Computer-supported reflective learning: how apps can foster reflection at work

Bettina Renner, Gudrun Wesiak, Viktoria Pammer-Schindler, Michael Prilla, Lars Müller, Dalia Morosini, Simone Mora, Nils Faltin and Ulrike Cress

Behaviour and Information Technology, 2020, vol. 39, issue 2, 167-187

Abstract: This paper discusses the potential of ICT to support reflective learning for professionals. We aggregated data collected in 20 field studies with 12 different applications, involving a total of 321 participants. The applications addressed individual reflection as well as collaborative reflection. Such a systematic analysis with different applications used across industry sectors and companies is unique in the current literature on computer-supported reflective learning in the workplace. Primarily, we assessed the reaction to reflection applications and their effectiveness regarding learning, behaviour change, and organisational impact. In addition, we investigated differences with respect to work experience. Results show that users had a positive reaction to the apps and perceived their use to be beneficial for their work by using them. In collaborative reflection an inexperienced employee can benefit from the experiences and perspectives of more experienced (co-)workers. In contrast, individual reflection was more profitable for more experienced workers. Notwithstanding the overall positive results, the actual implementation of reflection applications requires careful adaptation to the specific organisational and situational context, as well as introductory and accompanying measures to assure efficient and beneficial usage of the tools.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2019.1595726 (text/html)
Access to full text is restricted to subscribers.

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:taf:tbitxx:v:39:y:2020:i:2:p:167-187

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2019.1595726

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().