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  • 标题:Utilizing Multivariate Analysis for Assessing Student Learning Through Effective College-Industry Partnerships
  • 本地全文:下载
  • 作者:Caleb Burns ; Shweta Chopra ; Mack Shelley
  • 期刊名称:Journal of STEM Education: Innovations and Research
  • 印刷版ISSN:1557-5284
  • 电子版ISSN:1557-5284
  • 出版年度:2018
  • 卷号:19
  • 期号:3
  • 语种:English
  • 出版社:Institute of STEM Education and Research
  • 摘要:There is no doubt that college-industry collaboration is vital towards the success of undergraduate students in engineering and technology major. This provides students with an opportunity to bridge the gap between classroom education and real world experience. Bringing industry representatives to engage in the classroom, involving students with professional chapters, student field trips, virtual plant tours, and industry focused final projects are ways in which instructor tries to incorporate student-industry engagement. Often time’s juniors and seniors participate in internship program during the course of their undergraduate degree where they gain substantial industry engagement and opportunity to learn and apply classroom knowledge. To assess impact of industry engagement on student learning by disseminating questionnaire based survey among undergraduate students to identify what activities have most and least impact on student learning. This research analyzes student perceptions of effectiveness of industry engagement activities using multivariate analysis of variance (MANOVA). The objective is to determine which industry engagement activities are more effective when looking at student learning. Senior-level students at XXX University within the technology program were used along with their comments about the various activities for the sample. Results indicate that there is a difference in how activities impact student learning, with some activities having a higher correlation with student learning.
  • 关键词:student learning;industry engagement;case study;guest speaker;internship;MANOVA
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