Insights into Creating Effective and Efficient Reskilling and Upskilling Measures

Hazel Gruenewald () and Maren Mueller ()
Additional contact information
Hazel Gruenewald: Reutlingen University
Maren Mueller: Baden-Wuerttemberg Cooperative State University

Chapter 5 in Reskilling and Upskilling in a Globalized Economy, 2025, pp 101-133 from Springer

Abstract: Abstract This chapter begins by outlining the distinction between knowledge and learning. To develop precise and targeted reskilling and upskilling measures, it is essential to first examine the psychology of learning in greater detail. Building on this foundation, the chapter explores various learning methods, highlighting learning preferences, learning styles, and learning types to enable personalized and therefore more efficient learning experiences. Learning is then placed in the context of organizational change, and the differences between traditional learning and e-learning are explained. The chapter also examines how artificial intelligence can enhance learning efficiency.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-658-48384-5_5

Ordering information: This item can be ordered from
http://www.springer.com/9783658483845

DOI: 10.1007/978-3-658-48384-5_5

Access Statistics for this chapter

More chapters in Future of Business and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().