Research on the Implementation Status and Learning Satisfaction of Off-campus Internship Courses in the Department of Mechanical Engineering of the University of Technology

Dyi Cheng Chen, Hsi Chi Hsiao, Jen Chia Chang, Su Chang Chen, Kuo Cheng Wen, Jia Yue Guo, Yu Chen Gao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study explores 38 students of mechanical engineering at the University of Technology. The experiment group and the control group are used to compare the differences in the satisfaction of students with and without the intervention of topic-oriented teaching materials, and to understand the situation of learning satisfaction after the training with external students. This study uses a questionnaire distribution method for analysis and research. The content of the questionnaire is divided into two parts: student background attribute data and student learning satisfaction. The analysis is based on descriptive statistics and t test correlation. The results show that there are significant differences between interventional teaching materials and student learning satisfaction. The value of “Course Teaching” is 4.965 p <.001; the value of “Internship Environment” is 2.183 p <.05, and the value of “Internship Tutoring” is 4.423 p <.001. The study found that the learning level of “Course Teaching”, “Internship Environment” and “Internship Tutoring” has improved significantly. Before the internship, students conducted project-based off-campus internship teaching material teaching, so that students have a certain cognition for the enterprise during the internship. Preparing knowledge and standards can also improve self-study performance. Finally, on the basis of the research results, this study puts forward related suggestions, project-based and future research for improving undergraduate internships.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - Third International Conference, ICITL 2020, Proceedings
EditorsTien-Chi Huang, Ting-Ting Wu, João Barroso, Frode Eika Sandnes, Paulo Martins, Yueh-Min Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages172-181
Number of pages10
ISBN (Print)9783030638849
DOIs
Publication statusPublished - 2020
Event3rd International Conference on Innovative Technologies and Learning, ICITL 2020 - Porto, Portugal
Duration: 2020 Nov 232020 Nov 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12555 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Innovative Technologies and Learning, ICITL 2020
CountryPortugal
CityPorto
Period20-11-2320-11-26

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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