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Learning Software-Maintenance Tasks in the Transition Phase of Offshore Outsourcing Projects: Two Learning-Theoretical Perspectives

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Book cover The Dynamics of Global Sourcing. Perspectives and Practices (Global Sourcing 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 130))

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Abstract

The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While job-shadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.

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© 2012 Springer-Verlag Berlin Heidelberg

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Krancher, O., Dibbern, J. (2012). Learning Software-Maintenance Tasks in the Transition Phase of Offshore Outsourcing Projects: Two Learning-Theoretical Perspectives. In: Kotlarsky, J., Oshri, I., Willcocks, L.P. (eds) The Dynamics of Global Sourcing. Perspectives and Practices. Global Sourcing 2012. Lecture Notes in Business Information Processing, vol 130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33920-2_7

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  • DOI: https://doi.org/10.1007/978-3-642-33920-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33919-6

  • Online ISBN: 978-3-642-33920-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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