The phrase "adaptation of knowledge" is correct and usable in written English.
It can be used when discussing the process of modifying or adjusting knowledge to fit new contexts or situations.
Example: "The adaptation of knowledge is essential for effective problem-solving in dynamic environments."
Alternatives: "modification of knowledge" or "adjustment of knowledge".
Yet science and practice express a growing demand for adequate knowledge of adaptation and argue for an adaptation of knowledge as part of adaptive capacity and as a basis for adaptation measures or policies, which are both currently judged as insufficient (Smit et al. 2001).
In the loop's outer ring, the big arrows represent the sequence of the overall process, resulting in an altered adaptive capacity, which can be seen as the goal of the adaptation of knowledge.
It is the temporal capacity of these boundary objects that makes them points of juncture in a widely distributed memory system, enabling project-based firms to balance preservation and adaptation of knowledge.
By utilizing the dynamic knowledge loop, we were able to unravel the dynamics in knowledge of adaptation and the adaptation of knowledge.
The dynamic knowledge loop enables us to untangle the different steps of inter- and transdisciplinary cooperation, leading to a successive adaptation of knowledge.
Historical studies have shown that, in many instances, the presence of skilled and knowledgeable individuals is the most important element in the successful adoption and adaptation of knowledge and technology from outside a culture.
Maroon knowledge can thus be seen as a mixture of knowledge from cultural transmission (from one generation to the other) and adaptations of knowledge from external influences.
A shift to the skill of self-acquiring knowledge via information technology had widely changed the preferences and adaptation modes of knowledge acquirements of our 21st century learners.
For example, one might predict and then examine if tacit knowledge can support the contextual adaptation of explicit knowledge (e.g., research findings) so that they are relevant and applicable to local populations and conditions.
An effective approach is presented in this paper, which uses neural network architectures to both detect the need for adaptation of their knowledge, and adapt it through an efficient adaptation procedure.
Adoption must rely not only on incorporation of the methodology, but acceptance or adaptation of the knowledge content of CDS involving at least two of the three life cycle processes.
