The classroom flow and engagement experiences of Western Australian rural and remote secondary school students

This paper commences with a brief examination of non-metropolitan student engagement and participation in schooling. It then describes how student engagement in classroom learning was conceptualised utilising Flow Theory. The key elements in this conception were subsequently used to construct an interview schedule. The characteristics of the sample of students interviewed are presented and then the data collection procedures are explained. The application of an inductive data analysis technique to these data is explicated. The empirical results are discussed in consideration of the extant literature on student engagement and flow. This study was part of a much larger mixed-methods investigation funded by the Australian Research Council from 2008 to 2011 and concluded in 2012. It was conducted in Western Australian public schools with the support of the, then, Department of Education and Training

Semantic Invariance and Variance in Linguistic Analyses

This paper was written for a symposium on invariance (The Invariance Condition in Educational Research: Invariance Between Groups, Instruments, Language and Across Time). The philosophical genre of hermeneutical phenomenology provided a perspective for examination of invariance in scientific research and linguistic analysis that applies the Natural Semantic Metalanguage (NSM) Approach. In both instances, a medium (theory and instruments) is constructed a priori on the assumption it will display invariance when taken out of the laboratory. The real world then inscribes the medium in accordance with qualitative differences (variance) in the phenomenon of interest. In this study, the medium is the Natural Semantic Metalanguage Approach and the phenomenon of interest are three Japanese ʻhearsayʼ markers - rashii, sooda and tte. The NSM Approach uses a set of 64 universal and culture-independent concepts. These are termed ʻsemantic primesʼ because they represent innate meanings that are fundamental to human thought. They are indefinable, their meanings so basic that they cannot be broken down any further.The raw data for this study are the meanings of rashii, sooda and tte as expressed in a corpus of eight novels written in Japanese and with English translations. Using the NSM Approachʼs syntactic rules, a combination of primes was used to define each marker. Reductive paraphrases that are simpler than the original words were identified by a process of semantic reduction. The resulting definitions comprised discrete components that defined the respective markers. This NSM Approach analysis illustrates how explicating the differences between similar terms in one language and across more than one language, needs a common medium with specific attributes. The medium requires that meaning be reduced to a level beyond which further simplification is not possible. This medium also limits the number of semantic primes to 64. It is the invariant nature of the NSM Approach that provides definitions that can accurately and consistently reveal qualitative differences between the terms - linguistic variance

Senior secondary school students' risk of disengagement from further education, employment or training

In Western Australia, the school leaving age was mandated to rise from 15 Years to 16 Years in 2007. This policy has resulted in a large number of students remaining at school and entering the senior years of schooling. Of interest in this study were the students who would not normally have remained at school, particularly those who may have disengaged from schooling. Data were obtained from school and education district office student services staff on 23 attributes of 5313 Year Ten students identified at risk of not completing schooling, future training or entering employment. The data were dichotomous and the multi-variate nature of these data rendered it unsuitable for Rasch Model analysis but amenable to interpretation using Binomial Logistic Regression. Two models were tested with each containing a different dependent variable and common independent variables. The dependent variables for the respective models were: Model 1 - Student Risk of Disengagement; and Model 2 - Student Severe Risk of Disengagement. The study identified particular student attributes perceived by school and district office student services staff that statistically predicted two levels of disengagement with schooling, future training or future employment

Positive change and scholastic education

In this contribution the authors will explore the relationship between the school learning environment and positive psychological experience and theory. Specific attention will be addressed to flow, classroom experiences and optimal learning environments reported by scholars of education. The research reported in this chapter examined associations between flow and characteristics of both students and learning environments in secondary school classrooms. The theoretical bases of related lines of inquiry in Australia and the USA were derived from flow theory. The research methodology was systematic phenomenology in which targeted empirical questions were answered by the application of empirical tools and statistical analyses. The research shows the importance of positive relationships, intrinsic motivation, emotional support, relational support, positive self-esteem and self-concept for promoting flow and student engagement in the classroom. The application of meta-cognitive strategies such as planning, strategizing, provision of feedback, high expectations and mastery experiences were also revealed as essential facilitators of flow in learning environments

