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新能源材料与器件专业人才培养大数据分析与实践——以苏州大学能源学院为例

Big Data Analysis and Educational Practice for Talent Cultivation Pattern in New Energy Materials and Devices Major:A Case Study of the College of Energy in Soochow University
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摘要 通过大数据分析和实践研究,对苏州大学新能源材料与器件专业的人才培养模式进行了深入探讨。该专业人才培养以OBE理念为基础,强调学生全面发展,平衡专业知识与实践技能。课程体系涵盖专业核心课和基础课,注重跨学科学习。然而,存在实践性课程覆盖面不足和专业课程不完全满足学生需求等局限性。因此,我们将进一步拓展实践性课程和专业课程,完善产教融合创新平台,更注重培养学生的创新与独立思考能力,形成高水平的新工科人才培养体系,满足新能源行业发展对高素质人才多样化的需求。 An in-depth exploration of the talent cultivation pattern in new energy materials and devices major at Soochow University,based on big data analysis and practical investigation,has been conducted.Guided by the Outcome-Based Education(OBE)philosophy,students’overall development is emphasized,where a balance between professional knowledge and practical skills is obtained.The curriculum encompasses a range of core professional and basic courses,with a distinct emphasis on interdisciplinary learning.Nonetheless,several areas for improvement have been identified,including insufficient coverage of practical courses and a dearth of specialized courses tailored to fully address the evolving needs of students.To address these issues,this study proposes an expansion of practical and professional courses,an establishment of the industry-education integration practice platform,and an emphasis on nurturing students’innovative capacities and independent thinking.With these improvements,we aim to establish a high-level New Engineering Talent Cultivation Framework,satisfying the diverse needs of new energy industry towards high-quality talents.
作者 杨瑞枝 YANG Rui-zhi(College of Energy,Soochow University,Suzhou,Jiangsu 215006,China)
出处 《教育教学论坛》 2024年第23期33-36,共4页 Education And Teaching Forum
基金 2021年度苏州大学校级高等教育教改研究课题“基于OBE理念的新能源材料与器件专业人才培养的探索与实践”(苏州大学教字〔2021〕224号) 2022年度江苏省省级一流本科专业建设点(省特色专业)“新能源材料与器件专业”(江苏省教育厅苏教高函〔2022〕10号) 2022年度苏州大学卓越工程师教育培养计划2.0专业建设“新能源材料与器件专业”(苏州大学教字〔2022〕396号)。
关键词 新能源材料与器件专业 人才培养 OBE理念 大数据分析 实践教学 new energy materials and devices major talent cultivation pattern OBE concept big data analysis practical teaching
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