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1.
The effect of bilingualism on the processing of scalar implicatures
ANNE REBOUL, Arthur Stepanov, Jacques Jayez, Jean-Baptiste van der Henst, Viviane Déprez, Anne Cheylus, Ludivine Dupuy, Penka Stateva, Sara Andreetta, 2016, published scientific conference contribution abstract

Abstract: Scalar implicatures have been extensively investigated in the experimental literature, but almost exclusively in monolingual speakers. Very little research has been conducted on the pragmatic abilities of multilingual populations, including early bilinguals to L2 learners, a gap the current study aims to remedy.
Found in: ključnih besedah
Summary of found: ...L2 learning and early bilingualism, comprehension of scalar implicatures...
Keywords: L2 learning and early bilingualism, comprehension of scalar implicatures
Published: 22.04.2016; Views: 2279; Downloads: 0
.pdf Fulltext (227,83 KB)

2.
Does Grammatical Structure Accelerate Number Word Learning? Evidence from Learners of Dual and Non-Dual Dialects of Slovenian
Franc Marušič, Rok Žaucer, Vesna Plesničar, Tina Razboršek, Jessica Sullivan, David Barner, 2016, original scientific article

Abstract: How does linguistic structure affect children’s acquisition of early number word meanings? Previous studies have tested this question by comparing how children learning languages with different grammatical representations of number learn the meanings of labels for small numbers, like 1, 2, and 3. For example, children who acquire a language with singular-plural marking, like English, are faster to learn the word for 1 than children learning a language that lacks the singular-plural distinction, perhaps because the word for 1 is always used in singular contexts, highlighting its meaning. These studies are problematic, however, because reported differences in number word learning may be due to unmeasured cross-cultural differences rather than specific linguistic differences. To address this problem, we investigated number word learning in four groups of children from a single culture who spoke different dialects of the same language that differed chiefly with respect to how they grammatically mark number. We found that learning a dialect which features “dual” morphology (marking of pairs) accelerated children’s acquisition of the number word two relative to learning a “non-dual” dialect of the same language.
Found in: ključnih besedah
Keywords: števila, številke, slovnično število, dvojina, narečja, usvajanje, učenje, slovenščina, angleščina, numbers, grammatical number, dual, dialects, acquisition, learning, Slovenian, English
Published: 10.08.2016; Views: 2248; Downloads: 165
.pdf Fulltext (1,38 MB)

3.
The Learning Chain of Excerpts Didactic Model
Zoran Božič, 2017, original scientific article

Abstract: The paper presents a case study of the interpretation of a medium-length narrative text in pre-college settings based on a learning chain of excerpts model supplemented with questions for close reading. This didactic approach had already become widespread in Slovenia prior to WW II, and achieved a more systematic realization with the publication of two workbooks for home reading: Zlati poljub (The golden kiss; Božič 1998) and Poljub zlata (The kiss of gold; Božič 1998) in 1998. After almost two decades of its application in schools, it is time for a more detailed assessment of the approach and its usefulness, which has been carried out by also comparing two learning chains that were created for the well-known novella “Tantadruj” by Kosmač. The paper concludes with a learning chain that connects Tantadruj’s search for happiness with the narrator’s search for creative inspiration.
Found in: ključnih besedah
Keywords: Ciril Kosmač, learning chain, close reading, home reading, literature didactics
Published: 13.02.2017; Views: 1834; Downloads: 195
.pdf Fulltext (271,08 KB)

4.
Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms
Johannes Fuernkranz, Nada Lavrač, Dragan Gamberger, 2010, independent scientific component part or a chapter in a monograph