Measuring children's perceptions of their use of the Internet: A rasch analysis

Measuring children’s use of emerging technologies is prerequisite to determining the effect of such use on children’s health, development and learning. The Ecological Techno-Microsystem provides a theoretical foundation upon which to select test items appropriate to the measurement of children’s self-reported use of the internet across home, school and community contexts. A 15 item rating scale was developed which included five items across the three environments, for example: 1) I use the internet at home; 2) I use email at school; 3) I instant message at home; 4) At home, I use the internet to play games; 5) I visit websites when I am at somebody else’s house. Ninety children rated each of the 15 items on a four-category response scale. Individual item fit statistics confirmed that data from all 15 items fitted the model well. Differential Item Functioning, consistent with empirical evidence, suggested gender differences in patterns of internet use during childhood. Rasch analysis (i.e., Item Map) confirmed that children with the highest self-reported internet use scores on the 15 item rating scale affirmed the most difficult items, that is, the items to which the that fewest children responded in the affirmative

Parent Views of Involvement in their Child's Education: A Rasch model analysis

The theoretical basis for the study was the assumption that parental involvement in a child's education is an important aspect of school culture and that school renewal efforts intended to change the prevailing culture need to take into account the role of parents. Data (N=1,672) from administration of a 40-item rating scale instrument designed to elicit parent views of their involvement in their child's education were analysed using the Rasch model. The analyses were used to test the construct validity of an hypothesised model of parental involvement and the capacity of the instrument to measure the hypothesised components. The components were: Child's view of the importance of schooling, desire to learn, and achievement and engagement; the school's focus on children, learning and on education generally; and provision of information from teachers, teachers' commitment to working with parents, and parent confidence in communicating with the teacher. The instrument was shown to be eliciting data that did not fit the original theoretical model and in cognisance of the need for content validity and accurate measurement, the instrument was refined. Data from the refined instrument were then analysed to produce measures of different aspects of parental involvement as perceived by the parent respondents

A peptide mimic of the chemotaxis inhibitory protein of Staphylococcus aureus: towards the development of novel anti-inflammatory compounds

Complement factor C5a is one of the most powerful pro-inflammatory agents involved in recruitment of leukocytes, activation of phagocytes and other inflammatory responses. C5a triggers inflammatory responses by binding to its G-protein-coupled C5a-receptor (C5aR). Excessive or erroneous activation of the C5aR has been implicated in numerous inflammatory diseases. The C5aR is therefore a key target in the development of specific anti-inflammatory compounds. A very potent natural inhibitor of the C5aR is the 121-residue chemotaxis inhibitory protein of Staphylococcus aureus (CHIPS). Although CHIPS effectively blocks C5aR activation by binding tightly to its extra-cellular N terminus, it is not suitable as a potential anti-inflammatory drug due to its immunogenic properties. As a first step in the development of an improved CHIPS mimic, we designed and synthesized a substantially shorter 50-residue adapted peptide, designated CHOPS. This peptide included all residues important for receptor binding as based on the recent structure of CHIPS in complex with the C5aR N terminus. Using isothermal titration calorimetry we demonstrate that CHOPS has micromolar affinity for a model peptide comprising residues 7–28 of the C5aR N terminus including two O-sulfated tyrosine residues at positions 11 and 14. CD and NMR spectroscopy showed that CHOPS is unstructured free in solution. Upon addition of the doubly sulfated model peptide, however, the NMR and CD spectra reveal the formation of structural elements in CHOPS reminiscent of native CHIPS

Rough sets for mining educational data

While educational data are typically analyzed with statistical software, data mining techniques are increasingly appropriate in revealing complex relationships among multiple variables in large amounts of data. We experimented with the rough set method in conjunction with statistical analysis to identify patterns in, and thereby extract meaning from, complex educational data. Results establish the benefits of combining rough set decision making with stochastic analysis in mining exceedingly complex and difficult to interpret educational data sets