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Autor/inZoellner, Don
TitelVET Market Prognostications Two Decades Later: Using 'Big Data' to Compare Omens with Outcomes
QuelleIn: Journal of Vocational Education and Training, 74 (2022) 3, S.494-512 (19 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Zoellner, Don)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1363-6820
DOI10.1080/13636820.2020.1786438
SchlagwörterVocational Education; Educational Research; Educational Trends; Commercialization; Public Policy; Foreign Countries; Enrollment Trends; Trend Analysis; Australia
AbstractPublishing the results of thoughtfully designed research projects allows contemporary investigators to revisit the findings years later. The willingness of academics to make specific predictions about the impact of introducing user-choice principles into a state vocational education and training market has enabled comparisons to be drawn using extensive statistical collections. These data sets do not cover each of the forecasts; for example, employer reactions to increased marketisation can only be inferred. However, extensive information has been recorded on the training provider and student responses. The jurisdiction under study has a long history of centralised government decision-making and bureaucratic regulatory control; which allows for a substantial level of confidence in the causal relationship between public policy implementation and outcomes observed in the vocational education and training market. By making data-driven comparisons between what was hypothesised and the results over a long period of time, it is re-affirmed that good research is relevant and can assist governments in achieving their intended public policy priorities. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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