STUDENT LIFE EXPECTATIONS REGARDING THE CAREER DECISION OF DISADVANTAGED STUDENT GROUPS DURING THE COVID-19 PANDEMIC

Author(s):  
Cristina Cîrtiță-Buzoianu ◽  
Venera-Mihaela Cojocariu ◽  
Gabriel Mares
2018 ◽  
Vol 17 (4) ◽  
pp. 224-237 ◽  
Author(s):  
David Patton

Purpose Whilst drug use appears to be common amongst university students, the purpose of this paper is to move beyond mere drug prevalence, and use the six dimensions of normalisation to better understand the role and place drugs play in the lives of university students. Design/methodology/approach In total, 512 students completed a student lifestyle survey. Findings A differentiated normalisation is occurring amongst different student groups; the social supply of drugs is common, and some users are “drifting” into supply roles yet such acts are neutralised. Students are “drug literate” and have to navigate drugs, and their consumption, availability and marketing, as part of their everyday student life. Practical implications Student drug use is not homogenous and very little is known about the nuances and diversity of their use/non-use beyond prevalence data. Qualitative studies are needed to better understand the processes of differentiated normalisation and social supply. Originality/value This is the first study in the UK to use the six dimensions of normalisation amongst a sample of university students.


Methodology ◽  
2007 ◽  
Vol 3 (4) ◽  
pp. 149-159 ◽  
Author(s):  
Oliver Lüdtke ◽  
Alexander Robitzsch ◽  
Ulrich Trautwein ◽  
Frauke Kreuter ◽  
Jan Marten Ihme

Abstract. In large-scale educational assessments such as the Third International Mathematics and Sciences Study (TIMSS) or the Program for International Student Assessment (PISA), sizeable numbers of test administrators (TAs) are needed to conduct the assessment sessions in the participating schools. TA training sessions are run and administration manuals are compiled with the aim of ensuring standardized, comparable, assessment situations in all student groups. To date, however, there has been no empirical investigation of the effectiveness of these standardizing efforts. In the present article, we probe for systematic TA effects on mathematics achievement and sample attrition in a student achievement study. Multilevel analyses for cross-classified data using Markov Chain Monte Carlo (MCMC) procedures were performed to separate the variance that can be attributed to differences between schools from the variance associated with TAs. After controlling for school effects, only a very small, nonsignificant proportion of the variance in mathematics scores and response behavior was attributable to the TAs (< 1%). We discuss practical implications of these findings for the deployment of TAs in educational assessments.


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