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Double-loop learning entails the modification of goals or decision-making rules in the light of experience. In double-loop learning, individuals or organizations not only correct errors based on existing rules or assumptions, but also question and modify the underlying assumptions, goals, and norms that led to those actions. The first loop uses the goals or decision-making rules, the second loop enables their modification, hence "double-loop". Double-loop learning recognises that the way a problem is defined and solved can be a source of the problem. This type of learning can be useful in organizational learning since it can drive creativity and innovation, going beyond adapting to change to anticipating or being ahead of change.
Read more on Wikipedia →This topic has recently gained attention due to increased public interest. Search activity and Wikipedia pageviews suggest growing global engagement.
Search interest data over the past 12 months indicates that this topic periodically attracts global attention. Sudden spikes often correlate with major news events, public statements, or geopolitical developments.