Assessing the learning behavioral intention of commuters in mobility practices

  • Waqas Ahmed
  • , Habiba Akter
  • , Sheikh M. Hizam
  • , Ilham Sentosa
  • , Syeliya Md Zaini

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Learning behavior mechanism is widely anticipated in managed settings through the formal syllabus. However, heading for learning stimulus whilst daily mobility practices through urban transit is the novel feature in learning sciences. Theory of planned behavior (TPB), technology acceptance model (TAM), and service quality of transit are conceptualized to assess the learning behavioral intention (LBI) of commuters in Greater Kuala Lumpur. An online survey was conducted to understand the LBI of 117 travelers who use the technology to engage in the informal learning process during daily commuting. The results explored that all the model variables i.e., perceived ease of use, perceived usefulness, service quality, and subjective norms are significant predictors of LBI. The perceived usefulness of learning during traveling and transit service quality has a vibrant impact on LBI. The research will support the informal learning mechanism from commuters’ point of view. The study is a novel contribution to transport and learning literature that will open the new prospect of research in urban mobility and its connotation with personal learning and development.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume2817
StatePublished - 2021
Externally publishedYes
Event1st Workshop on Technology Enhanced Learning Environments for Blended Education - The Italian e-Learning Conference, teleXbe 2021 - Foggia, Italy
Duration: 21 Jan 202122 Jan 2021

Bibliographical note

Publisher Copyright:
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Keywords

  • Learning Behavioral Intention
  • Mobility
  • Service Quality

ASJC Scopus subject areas

  • General Computer Science

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