The influence of achievement motivation on college students’ employability: A chain mediation analysis of self-efficacy and academic performance
Xiang Li, Xiang Li, Ruihui Pu and 1 more
Frontiers in Psychology · 2022
doi:10.3389/fpsyg.2022.972910 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Employability of college students has been attached great importance by higher education institutions, employers, and governments because college graduates are the strategic human resource for the sustainable growth of universities, organizations, and countries across the world. It is also receiving growing attention from academic community. This study aimed to examine the psychological mechanism that impacts college students’ employability. It adopted an empirical approach by collecting data from 646 final-year students from 9 universities in the mainland of China. SPSS 25.0 was used for description, correlation, and regression analysis. AMOS 24.0 was utilized for path analysis. Model 6 Bootstrap method of PROCESS Version 3.5 was adopted for mediation analysis. The results showed that achievement motivation positively predicted self-efficacy, academic performance, and employability among undergraduates. Participants’ self-efficacy did not significantly impact their employability or play a mediating role in the relationship between achievement motivation and employability, while academic performance was a significant mediator of this association. Self-efficacy and academic performance served as chain mediators in the prediction of achievement motivation on college students’ employability. After controlling gender and family residence, achievement motivation still had significant and positive impact on employability of college students. This research made several noteworthy contributions to the existing studies on college students’ employability and provided insight for practitioners in strengthening their employability through these psychological constructs.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.