The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning

Social software is increasingly being used in higher and further education to support teaching and learning processes. These applications provide students with social and cognitive stimulation and also add to the interaction between students and educators. However, in addition to the benefits the introduction of social software into a course environment can also have adverse implications on students, educators and the education institution as a whole, a phenomenon which has received much less attention in the literature. In this study we explore the various implications of introducing social software into a course environment in order to identify the associated benefits, but also the potential drawbacks. We draw on data from 20 social software initiatives in UK based higher and further education institutions to identify the diverse experiences and concerns of students and educators. The findings are presented in form of a SWOT analysis, which allows us to better understand the otherwise ambiguous implications of social software in terms of its strengths, weaknesses, opportunities and threats. From the analysis we have derived concrete recommendations for the use of social software as a teaching and learning tool.

A túl- és az alulképzés bérhozama 25 európai országban (Returns for over-education and under-education for 25 European countries)

A tanulmányban 25 ország, kétezres évek közepi állapotot tükröző, reprezentatív keresztmetszeti mintáin egyrészt a Duncan-Hoffman-féle modellre támaszkodva megvizsgáljuk, hogy adatbázisunk milyen mértékben tükrözi az illeszkedés bérhozamával foglalkozó irodalom legfontosabb empirikus következtetéseit, másrészt - a Hartog- Oosterbeek-szerzőpáros által javasolt statisztikai próbák segítségével - azt elemezzük, hogy a becslések eredményei alapján mit mondhatunk Mincer emberitőke-, valamint Thurow állásversenymodelljének érvényességéről. Heckman szelekciós torzítást kiküszöbölő becslőfüggvényén alapuló eredményeink jórészt megerősítik az irodalomban vázolt legfontosabb empirikus sajátosságokat, ugyanakkor a statisztikai próbák az országok többségére nézve cáfolják mind az emberi tőke, mind az állásverseny modelljének empirikus érvényességét. / === / Using the Duncan–Hoffman model, the paper estimates returns for educational mismatch using comparable micro data for 25 European countries. The aim is to gauge the extent to which the main empirical regularities shown in other papers on the subject are confirmed by this data base. Based on tests proposed by Hartog and Oosterbeek, the author also considers whether the observed empirical patterns accord with the Mincerian basic human-capital model and Thurow's job-competition model. Heckman's sample-selection estimator shows the returns to be fairly consistent with those found in the literature; the job-competition model and the Mincerian human-capital model can be rejected for most countries.