Attitudes and interests towards biotechnology: The mismatch between students and teachers

Increasing the scientific literacy of Australians has become an educational priority in recent times. The ‘Science State – Smart State’ initiative of the Queensland Government involves an action plan for improving science education that includes a Science for Life action. A desired outcome is for an increased understanding of the natural world so that responsible decisions concerning our future wellbeing can be made in an age of science and technology. Biotechnology is a technology that is having profound impact on our lives. This paper describes how 15-16 year old students and biology teachers revealed a mismatch in both attitudes and interests towards biotechnology between the students and teachers. The findings are of interest as the teachers are writing biotechnology into their work programs in response to new syllabus documents. The teacher’s areas of interest did not match those of the students, possibly resulting in a curriculum the teachers want to teach, but the students do not want to learn.

Learning to be literate : issues of pedagogy for recently arrived refugee youth in Australia

This paper focuses on issues of access to productive literacy learning as part of socially just schooling for recently arrived refugee youth within Australia. It argues that a sole reliance on traditional ESL pedagogy is failing this vulnerable group of students, who differ significantly from past refugees who have settled in Australia. Many have been ‘placeless’ for some time, are likely to have received at best an interrupted education before arriving in Australia, and may have experienced signification trauma (Christie & Sidhu, 2006; Cottone, 2004; Miller, Mitchell, & Brown, 2005). Australian Government policy has resulted in spacialized settlement, leaving particular schools dealing with a large influx of refugee students who may be attending school for the first time (Centre for Multicultural Youth Issues, 2004; Sidhu & Christie, 2002). While this has implications generally, it has particular consequences for secondary school students attempting to learn English literacy in short periods of time, without basic foundations in either English or print-based literacy in any first language (Centre for Multicultural Youth Issues, 2006). Many of these students leave schools without the most basic early literacy practices, having endured several years of pedagogy pitched well beyond their needs. This paper suggests that schools must take up three key roles: to educate, to provide a site for the development of civic responsibility, and to act as a site for welfare with responsibility. As a system, our department needs to work out what can we do for 17-18 year olds that are coming into our school system in year 10 without more than 1-2 years of education. I don't think there is a policy about what to do. – (T2-ESL teacher)

EAP essentials : a teacher's guide to principles and practice

Book review - Ancient scholars once journeyed across the Alps to study Italian law while some sailed the Mediterranean to learn Greek philosophy or examine Arabic scripts on science, medicine and mathematics. Devotees of philosophical and religious thought migrated to the Orient in search of transcendental wisdom. Today, the quest for knowledge has not changed as English-medium universities experience unprecedented internationalisation. This book is a publication for such a time as this. The authors invite readers to "join the tribe" (Becher, 1998) and learn the specific academic discourse and culture of English for Academic Purposes (EAP).

Location-based games : transforming everyday environments into dynamic learning spaces

Location based games (LBGs) provide an opportunity to look at how new technologies can support a reciprocal relationship between formal classroom learning and learning that can potentially occur in other everyday environments. Fundamentally many games are intensely engaging due to the resulting social interactions and technical challenges they provide to individual and group players. By introducing the use of mobile devices we can transport these characteristics of games into everyday spaces. LBGs are understood as a broad genre incorporating ideas and tools that provide many unique opportunities for us to to reveal, create and even subvert various social, cultural, technical, and scientific interpretations of place, in particular places where learning is sometimes problematic.--------- A team of Queensland game developers have learnt a great deal through designing a range of LBGs such as SCOOT for various user groups and places. While these LBGs were primarily designed as social events, we found that the players recognised and valued the game as an opportunity to learn about their environment, it's history, cultural significance, inhabitants, services etc. Since identifying the strong pedagogical outcomes of LBGs, the team has created a set of authoring tools for people to design and host their own LBGs. A particular version of this is known as MiLK the mobile learning kit for schools.---------- This presentation will include examples of how LBGs have been used to improve the teaching and learning outcomes in various contexts. Participants will be introduced to MiLK and invited to trial it in their own classrooms with students.

Critique groups : a technique for the author’s toolbox?

With a lack of places to gain an education in the craft of romance writing, novelists have few places to turn to gain real feedback. This paper investigates an alternative to textbooks, conferences, and workshops through an examination of the role provided to the writer by critique groups. How these groups work, how they benefit an author, and the critique groups as a whole are discussed. This work studies the form of Peer Assessment and Learning (PAL) and compares the technique used by educational institutions all over the world with the practice of author groups critiquing their own work. The research shows how a critique group can assist a writer to learn, grow and develop, helping to enhance the writer’s skills through constructive feedback, which gives them confidence to sell their work.

