Although digitalization in the workplace is burgeoning, tools are needed to facilitate personalized learning in informal learning settings. Existing knowledge recommendation techniques do not account for dynamic and task-oriented user preferences. The purpose of this paper is to propose a new design of a knowledge recommender system (RS) to fill this research gap and provide guidance for practitioners on how to enhance the effectiveness of workplace learning.
This study employs the design science research approach. A novel hybrid knowledge recommendation technique is proposed. An experiment was carried out in a case company to demonstrate the effectiveness of the proposed system design. Quantitative data were collected to investigate the influence of personalized knowledge service on users’ learning attitude.
The proposed personalized knowledge RS obtained satisfactory user feedback. The results also show that providing personalized knowledge service can positively influence users’ perceived usefulness of learning.
This research highlights the importance of providing digital support for workplace learners. The proposed new knowledge recommendation technique would be useful for practitioners and developers to harness information technology to facilitate workplace learning and effect organization learning strategies.
This study expands the scope of research on RS and workplace learning. This research also draws scholarly attention to the effective utilization of digital techniques, such as a RS, to support user decision making in the workplace.
This paper is © Emerald Publishing. This paper is based on research presented at the International Conference on Information Resources Management, 2018 (https://aisel.aisnet.org/confirm2018/17/). This work was supported by the National Natural Science Foundation of China (71901150, 71971143, 71571120), Guangdong Province Soft Science Research Project 2019, Shenzhen Philosophy and Social Science Research Project (SZ2019D018). Ben Niu and Yuanyue Feng are both corresponding authors of this paper.
Geng, S., Tan, L., Niu, B., Feng, Y. and Chen, L. (2019), "Knowledge recommendation for workplace learning: a system design and evaluation perspective", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-07-2018-0336Download as .RIS
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