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Improving Student Learning Outcomes through Mobile Assessment: A Trend Analysis

Herwin Herwin, Anwar Senen, Riana Nurhayati, and Shakila Che Dahalan

Abstract—The integration of technology in learning is one of the popular issues today which is an alternative to solve the problems experienced in the difficulty of achieving maximum learning goals for students. This study aims to examine the effectiveness of the application of mobile assessment in learning activities in elementary schools. This research is a quantitative study using descriptive type. The respondents of this study were elementary school students who were at the fifth-grade level. Data were collected through learning outcomes tests using mobile assessment technology. The data analysis technique used is trend analysis. Research findings indicate that there is a positive trend in student learning outcomes when using mobile assessments in learning activities. Based on the model fit, the findings show that the Quadratic Trend Model is the best model with the smallest measurement error.

Index Terms—Learning outcomes, mobile assessment, trend analysis.

Herwin Herwin, Anwar Senen, and Riana Nurhayati are with the Faculty of Education, Universitas Negeri Yogyakarta, Indonesia (e-mail: herwin89@uny.ac.id, senen@uny.ac.id, riana_nurhayati@uny.ac.id).
Shakila Che Dahalan is with the Faculty of Human Science, Universiti Pendidikan Sultan Idris, Malaysia (e-mail: shakilacd@fsk.upsi.edu.my).

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Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2021: 1.3), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net

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