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Moving lab-based in-person training to online delivery: The case of a continuing engineering education program
Journal of Computer Assisted Learning ; 2023.
Article in English | Scopus | ID: covidwho-2271388
ABSTRACT

Background:

Online learning has recently surged due to the COVID-19 global pandemic. Because of the pandemic, many universities were forced to move to online learning, and various online teaching and learning environments emerged, both asynchronous and synchronous.

Objective:

This study explores how a large university in the Southeastern United States of America converted an in-person Lean Manufacturing professional course into synchronous online learning for industry participants.

Method:

The study analysed the performance of 212 in-person and 43 online industry participants and examined the views of online participants about the training. Paired t-tests, one-way multivariate analysis of covariance (MANCOVA), and univariate analysis of covariance (ANCOVA) were utilized to evaluate the performance of the in-person and online groups on the three competencies (Lean culture, problem-solving and Lean systems). Results and

Conclusion:

Both online and in-person programs performed equally well in two Lean Manufacturing competencies Lean systems and problem solving. The online program outperformed the in-person program in the third competency, Lean culture. Overall, the participants had a positive experience with the structure and organization of the online program, and their impression of the online learning environment for the program was positive. The study findings indicated that Lean Manufacturing could be trained effectively online and in person. Best practices are suggested for the conversion of in-person to synchronous online engineering continuing education programs. © 2023 The Authors. Journal of Computer Assisted Learning published by John Wiley & Sons Ltd.
Keywords

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Journal of Computer Assisted Learning Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Journal of Computer Assisted Learning Year: 2023 Document Type: Article