Search results
Results From The WOW.Com Content Network
Knowledge-based decision making model [1] Knowledge-Based Decision-Making (KBDM) in management is a decision-making process [2] that uses predetermined criteria to measure and ensure the optimal outcome for a specific topic. KBDM is used to make decisions by establishing a thought process and reasoning behind a decision. [3]
Choosing a research question is an essential element of both quantitative and qualitative research. Investigation will require data collection and analysis, and the methodology for this will vary widely. Good research questions seek to improve knowledge on an important topic, and are usually narrow and specific. [1]
Display questions work best for eliciting short and low-level answers that correspond to the answer already expected by the teacher. Since referential questions serve to request for new information, answers can be subjective and varied based on the students' opinions, judgement and experiences.
Knowledge retention projects are usually introduced in three stages: decision making, planning and implementation. There are differences among researchers on the terms of the stages. For example, Dalkir talks about knowledge capture, sharing and acquisition and Doan et al. introduces initiation, implementation and evaluation.
It further investigates the sources of knowledge, like perception, inference, and testimony, to determine how knowledge is created. Another topic is the extent and limits of knowledge, confronting questions about what people can and cannot know. [2] Other central concepts include belief, truth, justification, evidence, and reason. [3]
The history of scientific method considers changes in the methodology of scientific inquiry, not the history of science itself. The development of rules for scientific reasoning has not been straightforward; scientific method has been the subject of intense and recurring debate throughout the history of science, and eminent natural philosophers and scientists have argued for the primacy of ...
As knowledge-based technology scaled up, the need for larger knowledge bases and for modular knowledge bases that could communicate and integrate with each other became apparent. This gave rise to the discipline of ontology engineering, designing and building large knowledge bases that could be used by multiple projects.
Infallibilism – Knowledge is incompatible with the possibility of being wrong. Fallibilism – Claims can be accepted even though they cannot be conclusively proven or justified. Non-justificationism – Knowledge is produced by attacking claims and refuting them instead of justifying them.