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Paper Title:
Application of Information Technology-Based Startup E-Modules for Entrepreneurship Learning in Vocational Students Faculty Of Engineering Universitas Negeri Makassar
This study aims to (1) determine how much learning outcomes before and after the implementation of the Start-Up E-Module in the Mechatronics Vocational Education Study Program. (2) improve student learning outcomes after being taught using the Start-Up E-Module in the entrepreneurship course of the Mechatronics Vocational Education Study Program. This study uses a Pre pre-experimental design design in the form of a group Pretest-Posttest Design. Based on descriptive statistical analysis, it is found that there is a significant difference between the learning outcomes of entrepreneurship courses before and after the use of E-Modul Start-Up media. This can be seen in the average score obtained at the time of the pretest which is 57.42 and the average score at the time of the posttest is 87.53 while the results obtained by the N-Gain test showed that there was an average increase of 0.7 which is classified as high. So one of the efforts that can be made to improve learning outcomes in entrepreneurship course learning in Mechatronics Vocational Education Study Program students is to use E-Module Start-Up media in entrepreneurship course learning to be more interesting, and interactive and the quality of student learning can be improved.
Keywords:
Vocational Education, E-Module Startup, Information Technology, Entrepreneurship
Cite Article:
"Application of Information Technology-Based Startup E-Modules for Entrepreneurship Learning in Vocational Students Faculty Of Engineering Universitas Negeri Makassar", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.423 - 429, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405063.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator