Thinking Critically in the Land of Princesses and Giants : The Affordances and Challenges of Critical Approaches in the Early Years

During the last four decades, educators have created a range of critical literacy approaches for different contexts, including compulsory schooling (Luke & Woods, 2009) and second language education (Luke & Dooley, 2011). Despite inspirational examples of critical work with young students (e.g., O’Brien, 1994; Vasquez, 1994), Comber (2012) laments the persistent myth that critical literacy is not viable in the early years. Assumptions about childhood innocence and the priorities of the back-to-basics movement seem to limit the possibilities for early years literacy teaching and learning. Yet, teachers of young students need not face an either/or choice between the basic and critical dimensions of literacy. Systematic ways of treating literacy in all its complexity exist. We argue that the integrative imperative is especially important in schools that are under pressure to improve technical literacy outcomes. In this chapter, we document how critical literacy was addressed in a fairytales unit taught to 4.5 - 5.5 year olds in a high diversity, high poverty Australian school. We analyze the affordances and challenges of different approaches to critical literacy, concluding they are complementary rather than competing sources of possibility. Furthermore, we make the case for turning familiar classroom activities to critical ends.

Talking it through : the case for the use of conversation analytic approaches in the analysis of news journalism

This study makes out the case for the use of the Conversational Analytic method as a research approach that might both extricate and chronicle the features of the journalism interview. It seeks to encourage such research to help inform understanding of this form and to provide further lessons as to the nature of journalism practice. Such studies might follow many paths but this paper focuses more particularly on the outcomes for the debate as to the continued relevance of "objectivity" in informing journalism professional practice. To make out the case for the veracity of CA as a means through which the conduct of journalism practice might be explored the paper examines: the theories of the interaction order that gave rise to the CA method; outlines the key features of the journalism interview as explicated through the CA approach; outlines the implications of such research for the establishment of the standing of "objectivity". It concludes as to the wider relevance of such studies of journalism practice for a fracturing journalism field, which suffers from a lack of benchmarks to measure the public benefit of the range of forms that now proliferate on the internet.

Text recognition approaches for indoor robotics : a comparison

This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Critical literacy and second language learning

An introductory overview of the historical foundations, practical precedents of current 'critical' approaches to English as a Second Language teaching - with specific reference to 'critical pedagogy' and 'text analytic' work.

The heterogeneous cluster ensemble method using hubness for clustering text documents

We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Video-stimulated accounts: Young children accounting for interactional matters in front of peers

Research in the early years places increasing importance on participatory methods to engage children. The playback of video-recording to stimulate conversation is a research method that enables children’s accounts to be heard and attends to a participatory view. During video-stimulated sessions, participants watch an extract of video-recording of a specific event in which they were involved, and then account for their participation in that event. Using an interactional perspective, this paper draws distinctions between video-stimulated accounts and a similar research method, popular in education, that of video-stimulated recall. Reporting upon a study of young children’s interactions in a playground, video-stimulated accounts are explicated to show how the participants worked toward the construction of events in the video-stimulated session. This paper discusses how the children account for complex matters within their social worlds, and manage the accounting of others in the video-stimulated session. When viewed from an interactional perspective and used alongside fine grained analytic approaches, video-stimulated accounts are an effective method to provide the standpoint of the children involved and further the competent child paradigm.

University of Glasgow at ImageCLEFPhoto 2009 : optimising similarity and diversity in image retrieval

In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

Critical linguistics in the early years : exploring functions of language through sophisticated picture books and process drama strategies

In this chapter we describe a critical fairytales unit taught to 4.5 to 5.5 year olds in a context of intensifying pressure to raise literacy achievement. The unit was infused with lessons on reinterpreted fairytales followed by process drama activities built around a sophisticated picture book, Beware of the Bears (MacDonald, 2004). The latter entailed a text analytic approach to critical literacy derived from systemic functional linguistics (Halliday, 1978; Halliday & Matthiessen, 2004). This approach provides a way of analysing how words and discourse are used to represent the world in a particular way and shape reader relations with the author in a particular field (Janks, 2010).

Achieving competence: The interactional features of children's storytelling

Early years researchers interested in storytelling have largely focused on the development of children’s language and social skills within constructed story sessions. Less focus has been given to the interactional aspects of storytelling in children’s everyday conversation and how the members themselves, the storytellers and story recipients, manage storytelling. An interactional view, using ethnomethodological and conversation analytic approaches, offers the opportunity to study children’s narratives in terms of ‘members work’. Detailed examination of a video-recorded interaction among a group of children in a preparatory year playground shows how the children managed interactions within conversational storytelling. Analyses highlight the ways in which children worked at gaining a turn and made a story tellable within a round of second stories. Investigating children’s competence-in-action ‘from within’, the findings from this research show how children invoke and accomplish competence through their interactions.

Afterschool MediaClub: Critical literacy in a high diversity, high poverty urban setting

In this chapter we present analyses of data produced with young people in an afterschool digital literacy program for 9 – 12 year olds. The young people were students at a high diversity, high poverty outer suburban elementary school in Queensland, Australia. The club was part of the URLearning research project (2010-14). In the classroom-based component of the project we worked with teachers to develop intellectually substantive and critical digital literacy practice. MediaClub was in some ways complementary to the classroom component; it was designed to skill up interested kids as digital media experts not only for their families and communities, but also for the classroom. Given the critical literacy traditions established in Australian schools, we approached MediaClub with certain critical expectations. In this chapter we look at what ensued, highlighting unanticipated critical outcomes at a time of heightened struggle over English curriculum. Critical literacy has been part of official English curriculum in Queensland since the early 1990s. The approach has been primarily text analytic, concerned with giving students access to genres of power and tools for understanding the ideological work of language through text. Many ideas for translating this normative critical project into classroom practice have been developed for use from the earliest elementary grades onwards. However, curricular space for critical literacy is under pressure. Amongst other things, this reflects both the development of Australia’s first national curriculum and the construction of a regimen of national literacy testing. At MediaClub we found a certain resistance to learning activities which were “too much like school”. However, in a context of increased control of teachers’ and students’ work in the classroom, MediaClub evolved as a learning space that can be understood in critical terms. Our experience in this regard might be of interest to teachers and researchers in high diversity high poverty settings that are strongly controlled through increasingly prescriptive – even scripted – pedagogies.

Multilingualism and speech-language competence in early childhood: Impact on academic and social-emotional outcomes at school

This large-scale longitudinal population study provided a rare opportunity to consider the interface between multilingualism and speech-language competence on children’s academic and social-emotional outcomes and to determine whether differences between groups at 4 to 5 years persist, deepen, or disappear with time and schooling. Four distinct groups were identified from the Kindergarten cohort of the Longitudinal Study of Australian Children (LSAC) (1) English-only + typical speech and language (n = 2,012); (2) multilingual + typical speech and language (n = 476); (3) English-only + speech and language concern (n = 643); and (4) multilingual + speech and language concern (n = 109). Two analytic approaches were used to compare these groups. First, a matched case-control design was used to randomly match multilingual children with speech and language concern (group 4, n = 109) to children in groups 1, 2, and 3 on gender, age, and family socio-economic position in a cross-sectional comparison of vocabulary, school readiness, and behavioral adjustment. Next, analyses were applied to the whole sample to determine longitudinal effects of group membership on teachers’ ratings of literacy, numeracy, and behavioral adjustment at ages 6 to 7 and 8 to 9 years. At 4 to 5 years, multilingual children with speech and language concern did equally well or better than English-only children (with or without speech and language concern) on school readiness tests but performed more poorly on measures of English vocabulary and behavior. At ages 6 to 7 and 8 to 9, the early gap between English-only and multilingual children had closed. Multilingualism was not found to contribute to differences in literacy and numeracy outcomes at school; instead, outcomes were more related to concerns about children’s speech and language in early childhood. There were no group differences for socio-emotional outcomes. Early evidence for the combined risks of multilingualism plus speech and language concern was not upheld into the school years.

“Let’s see if you can see me”: Making connections with Google Earth™ in a preschool classroom

Bringing a social interaction approach to children’s geographies to investigate how children accomplish place in everyday lives, we draw on ethnomethodological and conversation analytic approaches that recognize children’s competence to manipulate their social and digital worlds. An investigation of preschool-aged children engaged with Google Earth™ shows how they both claimed and displayed technological understandings and practices such as maneuvering the mouse and screen, and referenced place through relationships with local landmarks and familiar settings such as their school. At times, the children’s competing agendas required orientation to each other’s ideas, and shared negotiation to come to resolution. A focus on children’s use of digital technologies as they make meaning of the world around them makes possible new understandings of place within the geographies of childhood and education.

Identifying work related injuries : comparison of methods for interrogating text fields

Background: Work-related injuries in Australia are estimated to cost around $57.5 billion annually, however there are currently insufficient surveillance data available to support an evidence-based public health response. Emergency departments (ED) in Australia are a potential source of information on work-related injuries though most ED’s do not have an ‘Activity Code’ to identify work-related cases with information about the presenting problem recorded in a short free text field. This study compared methods for interrogating text fields for identifying work-related injuries presenting at emergency departments to inform approaches to surveillance of work-related injury.---------- Methods: Three approaches were used to interrogate an injury description text field to classify cases as work-related: keyword search, index search, and content analytic text mining. Sensitivity and specificity were examined by comparing cases flagged by each approach to cases coded with an Activity code during triage. Methods to improve the sensitivity and/or specificity of each approach were explored by adjusting the classification techniques within each broad approach.---------- Results: The basic keyword search detected 58% of cases (Specificity 0.99), an index search detected 62% of cases (Specificity 0.87), and the content analytic text mining (using adjusted probabilities) approach detected 77% of cases (Specificity 0.95).---------- Conclusions The findings of this study provide strong support for continued development of text searching methods to obtain information from routine emergency department data, to improve the capacity for comprehensive injury surveillance.