Determinants of long-term E-learning engagement: Integrating expectation confirmation theory and individual innovativeness using PLS-SEM

Fadi Herzallah*, Husam Tewfeek Mohamad Herz Allah, Mohammed A. Al-Sharafi, Mahmoud Alhayek

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The COVID-19 pandemic has forced many educational institutions to switch to e-learning. However, the concern of most stakeholders from higher education institutions about adopting and using e-learning systems in many developing countries has become more pronounced given several challenges facing the industry. This article investigates the determinants of students' continuance intention to use e-learning systems by extending the Expectation Confirmation Theory with individual innovativeness. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM), data collected from 361 students at Palestinian universities was analyzed. The relationship between perceived usefulness, satisfaction, expectation confirmation, and individual innovativeness was evaluated within the proposed model to determine their impact on students' intention to continue utilizing e-learning platforms. The results reveal that perceived usefulness and satisfaction significantly influence students' continuance intention to use e-learning systems. Expectation confirmation also positively influences satisfaction and perceived usefulness, underpinning the significance of achieving the initial expectations of students. Additionally, individual innovativeness is identified as a critical factor that enhances both perceived usefulness and the likelihood of continued e-learning use. However, the study is limited by its cross-sectional design, convenience sampling methodology, and focus on only two Palestinian universities (PTUK and QOU), which constrains generalizability to other cultural contexts and higher education systems. The study adds valuable insights and guidance to policymakers and educators to strengthen adoption and retention in similar educational settings, contributing to a more engaging and effective digital learning environment.

Original languageEnglish
Article number100853
JournalComputers in Human Behavior Reports
Volume20
DOIs
StatePublished - Dec 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 The Authors.

Keywords

  • Expectation confirmation theory
  • Individual innovativeness
  • PLS-SEM
  • s: E-learning continuance
  • Student satisfaction
  • Technology adoption

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Applied Psychology
  • Human-Computer Interaction
  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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