Jelovsek F R, Catanzarite V A, Price R D, Stull R E
University of Arkansas for Medical Sciences.
MD Comput. 1990 Mar-Apr;7(2):98-103.
The development of computer-aided instructional (CAI) systems suffers from a lack of a cohesive theory of learning--how do students acquire and store knowledge? From studies of computer systems that learn and tutor, we can infer generic activities that appear to be integral parts of the learning process, such as aggregation, clustering, characterization, and storage for later retrieval. Learning is faster and more efficient if the goal of a task is made explicit. Hints should be given with the correct timing in relation to an objective so that students can advance in their own problem-solving strategies with the prerequisites in mind. The general form of a rule should usually be taught first, followed by exceptions and special instances. We review theories of learning associated with CAI that illustrate the classification of different types of knowledge. Rule-based (if-then) knowledge forms are represented in these theories, as are declarative and causal knowledge structures. Extracting the common themes from different classifications of knowledge may help us create better CAI.
计算机辅助教学（CAI）系统的发展因缺乏连贯的学习理论而受阻——学生是如何获取和存储知识的？通过对学习和辅导计算机系统的研究，我们可以推断出一些似乎是学习过程不可或缺部分的通用活动，比如聚合、聚类、特征描述以及为后续检索而进行的存储。如果任务目标明确，学习会更快且更高效。提示应该在与目标相关的正确时机给出，以便学生在牢记先决条件的情况下推进自己的问题解决策略。规则的一般形式通常应该先教，然后再教例外情况和特殊实例。我们回顾与CAI相关的学习理论，这些理论阐释了不同类型知识的分类。基于规则（如果……那么……）的知识形式以及陈述性和因果性知识结构都在这些理论中有所体现。从不同的知识分类中提取共同主题可能有助于我们创建更好的CAI。
