IDEAS home Printed from https://ideas.repec.org/a/mth/jeijnl/v8y2022i2p152161.html
   My bibliography  Save this article

Developing Grade 10 Student Learning Achievement of Relation Using Deductive Learning Management with Online Exercises

Author

Listed:
  • Minmanee Reangnok
  • Apantee Poonputta

Abstract

The purposes of the study were 1) to investigate the effectiveness of deductive learning management with online exercises on grade 10 students learning achievement of mathematical relations; and 2) to investigate students’ satisfaction with the learning management. The study was conducted in a one-group pretest-posttest design. The participants were 41 Thai grade 10 students learning mathematics. The cluster random sampling method was employed in the participant selection process. The instruments were a learning management plan designed in a deductive learning management, a learning achievement test, and a satisfaction questionnaire. The effectiveness of the deductive learning management on students’ learning achievement of mathematical relation was assessed by considering the participant’s performance while learning in the class and at the end of the class. The statistics used in the data analysis were percentages, mean scores, standard deviation, a paired t-test, and an effectiveness test (E1/E2) with the determining criteria of 75/75. The results of the study indicate that the deductive learning management plan with online exercises was capable of improving grade 10 students’ learning achievement of mathematical relations. Moreover, it also brought about a satisfying experience learning the concept. The study contributed to the area of mathematics education as it provided an example to support the use of the deductive learning management on learners with limited mathematic skills.

Suggested Citation

  • Minmanee Reangnok & Apantee Poonputta, 2022. "Developing Grade 10 Student Learning Achievement of Relation Using Deductive Learning Management with Online Exercises," Journal of Educational Issues, Macrothink Institute, vol. 8(2), pages 152161-1521, December.
  • Handle: RePEc:mth:jeijnl:v:8:y:2022:i:2:p:152161
    as

    Download full text from publisher

    File URL: https://www.macrothink.org/journal/index.php/jei/article/download/20065/15581
    Download Restriction: no

    File URL: https://www.macrothink.org/journal/index.php/jei/article/view/20065
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:mth:jeijnl:v:8:y:2022:i:2:p:152161. 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: Technical Support Office (email available below). General contact details of provider: http://jei.macrothink.org .

    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.