Learners’ Perceptions, an Entry to the E-communication Dynamic
- DOI
- 10.2991/978-94-6239-634-0_12How to use a DOI?
- Keywords
- e-communication; perception; Technology Acceptance Model; Task-Technology Fit
- Abstract
E-communication, encompassing exchanges mediated by digital technologies, is becoming indispensable across professional and social realms. Understanding why certain tools thrive while others languish depends largely on perception. From a psychosociological view, perception is an interpretive process shaped by individual experience, social context, and cultural norms. The Technology Acceptance Model (TAM) highlights perceived usefulness and perceived ease of use as key determinants of adoption. Meanwhile, the Task-Technology Fit (TTF) framework emphasizes aligning technology features with users’ concrete needs. Together, these models clarify why even a capable tool fails if it does not “fit” tasks or user expectations. Applied to e-learning, perception of ergonomics, quality, and support drives motivation and engagement. Ultimately, adopting a new system requires not only its perceived benefits and simplicity but also a favorable social environment and consistent managerial support. Perception thus underpins a collective dynamic that shapes the long-term success of e-communication implementations.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Chinkhir Btissam AU - Ayah Oudghiri AU - Ibrahimi Ahmed PY - 2026 DA - 2026/04/02 TI - Learners’ Perceptions, an Entry to the E-communication Dynamic BT - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2025) PB - Atlantis Press SP - 152 EP - 163 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6239-634-0_12 DO - 10.2991/978-94-6239-634-0_12 ID - Btissam2026 ER -