Education, Globalisation and the Role of Comparative Education

Comparative education has traditionally meant the study of national education systems. But how far is this approach valid today? Doesn’t the ‘decline’ of the nation state make national systems obsolete? Isn’t the very idea of a ‘system’ anachronistic in a world of market triumphalism and global disorganization? The purpose of this article is to explore how globalisation is changing education and the implication of this for comparative study. Why study education systems and why study national education systems in particular? What else should comparativists study, and how? What defines the field of comparative education? These questions are approached first historically and secondly methodologically

On the taxonomic resolution of pollen and spore records of Earth’s vegetation

Premise of research. Pollen and spores (sporomorphs) are a valuable record of plant life and have provided information on subjects ranging from the nature and timing of evolutionary events to the relationship between vegetation and climate. However, sporomorphs can be morphologically similar at the species, genus, or family level. Studies of extinct plant groups in pre-Quaternary time often include dispersed sporomorph taxa whose parent plant is known only to the class level. Consequently, sporomorph records of vegetation suffer from limited taxonomic resolution and typically record information about plant life at a taxonomic rank above species.Methodology. In this article, we review the causes of low taxonomic resolution, highlight examples where this has hampered the study of vegetation, and discuss the strategies researchers have developed to overcome the low taxonomic resolution of the sporomorph record. Based on this review, we offer our views on how greater taxonomic precision might be attained in future work. Pivotal results. Low taxonomic resolution results from a combination of several factors, including inadequate reference collections, the absence of sporomorphs in situ in fossilized reproductive structures, and damage following fossilization. A primary cause is the difficulty of accurately describing the very small morphological differences between species using descriptive terminology, which results in palynologists classifying sporomorphs conservatively at the genus or family level to ensure that classifications are reproducible between samples and between researchers. Conclusions. In our view, the most promising approach to the problem of low taxonomic resolution is a combination of high-resolution imaging and computational image analysis. In particular, we encourage palynologists to explore the utility of microscopy techniques that aim to recover morphological information from below the diffraction limit of light and to employ computational image analyses to consistently quantify small morphological differences between species

Examining characteristics of teacher feedback in organizing written texts

This study aimed to examine teachers' written feedback on student texts in terms of dimensions focused and qualitative characteristics. The study was conducted using content analysis technique that is one of the qualitative research methods. The participants were 28 Turkish language teachers working at middle schools in Nigde in the 2013-2014 school year. In the data gathering process, 6th graders were firstly asked to write sample texts of 250- 300-word length. Four of these texts were then selected by three experts. The participant teachers were asked to provide feedback on the four selected texts. The written feedback provided by the teachers were analysed by the researcher and two experts in terms of dimensions focused and quality. As a result of the analysis, a total of 750 pieces of feedback provided by 28 teachers for four different student texts were mostly about the dimension of spelling and punctuation. On the other hand, in terms of quality, 67,1% of the feedback was evaluative

Qualitative System Identification from Imperfect Data

Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to mean the identification of quantitative models expressed as differential equations. Quantitative modelling works best when the structure of the model (i.e., the form of the equations) is known; and the primary concern is one of estimating the values of the parameters in the model. For complex biological systems, the model-structure is rarely known and the modeler has to deal with both model-identification and parameter-estimation. In this paper we are concerned with providing automated assistance to the first of these problems. Specifically, we examine the identification by machine of the structural relationships between experimentally observed variables. These relationship will be expressed in the form of qualitative abstractions of a quantitative model. Such qualitative models may not only provide clues to the precise quantitative model, but also assist in understanding the essence of that model. Our position in this paper is that background knowledge incorporating system modelling principles can be used to constrain effectively the set of good qualitative models. Utilising the model-identification framework provided by Inductive Logic Programming (ILP) we present empirical support for this position using a series of increasingly complex artificial datasets. The results are obtained with qualitative and quantitative data subject to varying amounts of noise and different degrees of sparsity. The results also point to the presence of a set of qualitative states, which we term kernel subsets, that may be necessary for a qualitative model-learner to learn correct models. We demonstrate scalability of the method to biological system modelling by identification of the glycolysis metabolic pathway from data