Learning to win process-control games watching game-masters

The present paper focuses on some interesting classes of process-control games, where winning essentially means successfully controlling the process. A master for one of these games is an agent who plays a winning strategy. In this paper we investigate situations in which even a complete model (given by a program) of a particular game does not provide enough information to synthesize—even incrementally—a winning strategy. However, if in addition to getting a program, a machine may also watch masters play winning strategies, then the machine is able to incrementally learn a winning strategy for the given game. Studied are successful learning from arbitrary masters and from pedagogically useful selected masters. It is shown that selected masters are strictly more helpful for learning than are arbitrary masters. Both for learning from arbitrary masters and for learning from selected masters, though, there are cases where one can learn programs for winning strategies from masters but not if one is required to learn a program for the master's strategy itself. Both for learning from arbitrary masters and for learning from selected masters, one can learn strictly more by watching m+1 masters than one can learn by watching only m. Last, a simulation result is presented where the presence of a selected master reduces the complexity from infinitely many semantic mind changes to finitely many syntactic ones.

From Civil Strife to Civil Society: civil and military responsibilities in disrupted states

"The 1990s saw the United Nations, the militaries of key member states, and NGOs increasingly entangled in the complex affairs of disrupted states. Whether as deliverers of humanitarian assistance or as agents of political, social, and civic reconstruction, whether in Somalia, Bosnia, Kosovo, or East Timor, these actors have had to learn ways of interacting with each other in order to optimize the benefits for the populations they seek to assist. Yet the challenges have proved daunting. Civil and military actors have different organizational cultures and standard operating procedures and are confronted with the need to work together to perform tasks to which different actors may attach quite different priorities."--BOOK JACKET.

The nonconceptual gateway to early word learning

My research investigates why nouns are learned disproportionately more frequently than other kinds of words during early language acquisition (Gentner, 1982; Gleitman, et al., 2004). This question must be considered in the context of cognitive development in general. Infants have two major streams of environmental information to make meaningful: perceptual and linguistic. Perceptual information flows in from the senses and is processed into symbolic representations by the primitive language of thought (Fodor, 1975). These symbolic representations are then linked to linguistic input to enable language comprehension and ultimately production. Yet, how exactly does perceptual information become conceptualized? Although this question is difficult, there has been progress. One way that children might have an easier job is if they have structures that simplify the data. Thus, if particular sorts of perceptual information could be separated from the mass of input, then it would be easier for children to refer to those specific things when learning words (Spelke, 1990; Pylyshyn, 2003). It would be easier still, if linguistic input was segmented in predictable ways (Gentner, 1982; Gleitman, et al., 2004) Unfortunately the frequency of patterns in lexical or grammatical input cannot explain the cross-cultural and cross-linguistic tendency to favor nouns over verbs and predicates. There are three examples of this failure: 1) a wide variety of nouns are uttered less frequently than a smaller number of verbs and yet are learnt far more easily (Gentner, 1982); 2) word order and morphological transparency offer no insight when you contrast the sentence structures and word inflections of different languages (Slobin, 1973) and 3) particular language teaching behaviors (e.g. pointing at objects and repeating names for them) have little impact on children's tendency to prefer concrete nouns in their first fifty words (Newport, et al., 1977). Although the linguistic solution appears problematic, there has been increasing evidence that the early visual system does indeed segment perceptual information in specific ways before the conscious mind begins to intervene (Pylyshyn, 2003). I argue that nouns are easier to learn because their referents directly connect with innate features of the perceptual faculty. This hypothesis stems from work done on visual indexes by Zenon Pylyshyn (2001, 2003). Pylyshyn argues that the early visual system (the architecture of the "vision module") segments perceptual data into pre-conceptual proto-objects called FINSTs. FINSTs typically correspond to physical things such as Spelke objects (Spelke, 1990). Hence, before conceptualization, visual objects are picked out by the perceptual system demonstratively, like a finger pointing indicating ‘this’ or ‘that’. I suggest that this primitive system of demonstration elaborates on Gareth Evan's (1982) theory of nonconceptual content. Nouns are learnt first because their referents attract demonstrative visual indexes. This theory also explains why infants less often name stationary objects such as plate or table, but do name things that attract the focal attention of the early visual system, i.e., small objects that move, such as ‘dog’ or ‘ball’. This view leaves open the question how blind children learn words for visible objects and why children learn category nouns (e.g. 'dog'), rather than proper nouns (e.g. 'Fido') or higher taxonomic distinctions (e.g. 'animal').

