IDEAS home Printed from https://ideas.repec.org/a/rnd/arjevr/v7y2016i3p30-37.html
   My bibliography  Save this article

Effectiveness of Modern Teaching Methods; Evidence from Digital Learning Model of Modern Teaching Methods

Author

Listed:
  • Ejaz Gul

Abstract

This paper elucidates the efficacy of three selected modern and innovative methods of learning by taking a group of 80 students of economics class at university level. Their opinion regarding three selected modern teaching methods was obtained through a questionnaire and statistical analysis of their opinion was carried out which indicated strong tendency towards mutual practice method as 40 out of 80 students (50%) declared it as very effective method of learning in the practice stage. On the other hand, 30 students (37.5%) opined that controlled practice method is moderately effective and 28 (35%) students opined that team practice method is slightly effective. After this analysis, students were put to practically learn use of econometric software ‘E Views’ through the same three selected methods. The digital model for their learning process was created using Computer Assisted Qualitative Data Assisted Software (CAQDAS). The statistical analysis of students’ opinion and digital analysis of practical learning process indicated that mutual practice is the most effective method of practice. It is because students learn better and fast when they are allowed to use their initiative and judgment. At the end, guidelines for effective teaching have been suggested.

Suggested Citation

  • Ejaz Gul, 2016. "Effectiveness of Modern Teaching Methods; Evidence from Digital Learning Model of Modern Teaching Methods," Journal of Education and Vocational Research, AMH International, vol. 7(3), pages 30-37.
    • Handle: RePEc:rnd:arjevr:v:7:y:2016:i:3:p:30-37
    DOI: 10.22610/jevr.v7i3.1413
    as

    Download full text from publisher

    File URL: https://ojs.amhinternational.com/index.php/jevr/article/view/1413/1308
    Download Restriction: no
    File URL: https://ojs.amhinternational.com/index.php/jevr/article/view/1413
    Download Restriction: no
    File URL: https://libkey.io/10.22610/jevr.v7i3.1413?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:rnd:arjevr:v:7:y:2016:i:3:p:30-37. 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: Muhammad Tayyab (email available below). General contact details of provider: https://ojs.amhinternational.com/index.php/jevr .

    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.