Making sense of an everyday science text : linguistic, visual and spatial design

In this article, we take a close look at the literacy demands of one task from the ‘Marvellous Micro-organisms Stage 3 Life and Living’ Primary Connections unit (Australian Academy of Science, 2005). One lesson from the unit, ‘Exploring Bread’, (pp 4-8) asks students to ‘use bread labels to locate ingredient information and synthesise understanding of bread ingredients’. We draw upon a framework offered by the New London Group (2000), that of linguistic, visual and spatial design, to consider in more detail three bread wrappers and from there the complex literacies that students need to interrelate to undertake the required task. Our findings are that although bread wrappers are an example of an everyday science text, their linguistic, visual and spatial designs and their interrelationship are not trivial. We conclude by reinforcing the need for teachers of science to also consider how the complex design elements of everyday science texts and their interrelated literacies are made visible through instructional practice.

Hybridized writing for scientific literacy : pedagogy and evidence

Disengagement of students in science and the scientific literacy of young adults are interrelated international concerns. One way to address these concerns is to engage students imaginatively in activities designed to improve their scientific literacy. Our ongoing program of research has focused on the effects of a sequence of activities that require students to transform scientific information on important issues for their communities from government websites into narrative text suitable for a lay reader. These hybridized stories we call BioStories. Students upload their stories for peer review to a dedicated website. Peer reviews are intended to help students refine their stories. Reviewing BioStories also gives students access to a wider range of scientific topics and writing styles. We have conducted separate studies with students from Grade 6, Grade 9 and Grade 12, involving case study and quasi-experimental designs. The results from the 6th grade study support the argument that writing the sequence of stories helped the students become more familiar with the scientific issue, develop a deeper understanding of related biological concepts, and improve their interest in science. Unlike the Grade 6 study, it was not possible to include a control group for the study conducted across eight 9th grade classes. Nevertheless, these results suggest that hybridized writing developed more positive attitudes toward science and science learning, particularly in terms of the students’ interest and enjoyment. In the most recent case study with Grade 12 students, we found that pride, strength, determination, interest and alertness were among the positive emotions most strongly elicited by the writing project. Furthermore, the students expressed enhanced feelings of self-efficacy in successfully writing hybridized scientific narratives in science. In this chapter, we describe the pedagogy of hybridized writing in science, overview the evidence to support this approach, and identify future developments.

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

Childhood-as-rescue in the emergence and spread of the U.S. public school

In this volume, the editors have brought together prominent international contributors to examine the relevance of Foucauldian thought on educational theory, practice and institutional life. The result is a diverse collection that offers broad and engaging analyses of how power and knowledge are configured in the practices and norms of schooling. This text not only provides a critical examination of the significance of Foucauldian thought for education, but also discusses how Foucault's theories are arrayed in the everyday life of schools.