the Youth Court. Most offenders referred to the programme are Maori4 and the process incorporates Maori tikanga (Maori customs).

year: 2014