Building on the past for the future : assessment for learning as a field of exchange

Standardised testing does not recognise the creativity and skills of marginalised youth. This paper presents the development of an innovative approach to assessment designed for the re-engagement of at risk youth who have left formal schooling and are now in an alternative education institution. An electronic portfolio system (EPS) has been developed to capture, record and build on the broad range of students’ cultural and social capital. The assessment as a field of exchange model draws on categories from sociological fields of capital and reconceptualises an eportfolio and social networking hybrid system as a sociocultural zone of learning and development. The EPS, and assessment for learning more generally, are conceptualised as social fields for the exchange of capital (Bourdieu 1977, 1990). The research is underpinned by a sociocultural theoretical perspective that focuses on how students and teachers at the Flexible Learning Centre (FLC) develop and learn, within the zone of proximal development (Vygotsky, 1978). The EPS is seen to be highly effective in the engagement and social interaction between students, teachers and institutions. It is argued throughout this paper that the EPS provides a structurally identifiable space, an arena of social activity, or a field of exchange. The students, teachers and the FLC within this field are producing cultural capital exchanges. The term efield (exchange field) has been coined to refer to this constructed abstract space. Initial results from the trial show a general tendency towards engagement with the EPS and potential for the attainment of socially valued cultural capital in the form of school credentials.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

Multiview point cloud kernels for semisupervised learning [Lecture Notes]

In semisupervised learning (SSL), a predictive model is learn from a collection of labeled data and a typically much larger collection of unlabeled data. These paper presented a framework called multi-view point cloud regularization (MVPCR), which unifies and generalizes several semisupervised kernel methods that are based on data-dependent regularization in reproducing kernel Hilbert spaces (RKHSs). Special cases of MVPCR include coregularized least squares (CoRLS), manifold regularization (MR), and graph-based SSL. An accompanying theorem shows how to reduce any MVPCR problem to standard supervised learning with a new multi-view kernel.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Learning domain ontology for tag recommendation

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging and represent those in a form of ontology, but the application of the learned ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

Elementary teacher’s conceptions of inquiry teaching : messages for teacher development

The advocacy for inquiry-based learning in contemporary curricula assumes the principle that students learn in their own way by drawing on direct experience fostered by the teacher. That students should be able to discover answers themselves through active engagement with new experiences was central to the thinking of eminent educators such as Pestalozzi, Dewey and Montessori. However, even after many years of research and practice, inquiry learning as a referent for teaching still struggles to find expression in the average teachers' pedagogy. This study drew on interview data from 20 elementary teachers. A phenomenographic analysis revealed three conceptions of teaching for inquiry learning in science in the elementary years of schooling: (a) The Experience- centred conception where teachers focused on providing interesting sensory experiences to students; (b) The Problem-centred conception where teachers focused on challenging students with engaging problems; and (c) The Question-centred conception where teachers focused on helping students to ask and answer their own questions. Understanding teachers' conceptions has implications for both the enactment of inquiry teaching in the classroom as well as the uptake of new teaching behaviours during professional development, with enhanced outcomes for engaging students in Science.

Ontology learning from user tagging for recommendation making

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging into some form of ontology, but the application of the resulted ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

Current AI in games : a review

As the graphics race subsides and gamers grow weary of predictable and deterministic game characters, game developers must put aside their “old faithful” finite state machines and look to more advanced techniques that give the users the gaming experience they crave. The next industry breakthrough will be with characters that behave realistically and that can learn and adapt, rather than more polygons, higher resolution textures and more frames-per-second. This paper explores the various artificial intelligence techniques that are currently being used by game developers, as well as techniques that are new to the industry. The techniques covered in this paper are finite state machines, scripting, agents, flocking, fuzzy logic and fuzzy state machines decision trees, neural networks, genetic algorithms and extensible AI. This paper introduces each of these technique, explains how they can be applied to games and how commercial games are currently making use of them. Finally, the effectiveness of these techniques and their future role in the industry are evaluated.

Crisis preparedness of construction companies

In high-risk industries, companies with well-conceived crisis management plans are at a commercial advantage. While there is some understanding of the risk management practices of construction companies, there is little insight into their crisis preparedness. This paper presents the findings of exploratory research that investigated this issue. Using a diagnostic model of crisis preparedness that has been developed and tested across a broad range of industries, it concludes that if the sample surveyed is typical, then corporate philosophies in construction companies do not support crisis management activities. Furthermore, crisis planning is rudimentary and undertaken in an insular, informal, fragmented fashion, supported by few resources and little strategic guidance. Consequently, many construction companies will have an inadequate understanding of their crisis exposure, of how to cope with crises when they happen, and of how to learn and recover from their aftermath.

How can a mentor’s personal attributes and pedagogical knowledge develop a preservice teacher’s behaviour management?

This study presents the importance of a mentor’s (experienced teacher’s) personal attributes and pedagogical knowledge for developing a mentee’s (preservice teacher’s) teaching practices. Specifically, preservice teachers can have difficulties with behaviour management and must learn management strategies that help them to teach more effectively. This paper investigates how mentoring may facilitate the development of a mentee’s behaviour management strategies, in particular what personal attributes and pedagogical knowledge are used in this process.

