Exploring how psychological capital and grit shape language learners' psychological well-being in AI-based educational contexts: A bifactor analysis

Hehe Huang; Qiumei Wang

doi:10.30827/portalin.vi46.37101

Authors

Hehe Huang Guangdong University of Science and Technology
Qiumei Wang Youjiang Medical College for Nationalities (Corresponding author)

DOI:

https://doi.org/10.30827/portalin.vi46.37101

Keywords:

Artificial intelligence-based contexts, Grit, Psychological capital, Psychological well-being, Self-Determination theory

Agencies: This work was supported by Undergraduate Teaching Reform Project of Guangxi Higher Education (2023JGB319) and Academy of the Sense of Community for the Chinese Nation of Guangxi (2024GXMGY0101).

Abstract

Integrating Artificial Intelligence (AI) into language teaching has changed learning settings, yet the mental systems sustaining students' Psychological Well-being (PWB) remain largely overlooked. Based on Self-Determination Theory (SDT), this research examines how two intrinsic resources—PsyCap and L2 grit—boost PWB in AI-based contexts, as both are vital for protecting PWB in feedback-rich, demanding environments. Thus, 498 Chinese learners of Japanese from four universities who actively use AI-based apps participated. Three validated questionnaires adapted to AI settings were administered online. To disentangle the unique contributions of grit and PsyCap to PWB, a bifactor modeling approach was used. Results showed that both PsyCap and grit significantly predicted PWB, with the bifactor model revealing that a general psychological resource factor accounted for substantial variance, while specific dimensions of each provided unique contributions. By integrating positive psychology and SDT in AI-based learning, this research advances theory and suggests practical interventions that promote PsyCap and grit to develop learners' PWB.

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