IDEAS home Printed from https://ideas.repec.org/a/bcp/journl/v9y2025issue-8p7432-7444.html
   My bibliography  Save this article

Predicting College Students’ Squared Platform Utilization: A Multiple Regression Analysis of the Technology Acceptance Model

Author

Listed:
  • Justine G. Landicho

    (Davao Central College, Toril, Davao City, Philippines)

  • Roberto Jr. P. Tacbobo

    (Davao Central College, Toril, Davao City, Philippines)

  • Alkhaser V. Sappayani

    (Davao Central College, Toril, Davao City, Philippines)

Abstract

This study explored the factors that influence college students’ use of the Squared Platform, a QR code-based attendance system created by the College Supreme Student Government of Davao Central College in Davao City. The research was anchored on the Technology Acceptance Model (TAM), which focuses on how perceived ease of use, perceived usefulness, and behavioral intention affect actual system use. Using a predictive-correlational design, data were collected from a stratified sample of 368 enrolled students from five different departments through a validated and reliable questionnaires. The responses were analyzed using frequency, percentage, mean, ANOVA, Pearson correlation, and multiple regression analysis. Findings revealed that students had a very high level of acceptance toward the platform across all TAM constructs. No significant differences were found in terms of year level, but there were significant differences across departments, especially in perceived usefulness. Strong positive relationships were also found between each TAM variable and students’ actual usage behavior, with behavioral intention having the strongest influence. The combined predictors significantly explained more than half of the variance in actual usage. The results support the Technology Acceptance Model, proving that ease of use and usefulness influence students’ intention and actual behavior in using educational technologies like the Squared Platform. Based on the findings, it is recommended that the school promote training, raise awareness, and offer department-specific support to improve technology adoption and ensure effective implementation across all programs.

Suggested Citation

  • Justine G. Landicho & Roberto Jr. P. Tacbobo & Alkhaser V. Sappayani, 2025. "Predicting College Students’ Squared Platform Utilization: A Multiple Regression Analysis of the Technology Acceptance Model," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(8), pages 7432-7444, August.
  • Handle: RePEc:bcp:journl:v:9:y:2025:issue-8:p:7432-7444
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijriss/Digital-Library/volume-9-issue-8/7432-7444.pdf
    Download Restriction: no

    File URL: https://rsisinternational.org/journals/ijriss/articles/predicting-college-students-squared-platform-utilization-a-multiple-regression-analysis-of-the-technology-acceptance-model/
    Download Restriction: no
    ---><---

    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:bcp:journl:v:9:y:2025:issue-8:p:7432-7444. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .

    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.