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Framework effect and achievement motivation on college students’ online learning intention–based on technology acceptance model (TAM) and theory of planned behaviour (TPB) model

  • Hang Wang,
  • Xiaorong Hou,
  • Jiaxiu Liu,
  • Xiaoyu Zhou,
  • Mengyao Jiang,
  • Jing Liao

摘要

The purpose of this study was to explore the factors of college students’ learning intention when they use online learning platforms by using structural equation model (SEM), integration technology acceptance model (TAM) and planned behavior theory (TPB). With the help of this study, the development of distance online learning for college students is promoted. The study delves into the underlying factor influencing college students’ intention towards online learning. Moreover, it explores the specific impact of framework effect and achievement motivation on their online learning intention. Employing a convenient sampling technique, the study gathered responses from a sample of 468 students enrolled in a specific university. The findings reveal the successful establishment of a comprehensive model elucidating the factors influencing online learning intention. Notably, achievement motivation not only exerts a direct influence on learning intention, but also indirectly affects it through various factors within the online learning intention model, including learning attitude (LA), perceived ease of used (PEOU), and perceived usefulness (PU). Furthermore, these factors exhibit varying impacts on online learning intention within different message framing contexts. The study’s innovative and practical nature lies in its integration of the technology acceptance model (TAM) and theory of planned behavior (TPB) to establish a comprehensive model of online learning intention. By offering pertinent recommendations, the study aims to optimize the online learning methods of university educators and improve the quality of online instruction. By investigation the specific influence of achievement motivation and framing effect on online learning intention through this model, the study provides some feasible methods for educators to use the factor model to improve online learning intention of university students.