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ACUP Seminar : “Faculty at the Catalan public universities. Retributive system and mobility”

International mobility of university staff – trends, opportunities and caveats Irina Ferencz, ACA Policy Officer. ACUP Seminar : “Faculty at the Catalan public universities. Retributive system and mobility”. Outline. Background considerations Why staff mobility?

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ACUP Seminar : “Faculty at the Catalan public universities. Retributive system and mobility”

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  1. International mobility of university staff – trends, opportunities and caveats Irina Ferencz, ACA Policy Officer ACUP Seminar : “Faculty at the Catalan public universities. Retributive system and mobility”

  2. Outline • Background considerations • Why staff mobility? • Who is “staff”? Terminological caveats • Who is “mobile”? Terminological caveats • The patchy picture of staff mobility (some data collection examples) • Routes for more and better data collection • What could universities do… • My presentation – inevitably show what we don’t know about staff mobility rather than what we safely know • Based on article by Ulrich Teichler, “Academic staff mobility” in Teichler, U., Ferencz, I. & Wächter, B. (2011) Mapping mobility in European higher education, Vol. I, Doc&Mat, DAAD, Bonn.

  3. 1.Background considerations • Staff mobility – less of a policy priority than student mobility, because of: • smaller numbers (in absolute terms) • not yet “the normal option” for staff • not part of strategic efforts (in general) – an “individual matter” • internationalisation – traditionally related to students (alone) • ambivalent value judgements • weaker knowledge base • just one of many forms of international collaboration

  4. 2. Why staff mobility? 2.1 Internationalisation • Helps internationalisation @ home • A feature of “world-class universities” (cf. Salmi) (talent from abroad) • Part of institutional strategy • Used in performance agreements with governments • Indicator in international rankings

  5. 2. Why staff mobility? 2.2 The multiplier effect (power of example) • Teaching staff mobility → student mobility • Sensible conclusion, but still weak empirical base • Teachers for, but also against mobility – mutual trust problems and partial recognition

  6. 3. Who is “staff”? Terminological caveats • No international, shared understanding of “staff” • Variety of definitions, country and funding-scheme specific, e.g. : • research vs. teaching staff vs. “administrators” • classification by level of experience (Marie Curie Actions) • within universities or also outside? • headcounts vs. full-time equivalent • where put doctoral candidates (staff or students?) • A moving target in Europe*: • 3,1 million R&D personnel (HC) • 2,2 million R&D personnel (FTE) • 1,9 mill. researchers (HC) • 1,3 mill. researchers (FTE) • 1,3 mill. teaching staff *European Commission and UIS data

  7. 4. Who is “mobile”? Terminological caveats • No international, shared understanding of “staff mobility” • No international, comprehensive data set • Variety of forms: • Visits • Sabbaticals • Exchanges • Recruitment of academic staff from abroad • Data collections – mostly national and/or by funding organisation (fellowships and grants) • Still, a standard feature of higher education systems • Longer track record of support at EU level

  8. 5. The patchy picture of staff mobility (data collection e.g.)Examples of European-level data collections – Erasmus Programme Source: European Commission

  9. 5. The patchy picture of staff mobility (data collection e.g.)aExamples of European-level data collections – Marie Skłodowska-Curie Programme Source: European Commission

  10. 6. Routes for more and better data collection Need at least 4 new data systems on: • University staff as such (mobile or not); • Mobility of PhD students and PhD awards (graduates); • Short-term visits, exchanges and sabbaticals (e.g. through CV standardisation as the Diploma Supplement); • Career mobility (European-wide survey).

  11. 7. What could universities do… • Decide on the priorities – which staff mobility? (mobility = a tool for other ends, not an end in itself) • Map relevant data that is already being collected • Link to strategy (stay realistic and put it into context) • Adjust data collection as needed • Monitor and evaluate

  12. Thank you for your attention! Questions? More about ACA: www.aca-secretariat.be irina.ferencz@aca-secretariat.be

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