Psychological Distance Reduces Literal Imitation: Evidence From an Imitation-Learning Paradigm

被引:25
|
作者
Hansen, Jochim [1 ]
Alves, Hans [2 ]
Trope, Yaacov [3 ]
机构
[1] Salzburg Univ, Dept Psychol, Hellbrunner Str 34, A-5020 Salzburg, Austria
[2] Univ Cologne, Social Cognit Ctr Cologne, Cologne, Germany
[3] NYU, Dept Psychol, New York, NY 10003 USA
基金
美国国家科学基金会; 瑞士国家科学基金会; 奥地利科学基金会;
关键词
imitation; emulation; psychological distance; construal level; ACTION IDENTIFICATION; PERCEPTION; FUTURE; BEHAVIOR; CHILDREN; MODELS;
D O I
10.1037/xhp0000150
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
The present experiments tested the hypothesis that observers engage in more literal imitation of a model when the model is psychologically near to (vs. distant from) the observer. Participants learned to fold a dog out of towels by watching a model performing this task. Temporal (Experiment 1) and spatial (Experiment 2) distance from the model were manipulated. As predicted, participants copied more of the model's specific movements when the model was near (vs. distant). Experiment 3 replicated this finding with a paper-folding task, suggesting that distance from a model also affects imitation of less complex tasks. Perceived task difficulty, motivation, and the quality of the end product were not affected by distance. We interpret the findings as reflecting different levels of construal of the model's performance: When the model is psychologically distant, social learners focus more on the model's goal and devise their own means for achieving the goal, and as a result show less literal imitation of the model.
引用
收藏
页码:320 / 330
页数:11
相关论文
共 50 条
  • [1] Psychological distance and imitation
    Hansen, Jochim
    Genschow, Oliver
    SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS, 2020, 14 (11)
  • [2] Two Human-Like Imitation-Learning Bots with Probabilistic Behaviors
    Pelling, Chris
    Gardner, Henry
    2019 IEEE CONFERENCE ON GAMES (COG), 2019,
  • [3] Imitation Learning from Observation
    Torabi, Faraz
    THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2019, : 9900 - 9901
  • [4] Conceptual Imitation Learning in a Human-Robot Interaction Paradigm
    Hajimirsadeghi, Hossein
    Ahmadabadi, Majid Nili
    Araabi, Babak Nadjar
    Moradi, Hadi
    ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2012, 3 (02)
  • [5] An imitation from observation approach for dozing distance learning in autonomous bulldozer operation
    You, Ke
    Ding, Lieyun
    Dou, Quanli
    Jiang, Yutian
    Wu, Zhangang
    Zhou, Cheng
    ADVANCED ENGINEERING INFORMATICS, 2022, 54
  • [6] Imitation Learning from Vague Feedback
    Cai, Xin-Qiang
    Zhang, Yu-Jie
    Chiang, Chao-Kai
    Sugiyama, Masashi
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
  • [7] Imitation Learning from Imperfect Demonstration
    Wu, Yueh-Hua
    Charoenphakdee, Nontawat
    Bao, Han
    Tangkaratt, Voot
    Sugiyama, Masashi
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 97, 2019, 97
  • [8] Imitation of counter-goal behavior: The role of psychological distance and level of construal
    Hansen, Jochim
    Michelbach, Johanna
    Stabenow, Manuel
    ACTA PSYCHOLOGICA, 2020, 210
  • [9] Prosodic Similarity - Evidence from an Imitation Study
    Mixdorff, Hansjoerg
    Cole, Jennifer
    Shattuck-Hufnagel, Stefanie
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON SPEECH PROSODY, VOLS I AND II, 2012, : 571 - 574
  • [10] Sequential robot imitation learning from observations
    Tanwani, Ajay Kumar
    Yan, Andy
    Lee, Jonathan
    Calinon, Sylvain
    Goldberg, Ken
    INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2021, 40 (10-11): : 1306 - 1325