Acquiring reading and vocabulary in Dutch and English: the effect of concurrent instruction

To investigate the effect of concurrent instruction in Dutch and English on reading acquisition in both languages, 23 pupils were selected from a school with bilingual education, and 23 from a school with education in Dutch only. The pupils had a Dutch majority language background and were comparable with regard to social-economic status (SES). Reading and vocabulary were measured twice within an interval of 1 year in Grade 2 and 3. The bilingual group performed better on most English and some of the Dutch tests. Controlling for general variables and related skills, instruction in English contributed significantly to the prediction of L2 vocabulary and orthographic awareness at the second measurement. As expected, word reading fluency was easier to acquire in Dutch with its relatively transparent orthography in comparison to English with its deep orthography, but the skills intercorrelated highly. With regard to cross-linguistic transfer, orthographic knowledge and reading comprehension in Dutch were positively influenced by bilingual instruction, but there was no indication of generalization to orthographic awareness or knowledge of a language in which no instruction had been given (German). The results of the present study support the assumption that concurrent instruction in Dutch and English has positive effects on the acquisition of L2 English and L1 Dutch

Stealth Assessment in ITS - A Study for Developmental Dyscalculia

Intelligent tutoring systems are adapting the curriculum to the needs of the student. The integration of stealth assessments of student traits into tutoring systems, i.e. the automatic detection of student characteristics has the potential to re?ne this adaptation. We present a pipeline for integrating automatic assessment seamlessly into a tutoring system and apply the method to the case of developmental dyscalculia (DD). The proposed classi?er is based on user inputs only, allowing non-intrusive and unsupervised, universal screening of children. We demonstrate that interaction logs provide enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91% after 11 minutes on average