基于回归和深度学习技术的高校科研生产力影响因素的探索性研究

Rasha G Mohammed Helali
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引用次数: 0

摘要

高等教育正在努力应对全球化带来的挑战。世界大学之间的竞争不仅取决于基础设施的可用性和教师的教学质量,还取决于他们的研究表现。教职员工的研究成果对一所大学的地位、获得资金的能力以及招收国内和国际学生的能力都有重大影响。本文的目的是找出影响高校科研生产力的因素。本文报告了来自不同教育机构的学术人员对研究绩效决定因素等问题的看法。除了深度学习之外,还使用了定量分析方法,包括相关和回归,以实现本文的目标。本研究的结果显示,学术机构对加强研究的支持,以及为此提供的设施和资金,对研究绩效有很大的影响。教师科研时数的分配也对科研水平的提高产生了积极的影响。将职业晋升与科学研究联系起来,鼓励教师发表更多的论文。此外,教师的资格水平对他们的论文发表率有很大的影响。
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An Exploratory Study of Factors Affecting Research Productivity in Higher Educational Institutes Using Regression and Deep Learning Techniques
Higher education is grappling with challenges from globalization. The competition between worldwide universities depends not only on the availability of infrastructure and faculty members' teaching quality, but also on their research performance. The research produced by faculty members has a significant impact on a university's standing, ability to acquire funds, and ability to enroll both domestic and international students. The objective of this paper is to identify factors affecting scientific research productivity in selected higher educational institutes. The paper reports the views of academic staff from different educational institutes on such issues as the determinants of research performance. A quantitative analysis approach, including correlation and regression, in addition to deep learning, was utilized to achieve the aim of the paper. The findings of this research demonstrate that the support of academic institutes for enhancing research and providing facilities and funds for such purpose has a great impact on research performance. The allocation of hours of scientific research to the faculty member also had a positive impact on the improvement of scientific research. Linking career promotion and scientific research encourages faculty members to publish more papers. Moreover, the level of qualification for faculty members has a great impact on their rate of publishing papers.
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