工业工程

工业工程 ›› 2018, Vol. 21 ›› Issue (5): 93-99.doi: 10.3969/j.issn.1007-7375.2018.05.013

• 教育与培训 • 上一篇    

工业工程应用型创新人才培养模式响应性测度研究

颜伟1,2, 袁清和1,2, 孙佳欣1, 欧龙飞1   

  1. 1. 山东科技大学 矿业与安全工程学院, 山东 青岛 266590;
    2. 山东科技大学 矿业工程国家级实验教学示范中心, 山东 青岛 266590
  • 收稿日期:2018-04-08 出版日期:2018-10-30 发布日期:2018-11-05
  • 通讯作者: 孙佳欣(1993-),女,山东省人,硕士研究生,主要研究方向为系统决策理论与应用.
  • 作者简介:颜伟(1980-),女,山东省人,副教授,博士,主要研究方向为系统工程
  • 基金资助:

    国家自然科学基金资助项目（51509149）

Measurement of the Responsiveness of Industrial Engineering Application-oriented Innovative Talent Training Mode

YAN Wei1,2, YUAN Qinghe1,2, SUN Jiaxin1, OU Longfei1   

  1. 1. College of Mining and Safety Engineering, Shandong University of Science and Technology, Qingdao 266590, China;
    2. National Demonstration Center for Experimental Mining Engineering Education, Shandong University of Science and Technology, Qingdao 266590, China
  • Received:2018-04-08 Online:2018-10-30 Published:2018-11-05

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摘要：

培养符合创新型社会发展需求和与国际接轨的工程教育专业认证标准要求的应用型创新人才已经成为各高校工业工程专业需要长远规划的问题，因此测度人才培养模式对专业认证标准的响应契合程度是评价该模式有效性的重要指标。为了构建一套良好的应用型创新人才培养模式，本文基于能够全面表达模糊性和随机性特征的云理论，确立了7级测度云标尺，根据云理论扩展标度的层次分析法为培养模式各要素指标分配了权重，构建了响应云的测度模型，通过计算响应云与标尺云的贴近度确定隶属等级，实现了“培养模式—认证标准”响应性的有效测度。最后，将该测度模型进行了实证分析，结论表明：采用云理论构建了响应云的测度模型，实现了“培养模式—认证标准”响应性的评价，并客观表达了测度本身的模糊性和随机性；应用型创新人才培养模式包含的要素中，“教育理念B2”和“培养过程B4”占据了60%以上的比重，高校只有在这两个要素上取得较好的分值，才能提高培养模式对通用标准的响应契合程度。为今后高校工业工程专业制定契合工程教育专业认证的应用型创新人才培养模式提供了有价值的参考。

关键词: 工程教育专业认证标准, 工业工程, 应用型创新, 人才培养模式, 响应性, 云理论

Abstract:

Cultivating application-oriented innovative talents meeting the needs of innovative social development and the requirements of international standards for engineering education certification has become a problem for the long-term planning of university industrial engineering major courses. So measuring the fitness of personnel training modes to professional certification standards is an important indicator to evaluate the effectiveness of the models. In order to build a good model of application-oriented innovative talents, a 7-level cloud scale is established, with the cloud theory fully expressing the characteristics of ambiguity and randomness. The analytic hierarchy process, which measures the scale according to the cloud theory, assigns weights to the various elements of the training model, and constructs a measure model of the response cloud. The degree of subordination is determined by the degree of closeness between the computational response cloud and the ruler cloud, and an effective measure of the responsiveness of the "cultivation mode-authentication standard" is achieved. Finally, this measurement model is empirically analyzed. The conclusion shows:The cloud model is used to construct a response cloud measurement model, which achieves the evaluation of the responsiveness of the "cultivation mode-authentication standard" and objectively expresses the ambiguity and randomness of the measure itself. Among the elements of the training model for application-oriented innovative talents, the "education concept B2" and "cultivation process B4" account for more than 60% of the total. Only when the colleges and universities obtain good scores in these two factors can the training mode be more responsive to the common standards. This will provide a valuable reference for the development of application-oriented innovative talents training mode for professional engineering education in colleges and universities.

Key words: engineering education accreditation standards, industrial engineering, applied innovation, talent training mode, responsiveness, cloud theory

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