Job performance has been shown to be a function of both declarative knowledge (i.e., knowledge of facts, rules, etc.) and procedural knowledge (i.e., knowledge of the steps involved in actually performing a task, such as solving a particular type of problem or analyzing a particular issue). In addition, it has been shown that properly structured performance support tools (i.e., checklists, flowcharts, decision matrices, etc.) can mitigate knowledge deficiencies and enhance job performance.
Notwithstanding extensive research demonstrating the existence of two types of knowledge and the fact that both influence task performance, traditional formal training has focused almost exclusively on declarative knowledge, leaving procedural knowledge to be learned "on-the-job". Moreover, training participants have frequently viewed training and on-the-job task performance as discrete, as opposed to interrelated, activities.
The LogicFlow training and performance support model has been designed to address these deficiencies inherent in traditional approaches to training by:
Organizing instructional materials in a manner that facilitates participants learning not only the applicable rules (declarative knowledge) but, also, how to apply such rules to solve real-world problems (procedural knowledge); and
Designing courses in a manner that facilitates their use as a performance support tool that can be readily accessed on a continuous basis to improve day-to-day job performance.