Stress associated with the transition from high school to university: The effect of social support and self-efficacy

The present study aimed to evaluate the role of social support and self-efficacy on the level of stress associated with the transition from high school to university. One hundred and eight-five university students who had completed high school in the previous year completed a three-part questionnaire designed to gather information on their levels of self-efficacy, social support, and stress associated with their transition. The results showed that self-efficacy was a significant predictor of stress associated with the transition to university in that higher levels of self-efficacy were associated with lower levels of stress while social support was a non-significant predictor of stress. [Author abstract]

Secondary school support teachers' perception of speech-language pathology services to adolescents

A survey was conducted to investigate secondary school support teachers' perceptions of speech-language pathology services to students experiencing language difficulties. Information was sought regarding support teachers' understanding of language disorder, their experience with students who have language difficulties and their involvement with speech-language pathologists with regard to these students. Support teachers' views on supporting adolescents who are experiencing language difficulties were also sought as well as information regarding their satisfaction with speech-language pathology services to adolescents. Findings indicated variations in support teachers' perceptions, including mixed views regarding how speech-language pathologists should offer assistance to students. The need for support teachers and speech-language pathologists to offer each other professional training was indicated.

Authorship Attribution with Support Vector Machines

In this paper we explore the use of text-mining methods for the identification of the author of a text. We apply the support vector machine (SVM) to this problem, as it is able to cope with half a million of inputs it requires no feature selection and can process the frequency vector of all words of a text. We performed a number of experiments with texts from a German newspaper. With nearly perfect reliability the SVM was able to reject other authors and detected the target author in 60–80% of the cases. In a second experiment, we ignored nouns, verbs and adjectives and replaced them by grammatical tags and bigrams. This resulted in slightly reduced performance. Author detection with SVMs on full word forms was remarkably robust even if the author wrote about different topics.