IDEAS home Printed from https://ideas.repec.org/a/dbk/datame/v3y2024ip.415id1056294dm2024415.html
   My bibliography  Save this article

Work-Based Learning Independent Learning (WBL-MB): Optimizing Learning Models Based on the Industrial World

Author

Listed:
  • Adi Fitra Andikos
  • M Giatman
  • Sukardi

Abstract

The selection of learning models can have a significant influence on the quality of the learning process. A new learning paradigm called Work Base Learning Merdeka Belajar (WBLMB) was created to increase the effectiveness of integrating learning into the workplace. The main purpose of this study is to evaluate the effectiveness of the WBLMB learning paradigm. In the January-June 2024 semester, the research was carried out at the Multimedia Department of SMK Negeri 1 Koto Baru, Indonesia. Samples from the experimental and control groups were obtained because this study used a pseudo-experimental design. The experimental group used the Work-Based Learning (WBL) model, while the control group used the WBLMB model. In this study, primary and quantitative data were used. Different test equipment is used to perform before and after testing to obtain these results. The N-Gain method was used to create this data to evaluate the efficacy of the WBLMB model. The N-Gain technique is based on the criteria of homogeneity test, normality test, and t-test. The experimental group scored 35.22 out of 40, while the control group scored 38.17. In the follow-up test, the experimental group scored 85.52, while the control group scored 67.12. Based on the post-test findings in the experimental group, the results were 62.44% to 90.76%, with an average score of 79.02%. On the N-Gain value spectrum, a score of 79.02% is classified as very high. The improvement of learning outcomes occurs if the WBL-MB learning paradigm is prioritized in the world of work.

Suggested Citation

Handle: RePEc:dbk:datame:v:3:y:2024:i::p:.415:id:1056294dm2024415
DOI: 10.56294/dm2024.415
as

Download full text from publisher

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a
for a similarly titled item that would be available.

More about this item

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dbk:datame:v:3:y:2024:i::p:.415:id:1056294dm2024415. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Javier Gonzalez-Argote (email available below). General contact details of provider: https://dm.ageditor.ar/ .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.