High achievers’ attitudes, flow experience, programming intentions and perceived teacher support in primary school: A moderated mediation analysis

School climate and left-behind children’s achievement motivation: The mediating role of learning adaptability and the moderating role of teacher support

“…In addition, as children advance in grade, they face more life and physical problems. Multiple reasons, such as heavy homework burden, fierce competition among classmates, strict requirements of teachers, and extra attention to academic performance ( Chaudhuri et al, 2022 ; Granziera et al, 2022 ; Kong and Lin, 2022 ), will lead to low attention of left-behind children to teachers. At the same time, as left-behind children get older, their learning adaptability and achievement motivation may also decrease.…”

Exploring EFL learners’ acceptance and cognitive absorption at VR-Based language learning: A survey and experimental study

“…This experience revealed that EFL learners’ curiosity toward VR may not be a significant predictor of their behavioral intention to use and perception of immersion, where the other constructs were significantly associated with each other. Study 2 followed [ 40 ]; who replaced the four constructs of the HMSAM (perceived usefulness, curiosity, joy, and control) with CA and found that VR increased CA among EFL learners, leading to better learning outcomes.…”

“…Extending [ 38 ] hedonic system adoption model (HSAM), which was based on Davis' (1989) technology acceptance model (TAM), HMSAM sheds light on learners’ attitudes toward e-learning systems [ 39 , 40 ], gamified learning environment [ 41 , 42 ] as well as their flow experiences (i.e., concentration, intrinsic motivation, and enjoyment, please see Li et al, 2019 for details) and behavioral intention of continuous use [ 43 ]. The HMSAM helps researchers and practitioners design and evaluate target systems that enhance user engagement and satisfaction.…”

“…Many scholars have acknowledged the adequacy of HMSAM for academic research and adopted it to unpack user experiences with using innovative technology in educational practices, which covered multifaceted personal reasons such as the control of using, the ability to use, the happiness of such use and the level of immersion when using the technology [ 40 , 42 ]; Sampurna et al, 2021). Similarly, this study used the HMSAM to explore EFL learners’ perceptions of the hedonic and immersion functions of VR technology in English L2 learning.…”

Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

“…Attitudes have been described as positive or negative feelings about specific behaviors (Ajzen, 2012). Sufficient evidence exists in the literature that shows individuals' attitudes directly influence their behavioral intention to use or learn technology (Kong & Lin, 2022;Szymkowiak & Jeganathan, 2022). In the context of AI, Chai et al (2020) investigated how secondary school students' intentions to learn AI were linked to some psychological factors and found that attitude predicts behavioral intention.…”