摘要
综合十年的研究,作者描述了意义学习的一种分类办法。最有意义的学习结果是解决问题。在这种分类法中,四种不同的问题解决按层次方式排列。解决问题的先决条件是两种基本的推理技能——类比推理和因果推理,这是解决所有问题的基础。这些推理的形式要求运用概念,以及由概念和关系组成的低阶命题和高阶命题。解决问题的教学应该是让学习者解决问题,对结构相似的问题进行类比式比较,对问题空间中包含的因果关系(高阶命题)进行分析。
Synthesizing a decade of research,the author described a taxonomy of meaningful learning.The most meaningful learning result is solving problems.In such taxonomy,four kinds of different problem-solving are arranged in a hierarchical manner.The prerequisite of solving problems is two kinds of fundamental reasoning skills,namely,analogic reasoning and causal reasoning,the basics of solving all the problems.These reasoning forms require the application of concept,as well as low-order propositions and higher-order propositions consisting of concepts and relations.The teaching of solving problems should require learners to solve problems,compare the problems of structural similarity by analogy,and make an analysis of causal relations(higher-order propositions)in the problem space.
作者
戴维·H.乔纳森
盛群力(译)
David H.Jonassen;SHENG Qunli(College of Information Science and Learning Technology,University of Missouri-Columbia,Columbia,America 65211;College of Education,Zhejiang University,Hangzhou,Zhejiang,China 310028)
出处
《数字教育》
2021年第3期87-92,共6页
Digital Education
基金
国家自然科学基金面上项目“基于智能教学系统的精准教学模式与发生机制研究”(61977057)。
关键词
意义学习
分类学
问题解决
学习迁移
meaningful learning
taxonomy
problem-solving
learning transfer