主办单位:成都体育学院
ISSN 1001-9154 CN 51-1097/G8

成都体育学院学报 ›› 2014, Vol. 40 ›› Issue (5): 30-36.

• 运动项目训练教学理论与实践 • 上一篇    下一篇

国外力量训练研究跨学科知识整合特征

赵丙军   

  1. 聊城大学体育学院, 山东 聊城 252059
  • 收稿日期:2014-01-27 出版日期:2014-05-20 发布日期:2014-06-03
  • 作者简介:赵丙军(1966-), 男, 山东茌平人, 副教授, 博士, 主要研究方向为体育科技情报。
  • 基金资助:
    上海市体育局科研攻关与科技服务课题(综合类)(项目编号:11JT012)

Interdisciplinary Knowledge Integration Features of Foreign Strength Training Research

ZHAO Bing-jun   

  1. Liaocheng University, Liaocheng Shangdong, 25205
  • Received:2014-01-27 Online:2014-05-20 Published:2014-06-03

摘要: 运用文献资料调研、专家咨询、数理统计、共现分析等研究方法, 对国外力量训练研究百年发展历程中的跨学科知识整合特征进行了研究。结果表明:百年来涉足国外力量训练研究的学科仍呈指数式增长, 体育科学、生理学、康复学、营养学等学科的参与度较高;学科间的知识交流网络具有显著的小世界特征, 但各学科间的知识整合总体上并不频繁和畅通, 多为两两学科间的知识交叉与融合;国外力量训练研究历经了单学科研究起步、双学科研究拓展到多学科研究协同共进的过程, 并呈现出较为明显的阶段性特征;新进学科与领域研究相对成熟学科间知识的跨学科整合是国外力量训练研究领域知识创新的重要机制。

关键词: 力量训练, 跨学科, 知识整合, 小世界网络, 共现分析

Abstract: Depending on the methods of literature investigation, expert consultation, mathematical statistics, co-occurrence analysis, the paper researches the features of interdisciplinary knowledge integration of foreign strength training in last 100 years, with the result showing that disciplines related to foreign strength training research have seen exponential growth and among them, sports science, physiology, rehabilitation and nutrition are more involved. The knowledge exchange network between disciplines has witnessed remarkable characteristics of small world, but the interdisciplinary knowledge integration on the whole is not frequent or smooth, with knowledge overlapping and fusion between two disciplines. Foreign researches on strength training began in the sequence of single disciplinary research, double disciplinary research and then multidisciplinary research with obvious phase characters. Interdisciplinary integration of knowledge between new research subjects and relatively mature disciplines is an important knowledge innovation mechanism in the field of foreign strength training research.

Key words: strength training, interdisciplinary, knowledge integration, small world network, co-occurrence analysis

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