Informed learning: a pedagogical construct attending simultaneously to information use and learning.

The idea of informed learning, applicable in academic, workplace and community settings, has been derived largely from a program of phenomenographic research in the field of information literacy, which has illuminated the experience of using information to learn. Informed learning is about simultaneous attention to information use and learning, where both information and learning are considered to be relational; and is built upon a series of key concepts such as second–order perspective, simultaneity, awareness, and relationality. Informed learning also relies heavily on reflection as a strategy for bringing about learning. As a pedagogical construct, informed learning supports inclusive curriculum design and implementation. This paper reports aspects of the informed learning research agenda which are currently being pursued at the Queensland University of Technology (QUT). The first part elaborates the idea of informed learning, examines the key concepts underpinning this pedagogical construct, and explains its emergence from the research base of the QUT Information Studies research team. The second presents a case, which demonstrates the ongoing development of informed learning theory and practice, through the development of inclusive informed learning for a culturally diverse higher education context.

Anna Clark (2008) History’s Children: History Wars in the Classroom. UNSW Press, Sydney, 178 pages

“History’s Children” stems from Anna Clark’s 2004 postdoctoral research into the ways in which Australian students connect with the past, and aims at bringing some classroom perspectives into the public debates about Australian history education. Although the title makes reference to the “History Wars”, there is little evidence of contestation, engagement, passion or intellectual excitement in Clark’s conclusions about what happens in history classrooms. Rather, Clark’s small focus groups with 182 high school students in 34 high schools around Australia indicate that “it got a bit dismal hearing student after student being so dismissive of Australian history” (p. 143). Apart from some enthusiasm for the study of Australians at war, a sort of resigned boredom seems to characterise what students have to say about learning Australian history, despite their acknowledgement that it is important to “know about” it.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Doing justice : young people’s representations of the Murray-Darling Basin

The business of helping children to grow up as ‘custodians’, or ‘future managers’ of the Murray-Darling Basin is not simple, and that single sources of information and ways of seeing the environment are not enough. Children (and adults) need to be able to relate individually, emotionally and aesthetically to their places if they are to learn to love them. However, they also need access to a variety of ways of thinking and seeing those same places if they are to be able to take action to sustain them – action that inevitably involves forms of communication with their fellow citizens. This chapter documents the writing and art program Special Forever, with its focus on communications, as an important intervention into promoting eco-social sustainability.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

How to tell the difference between a positive image and a stereotype: reading Priscilla, Queen of the Desert

This paper intervenes in critical discussions about the representation of homosexuality. Rejecting the ‘manifest content’ of films, it turns to cultural history to map those public discourses which close down the ways in which films can be discussed. With relation to The Adventures of Priscilla, Queen of the Desert, it examines discussions of the film in Australian newspapers (both queer and mainstream) and finds that while there is disagreement about the interpretation to be made of the film, the terms within which those interpretations can be made are quite rigid. A matrix based on similarity, difference and value provides a series of positions and a vocabulary (transgression, assimilation, positive images and stereotypes) through which to make sense of this film. The article suggests that this matrix, and the idea that similarity and difference provide a suitable axis for making sense of homosexual identity, are problematic in discussing homosexual representation.

Adding a receding horizon to Locally Weighted Regression for learning robot control

There have been notable advances in learning to control complex robotic systems using methods such as Locally Weighted Regression (LWR). In this paper we explore some potential limits of LWR for robotic applications, particularly investigating its application to systems with a long horizon of temporal dependence. We define the horizon of temporal dependence as the delay from a control input to a desired change in output. LWR alone cannot be used in a temporally dependent system to find meaningful control values from only the current state variables and output, as the relationship between the input and the current state is under-constrained. By introducing a receding horizon of the future output states of the system, we show that sufficient constraint is applied to learn good solutions through LWR. The new method, Receding Horizon Locally Weighted Regression (RH-LWR), is demonstrated through one-shot learning on a real Series Elastic Actuator controlling a pendulum.