Abstract: Features are the main rule building blocks for rule learning algorithms. They can be simple tests for attribute values or complex logical terms representing available domain knowledge. In contrast to common practice in classification rule learning, we argue that separation of the feature construction and rule construction processes has theoretical and practical justification. Explicit usage of features enables a unifying framework of both propositional and relational rule learning and we present and analyze procedures for feature construction in both types of domains. It is demonstrated that the presented procedure for constructing a set of simple features has the property that the resulting set enables construction of complete and consistent rules whenever it is possible, and that the set does not include obviously irrelevant features. Additionally, the concept of feature relevancy is important for the effectiveness of rule learning. It this work, we illustrate the concept in the coverage space and prove that the relative relevancy has the quality-preserving property in respect to the resulting rules. Moreover, we show that the transformation from the attribute to the feature space enables a novel, theoretically justified way of handling unknown attribute values. The same approach enables that estimated imprecision of continuous attributes can be taken into account, resulting in construction of robust features in respect to this imprecision.
Found in: ključnih besedah
Keywords: Machine learning, Feature construction, Rule learning, Unknown attribute values
Published: 14.07.2017; Views: 1649; Downloads: 0
.pdf Fulltext (365,76 KB)

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The E-learning System for Teaching Bridging Mathematics Course to Applied Degree Studies
Donatella Gubiani, Irina Cristea, Maria Antonietta Lepellere, 2019, independent scientific component part or a chapter in a monograph

Found in: ključnih besedah
Keywords: E-learning, bridging math course, moodle platform
Published: 15.10.2018; Views: 783; Downloads: 0
.pdf Fulltext (577,50 KB)

8.
How the lack of negative input affects processing of complex syntax by advanced second language learners
Artur Stepanov, invited lecture at foreign university

Found in: ključnih besedah
Summary of found: ...Second language learning, ultimate attainment, syntax, sentence processing, negative evidence...
Keywords: Second language learning, ultimate attainment, syntax, sentence processing, negative evidence
Published: 18.01.2019; Views: 883; Downloads: 0
.pdf Fulltext (205,89 KB)

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10.
Mass composition of ultra-high energy cosmic rays at the Pierre Auger Observatory
Gašper Kukec Mezek, 2019, doctoral dissertation

Abstract: Cosmic rays with energies above 10^18 eV, usually referred to as ultra-high energy cosmic rays (UHECR), have been a mystery from the moment they have been discovered. Although we have now more information on their extragalactic origin, their direct sources still remain hidden due to deviations caused by galactic magnetic fields. Another mystery, apart from their production sites, is their nature. Their mass composition, still uncertain at these energies, would give us a better understanding on their production, acceleration, propagation and capacity to produce extensive air showers in the Earth's atmosphere. Mass composition studies of UHECR try to determine their nature from the difference in development of their extensive air showers. In this work, observational parameters from the hybrid detection system of the Pierre Auger Observatory are used in a multivariate analysis to obtain the mass composition of UHECR. The multivariate analysis (MVA) approach combines a number of mass composition sensitive variables and tries to improve the separation between different UHECR particle masses. Simulated distributions of different primary particles are fitted to measured observable distributions in order to determine individual elemental fractions of the composition. When including observables from the surface detector, we find a discrepancy in the estimated mass composition between a mixed simulation sample and the Pierre Auger data. Our analysis results from the Pierre Auger data are to a great degree independent on hadronic interaction models. Although they differ at higher primary masses, the different models are more consistent, when combining fractions of oxygen and iron. Compared to previously published results, the systematic uncertainty from hadronic interaction models is roughly four times smaller. Our analysis reports a predominantly heavy composition of UHECR, with more than a 50% fraction of oxygen and iron at low energies. The composition is then becoming heavier with increasing energy, with a fraction of oxygen and iron above 80% at the highest energies.
Found in: ključnih besedah
Summary of found: ...showers, mass composition, Pierre Auger Observatory, machine learning, multivariate analysis...
Keywords: astroparticle physics, ultra-high energy cosmic rays, extensive air showers, mass composition, Pierre Auger Observatory, machine learning, multivariate analysis
Published: 03.04.2019; Views: 1086; Downloads: 62
.pdf Fulltext (17,53 MB)

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