This article summarizes research on the roles of prior knowledge in learning. Educators often focus on the ideas that they want their audience to have. But research has shown that a learnerÕs prior knowledge often confounds an educatorÕs best efforts to deliver ideas accurately. A large body of findings shows that learning proceeds primarily from prior knowledge, and only secondarily from the p...

Making complex decisions in real world problems often involves assigning values to sets of interdependent variables where an expressive dependency structure among these can influence, or even dictate, what assignments are possible. Commonly used models typically ignore expressive dependencies since the traditional way of incorporating non-local dependencies is inefficient and hence lead to expe...

We describe a modiication to the AdaBoost algorithm that permits the incorporation of prior human knowledge as a means of compensating for a shortage of training data. We give a convergence result for the algorithm. We describe experiments on four datasets showing that prior knowledge can substantially improve performance.

This paper selectively reviews research on the relationship between topic interest and prior knowledge, and discusses the optimal association between these variables. The paper points out that interest has a facilitating impact on learning, and at least part of this effect must be ascribed to prior knowledge. While the interest-knowledge association may account for about 20 percent of the varia...

Although filling the gap in reading comprehension gained momentum with the rise of the top-down approach, Vygotsky’ concept of scaffolding and the dual code  theory provided a strong support for the use of paratext to enhance comprehension. Scaffolding is dependent on other-regulation, one type of which is object-regulation. From this vantage-point, various types of paratext can function as sou...