ArticleFrontiers in psychology2022
Enhancing Career Decision Status of Socioeconomically Disadvantaged Students Through Learning Engagement: Perspective of SOR Model.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Exploring the neurosurgery training landscape in Pakistan: A trainee's perspective in resource-limited settings.World neurosurgery: X · 2024Article
- Development of immersive learning framework (ILF) in achieving the goals of higher education: measuring the impact using a pre-post design.Scientific reports · 2023Article
- Enhancing students' English language learning via M-learning: Integrating technology acceptance model and S-O-R model.Heliyon · 2023Article
- The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR.Frontiers in psychology · 2023Article
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2 authors.
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Abstract
Higher education plays the role of cultivating talents in national development and meets the talent sources needed by the development of the state, industries and enterprises. Besides, for students, higher education can provide stimuli to improve the development of family and personal career. Especially for socioeconomically disadvantaged Students, higher education means the main factor for turning over the Socio- Economic Status. Universities endow students with abundant employment skills, so as to make them more confident in contending with the challenges in the job market. However, innate pessimism or negative attitudes and cognition may exist in socioeconomically disadvantaged Students, thereby providing effective learning context to improve their learning engagement. This study explores the influence on students' career decision status from deep approach to learning, problem-based learning, self-efficacy and employability. A total of 627 valid questionnaires are collected in this study. PLS-SEM was adopted to verify the structural relationship in data analysis
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