IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-622-2_92.html

The Effectiveness of the Problem-Based Learning Model and the Problem-Solving Learning Model on Student Learning Outcomes in Bali State Polytechnic

In: Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Social Applied Science 2024 (ICoSTAS-SAS 2024)

Author

Listed:
  • I Gusti Ayu Putu Dewi Paramita

    (Politeknik Negeri Bali, Civil Engineering Department)

  • Evin Yudhi Setyono

    (Politeknik Negeri Bali, Civil Engineering Department)

Abstract

To establish whether technique optimizes student learning results in the classroom, particularly for Engineering English courses, this study will compare the Problem-Based Learning (PBL) and Problem-Solving (PS) methods. The class that will act as the experimental class should be chosen first. Two courses, 4A and 4B D3 Civil Engineering, were chosen to undertake this study. Two courses, 4A and 4B D3 Civil Engineering, were chosen to undertake this study. The data collection methods include pre- and post-tests on student learning outcomes, as well as interview procedures. The respondents were two classes of fourth-semester students in the D3 study program, totaling 57 participants. The pretest-posttest nonequivalent control group design methodology is used in this quasi-experimental investigation. Data analysis tools include the Mann Whitney, Normality, and Difference tests, as well as SPSS for statistical computations on acquired data. Data analysis revealed that 0.000

Suggested Citation

  • I Gusti Ayu Putu Dewi Paramita & Evin Yudhi Setyono, 2024. "The Effectiveness of the Problem-Based Learning Model and the Problem-Solving Learning Model on Student Learning Outcomes in Bali State Polytechnic," Advances in Economics, Business and Management Research, in: Anak Agung Ngurah Gde Sapteka & I Gusti Lanang Made Parwita & I Komang Wiratama & Fransiska Moi & Ko (ed.), Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Social Applied Science 2024 (ICoSTAS-SAS 2024), pages 838-845, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-622-2_92
    DOI: 10.2991/978-94-6463-622-2_92
    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

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:advbcp:978-94-6463-622-2_92. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.