Cognitive load theory, learning difficulty, and instructional design

互动性 认知负荷 模式(遗传算法) 认知 要素(刑法) 教学设计 计算机科学 认知心理学 人机交互 认知科学 心理学 多媒体 政治学 机器学习 神经科学 法学
作者
John Sweller
出处
期刊:Learning and Instruction [Elsevier BV]
卷期号:4 (4): 295-312 被引量:3413
标识
DOI:10.1016/0959-4752(94)90003-5
摘要

This paper is concerned with some of the factors that determine the difficulty of material that needs to be learned. It is suggested that when considering intellectual activities, schema acquisition and automation are the primary mechanisms of learning. The consequences of cognitive load theory for the structuring of information in order to reduce difficulty by focusing cognitive activity on schema acquisition is briefly summarized. It is pointed out that cognitive load theory deals with learning and problem solving difficulty that is artificial in that it can be manipulated by instructional design. Intrinsic cognitive load in contrast, is constant for a given area because it is a basic component of the material. Intrinsic cognitive load is characterized in terms of element interactivity. The elements of most schemas must be learned simultaneously because they interact and it is the interaction that is critical. If, as in some areas, interactions between many elements must be learned, then intrinsic cognitive load will be high. In contrast, in different areas, if elements can be learned successively rather than simultaneously because they do not interact, intrinsic cognitive load will be low. It is suggested that extraneous cognitive load that interferes with learning only is a problem under conditions of high cognitive load caused by high element interactivity. Under conditions of low element interactivity, re-designing instruction to reduce extraneous cognitive load may have no appreciable consequences. In addition, the concept of element interactivity can be used to explain not only why some material is difficult to learn but also, why it can be difficult to understand. Understanding becomes relevant when high element interactivity material with a naturally high cognitive load must be learned.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Samsara完成签到 ,获得积分10
1秒前
酷波er应助诗谙采纳,获得10
1秒前
2秒前
YYY完成签到,获得积分10
2秒前
PAN完成签到,获得积分10
2秒前
金城武发布了新的文献求助10
2秒前
ex完成签到,获得积分10
2秒前
2秒前
隐形的凡阳完成签到,获得积分10
2秒前
3秒前
3秒前
smile关注了科研通微信公众号
3秒前
huangxin完成签到,获得积分10
4秒前
李似水完成签到 ,获得积分10
4秒前
Giaodv完成签到,获得积分10
4秒前
未寝的怀民完成签到,获得积分10
4秒前
4秒前
hana发布了新的文献求助30
4秒前
akjuly1发布了新的文献求助10
5秒前
穆仰完成签到,获得积分10
5秒前
袋袋发布了新的文献求助10
5秒前
willlow完成签到,获得积分10
5秒前
乐乐应助平淡晓蓝采纳,获得10
6秒前
于富强完成签到,获得积分10
6秒前
7秒前
7秒前
舒服的楷瑞应助Hl516采纳,获得10
7秒前
小王要努力完成签到,获得积分10
8秒前
CipherSage应助踏实的镜子采纳,获得30
9秒前
潦草小狗发布了新的文献求助10
9秒前
破灭圆舞曲完成签到,获得积分10
9秒前
111发布了新的文献求助10
9秒前
valiente发布了新的文献求助10
10秒前
佳loong完成签到,获得积分10
10秒前
11秒前
11秒前
李爱国应助奶油布丁采纳,获得10
11秒前
天真晓博完成签到,获得积分10
12秒前
XXX发布了新的文献求助10
12秒前
怜熙发布了新的文献求助10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7779484
求助须知:如何正确求助?哪些是违规求助? 9319821
关于积分的说明 20373700
捐赠科研通 7367117
什么是DOI,文献DOI怎么找? 3319530
关于科研通互助平台的介绍 2467476
邀请新用户注册赠送积分活动 2335116