Employee Deep Learning and Surface Learning in the Workplace

Learning is crucial for employees’ self-improvement and work success. While some forms of learning are effective in promoting expected results, certain types of learning might be inefficient and less helpful, draining organizational resources and hindering performance improvement. In three studies, we propose and differentiate two workplace learning strategies—deep learning and surface learning that employees may adopt in job-related learning. We theorize that deep learning focuses on truly comprehending knowledge, whereas surface learning merely focuses on memorizing and reproducing knowledge. Given such difference, we hypothesize that only deep learning, instead of surface learning, is effective in enhancing employees’ cognitive flexibility and subsequent creativity, especially when completing complex tasks. We also propose that deep learning tend to be triggered by learning-related job demands, while surface learning is likely to be induced by performing-related job demands. In Study 1, using four independent samples with qualitative and quantitative data, we developed the conceptualizations and measures of deep and surface learning. In Study 2, we examined the consequences and antecedents of deep and surface learning in an on-site training context. Results showed that compared to surface learning, deep learning had a stronger positive effect on employees’ cognitive flexibility and subsequent creativity. Learning demands were positively associated with deep learning, whereas performing demands were positively associated with surface learning. We replicated these findings in Study 3, a three-wave, multi-source survey conducted in a general field context. Additionally, Study 3 also found that the advantages of deep learning became more salient in complex (vs. simple) tasks.