The ABC of social learning: Affect, behavior, and cognition.

心理学 社会学习 心理信息 认知 认知心理学 感觉 错误 认知科学 透视图(图形) 动物认知 情感(语言学) 社会认知 社会心理学 沟通 神经科学 教育学 梅德林 人工智能 政治学 计算机科学 法学
作者
Thibaud Gruber,Marina Bazhydai,Christine Sievers,Fabrice Clément,Daniel Dukes
出处
期刊:Psychological Review [American Psychological Association]
卷期号:129 (6): 1296-1318 被引量:43
标识
DOI:10.1037/rev0000311
摘要

Debates concerning social learning in the behavioral and the developmental cognitive sciences have largely ignored the literature on social influence in the affective sciences despite having arguably the same object of study. We argue that this is a mistake and that no complete model of social learning can exclude an affective aspect. In addition, we argue that including affect can advance the somewhat stagnant debates concerning the unique characteristics of social learning in humans compared to other animals. We first review the two major bodies of literature in nonhuman animals and human development, highlighting the fact that the former has adopted a behavioral approach while the latter has adopted a cognitive approach, leading to irreconcilable differences. We then introduce a novel framework, affective social learning (ASL), that studies the way we learn about value(s). We show that all three approaches are complementary and focus, respectively, on behavior toward; cognitions concerning; and feelings about objects, events, and people in our environment. All three thus contribute to an affective, behavioral, and cognitive (ABC) story of knowledge transmission: the ABC of social learning. In particular, ASL can provide the backbone of an integrative approach to social learning. We argue that this novel perspective on social learning can allow both evolutionary continuity and ontogenetic development by lowering the cognitive thresholds that appear often too complex for other species and nonverbal infants. Yet, it can also explain some of the major achievements only found in human cultures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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
peggy发布了新的文献求助10
1秒前
Havier完成签到,获得积分10
1秒前
2秒前
水长聿完成签到,获得积分10
3秒前
lulu发布了新的文献求助30
3秒前
h_cl完成签到,获得积分10
3秒前
10 g发布了新的文献求助10
3秒前
4秒前
FashionBoy应助yanfang采纳,获得10
4秒前
今后应助zyj采纳,获得10
4秒前
4秒前
infe完成签到,获得积分10
5秒前
孤独秋白完成签到,获得积分10
5秒前
yc完成签到,获得积分20
5秒前
5秒前
阳光海云完成签到,获得积分10
5秒前
5秒前
OK完成签到,获得积分10
5秒前
6秒前
Eaven完成签到,获得积分10
6秒前
nalanfu完成签到,获得积分10
6秒前
7秒前
传奇3应助稳重安双采纳,获得10
7秒前
一头猪完成签到,获得积分10
7秒前
鱼鱼子完成签到,获得积分20
8秒前
孟宪岗发布了新的文献求助10
8秒前
十八完成签到,获得积分10
8秒前
懵懂的续完成签到 ,获得积分10
8秒前
Chen完成签到,获得积分10
8秒前
李健的小迷弟应助mengjie采纳,获得10
8秒前
aajhajkahna应助学白柒采纳,获得10
9秒前
柒姐应助zsq采纳,获得10
9秒前
9秒前
10秒前
10秒前
yc发布了新的文献求助10
10秒前
11秒前
雷小仙儿完成签到,获得积分10
11秒前
11秒前
11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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Les chinois de jakarta: temples et vie collective 500
The fast track to determining transfer functions of linear circuits: The student guide 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7628184
求助须知:如何正确求助?哪些是违规求助? 9202607
关于积分的说明 19731862
捐赠科研通 7197894
什么是DOI,文献DOI怎么找? 3273933
关于科研通互助平台的介绍 2436244
邀请新用户注册赠送积分活动 2270126