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Liontou T.,Greek Ministry of Education
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

The purpose of the present study was to delineate a range of linguistic features that characterize the English reading texts used at the B2 (Independent User) and C1 (Advanced User) level of the Greek State Certificate of English Language Proficiency (KPG) exams in order to better define text complexity per level of competence. The main outcome of the research was the L.A.S.T. Text Difficulty Index that makes possible the automatic classification of B2 and C1 English reading texts based on four in-depth linguistic features, i.e. lexical density, syntactic structure similarity, tokens per word family and academic vocabulary. Given that the predictive accuracy of the formula has reached 80% on a new set of reading comprehension texts with 32 out of the 40 new texts assigned to similar levels by both raters, the practical usefulness of the index might extend to EFL testers and materials writers, who are in constant need of calibrated texts. © Springer International Publishing Switzerland 2014. Source

Sotiropoulos M.Th.,Greek Ministry of Education
AIP Conference Proceedings

Concepts are defined as couples (O, A) of sets O and A: the object O (a set of none, or one or more elements) is assigned to the set A of these elements' (common) attributes. The objects change according to the sequence of attributes. Only couples of objects and attributes, that is concepts, are adequate for our world. The connections and links we need in databases and multimedia are expressed, naturally, by concepts, since concepts have been proved to dispose the order of a lattice (more complex and rich than linear and hierarchical ones). The lattice can be created by two algebraic operations: "intersection" as the multiplication and "symmetric-difference (!)" as the addition (!). There are, also, two other operations: the "union" and the "complement of a concept". Intersection and union (which cannot play the role neither of the addition nor of the multiplication) express similarities, while the other two operations express dissimilarities. The operation "complement of a concept" expresses the different, the uncommon, the variety. The symmetric-difference of two concepts has been proved to be a "distance" between them (in the mathematical sense!). We must not always see the natural numbers with their linear order (1,2,...,n,n+1,...), but is rather better to give them a more complex structure: the structure of a lattice. We need three operations: "union" of two numbers, "intersection" of two numbers and "complement" of a number. Research conclusion: the conceptual distance of (O1,A 1) and (O2,A2) and is always a prime number! (conceptual means, from the point of view of the characteristic "divisibility" we are examining now and not the Euclidean or any other distance). This is the unique way the prime numbers are generated: not by unions and intersections(which express similarities), but by distances(differences)!... © 2011 American Institute of Physics. Source

Tharouniati E.,Greek Ministry of Education | Houpi M.,Greek Ministry of Education
International Journal of Science, Mathematics and Technology Learning

In this paper we outline the procedure implemented in order to introduce translations of a parabola to tenth grade algebra students. Advantages in applying an interdisciplinary approach with physics are discussed. Promoting an investigative approach in teaching sciences is presented as an indivisible part of building a sense of scientific community in the classroom. The added value of the learning experience created is illustrated through differentiated participation and higher order thinking manifestations analysed and categorised so as to highlight changes in classroom practice. © Common Ground, Eleni Tharouniati, Maria Houpi. Source

Mantas P.,Greek Ministry of Education | Loukeris D.,Greek Ministry of Education
Computers and Education

Computational experiment approach considers modelling as the essential feature of Inquiry Based Science Education (IBSE), where the model and the computer take the place of the "classical" experimental set-up and simulation replaces the experiment (Landau, Pez, & Bordeianu, 2008). Modelling, as a pedagogical tool, involves the model construction, the exploration of model characteristics and the model application to a specific problem, resembling authentic activities of scientists and mathematicians (Herbert, 2003). Recent developments in strategy instruction research suggest that learning in a particular discipline is enhanced by guiding students through the development of content-relevant metacognitive strategies (Wosnitza & Volet, 2009). Problem-solving is a complex process, which involves several cognitive operations such as collecting and selecting information, heuristic strategy and metacognition (De Corte, 2003; Garofalo & Lester, 1985; Schoenfeld, 1994). The purpose of this study was to explore the impact of the Computational Experiment Methodology on learners' cognitive performance, use of modelling indicators and shift of the metacognitive experiences during problem solving using computational models. Sixty prospective primary school teachers volunteered to participate in the study. Students were exposed by the Instructor to a number of computational experiments, while during the course they developed their own models of simulation. The results of the experiment show that the use of the computational experiment approach has a substantial effect on the metacognitive experiences and the use of modelling indicators. © 2013 Elsevier Ltd. All rights reserved. Source

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