Early years teachers’ epistemic beliefs and beliefs about children’s moral learning

There is strong political and social interest in values education both internationally and across Australia. Investment in young children is recognised as important for the development of moral values for a cohesive society; however, little is known about early years teachers’ beliefs about moral values teaching and learning. The aim of the current study was to investigate the relationships between Australian early years teachers’ epistemic beliefs and their beliefs about children’s moral learning. Three hundred and seventy-nine teachers completed a survey about their personal epistemic beliefs and their beliefs about children’s moral learning. Results indicated that teachers with more sophisticated epistemic beliefs viewed children as capable of taking responsibility for their own moral learning. Conversely, teachers who held more naive or simplistic personal epistemic beliefs agreed that children need to learn morals through learning the rules for behaviour. Results are discussed in terms of the implications for moral pedagogy in the classroom and teacher professional development. It is suggested that in conjunction with explicitly reflecting on epistemic beliefs, professional development may need to assist teachers to ascertain how their beliefs might relate to their moral pedagogies in order to make any adjustments.

Teachers’ and parents’ perspectives of digital technology in the lives of young children

The pervasiveness of technology in the 21st Century has meant that adults and children live in a society where digital devices are integral to their everyday lives and participation in society. How we communicate, learn, work, entertain ourselves, and even shop is influenced by technology. Therefore, before children begin school they are potentially exposed to a range of learning opportunities mediated by digital devices. These devices include microwaves, mobile phones, computers, and console games such as Playstations® and iPods®. In Queensland preparatory classrooms and in the homes of these children, teachers and parents support and scaffold young children’s experiences, providing them with access to a range of tools that promote learning and provide entertainment. This paper examines teachers’ and parents’ perspectives and considers whether they are techno-optimists who advocate for and promote the inclusion of digital technology, or whether they are they techno-pessimists, who prefer to exclude digital devices from young children’s everyday experiences. An exploratory, single case study design was utilised to gather data from three teachers and ten parents of children in the preparatory year. Teacher data was collected through interviews and email correspondence. Parent data was collected from questionnaires and focus groups. All parents who responded to the research invitation were mothers. The results of data analysis identified a misalignment among adults’ perspectives. Teachers were identified as techno-optimists and parents were identified as techno-pessimists with further emergent themes particular to each category being established. This is concerning because both teachers and mothers influence young children’s experiences and numeracy knowledge, thus, a shared understanding and a common commitment to supporting young children’s use of technology would be beneficial. Further research must investigate fathers’ perspectives of digital devices and the beneficial and detrimental roles that a range of digital devices, tools, and entertainment gadgets play in 21st Century children’s lives.

Practices for teaching moral values in the early years : a call for a pedagogy of participation

Schools have long been seen as institutions for preparing children for life, both academically and as moral agents in society. In order to become capable, moral citizens, children need to be provided with opportunities to learn moral values. However, little is known about how teachers enact social and moral values programs in the classroom. The aim of this paper is to investigate the practices that Australian early years teachers describe as important for teaching moral values. To investigate early years teachers’ understandings of moral pedagogy, 379 Australian teachers with experience teaching children in the early years were invited to participate in an on-line survey. This paper focuses on responses provided to an open-ended question relating to teaching practices for moral values. The responses were analysed using an interpretive methodology. The results indicate that the most prominent approaches to teaching moral values described by this group of Australian early years teachers were engaging children in moral activities. This was closely followed by teaching practices for transmitting moral values. Engaging children in building meaning and participatory learning for moral values were least often described.

The African Institute for Mathematical Sciences

Its mission is to promote Mathematics and Science in Africa and to provide a focal point for Mathematics university training in Africa. It offers scholarships for up to 50 students to come and study for a period of nine months. Of the 50 students, about 15 positions are reserved for females. In the 2006/2007 intake there were over 250 applicants. The students are housed and fed and their return travel from their home town is fully funded. Lecturers also stay at AIMS and share their meals with the students, so that a rapport quickly develops. The students are away from their families and friends for nine months and are absolutely committed to the discipline of Mathematics. When they first arrive, some of them have little ability in English but since all tuition is in English they quickly learn. Some find the transitions difficult but they all support one another and at the end of their time their English skills are very good. The students do a series of subjects that last for about three weeks each, consisting of 30 contact hours, as well as a thesis/project. Each course has a number of assignments associated with it and these get evaluated. AIMS has seven or eight teaching assistants who help with the tutorials, marking, advice, and who are a vital component of AIMS.

Investigating literacy years 4-9 : a pilot. Final report.

Investigating Literacy Years 4-9: A pilot acknowledges that the literacy required of students in the middle years of schooling changes as they begin to read and write to learn across the subject areas using various resources and media. Teachers begin to look for evidence of understanding of concepts, content details, appropriate genre uses and the capacity to work with extended and complex texts. Yet, in comparison to the early years, there has been relatively little research conducted during this period of schooling, especially Years 4-7 of primary schooling (Comber et al, 2002). However, evidence suggests that gaps between those who perform highly and those who perform poorly on standardised measures of literacy increase rather than decrease, and these gaps relate to social background. Hence there is a need to investigate how different school communities with diverse student populations design rich curriculum at these stages of schooling and explicitly teach young people to handle new and changing literacy demands.