ABSTRACT
Background
Students’ science aspirations has received much attention worldwide in recent years, and becoming an important goal of science education. Although many studies have pointed out several factors potentially influencing science aspirations, there is still a relative lack of research on the specific mechanisms at play.
Purpose
This study aims to collectively discuss the effects of science capital, learning experiences, attitudes, self-efficacy, and outcome expectations on science aspirations and the mechanisms of these five factors in predicting students’ science aspirations.
Sample
This study was conducted with 8,501 primary and secondary school students from 320 schools in China.
Design and methods
The validity of the instrument was verified through EFA and CFA. The strength of the relationships between different variables was measured through correlation analysis. Direct effect analysis was used to establish the effect of the variables on science aspirations. Mediation effect analysis was used to test a series of pathways for mechanisms of action.
Results
The developed instrument is valid. Science capital, learning experiences, self-efficacy, attitudes, and outcome expectations were able to influence science aspirations significantly and positively. The mediation between science capital and science aspirations was established, specifically as a chain mediation.
Conclusion
The development of students’ science aspirations is a gradual process that is facilitated by coordinating the combined effects of science capital, learning experiences, self-efficacy, attitudes and outcome expectations in education.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data are available from the corresponding authors upon reasonable request.
Ethics statement
This research study was approved by the Ethics committee at the University. All individuals participating in this study consented to participate and agreed that data about their provided answers in the computational environment will be anonymously collected, stored and analysed.