A Summary Of The Theory-Driven Generation Of Knowledge

Introduction
“Almost all the knowledge required to produce more food than eroding soil is available today – we just need to use that knowledge within a holistic paradigm – managing agriculture holistically, forming the policies that undergird it holistically.” – Allan Savory
Back in the 599-661 CE, Imam Ali first mentioned “Knowledge is power” (Nahj Al-Balagha, Saying 146). Today, we are living in a world where knowledge has become a commodity, thus, knowledge being a form of power has also been exploited. Some services, goods, and information have become instant to obtain because of technology—an applied knowledge. Despite the benefits that people get from the easy access of these things, gaps like the digital divide and social stratifications widened and
Note that this continuum leans on the DIKW Hierarchy which is contested by other scholars. This continuum points to two ways of knowledge generation: Theory-Driven Generation of Knowledge and Data-Driven Generation of Knowledge. Figure 1. The DIKW Continuum adopted from Desouza and Paquette (2011), showing the relationships of some of the knowledge related concepts.
The Theory-Driven Generation of Knowledge is the movement from wisdom to knowledge. Desouza and Paquette (2011) related this to a researcher wanting to start a new research project. Wisdom becomes the starting point with the use of the researcher’s existing knowledge and experiences in formulating a problem to be solved. Intelligence is employed in the stage where the researcher acts in solving the problem—gather and analyze data and information. The researcher formulates new knowledge when he or she has solved the problem. Furthermore, the researcher improves his or her prior knowledge. Figure 2. Theory-Driven Generation of Knowledge is the conversion of knowledge from wisdom (Desouza and Paquette,