INFLUENCING FACTORS OF 10th GRADE STUDENTS’ SCIENCE CAREER EXPECTATIONS: A STRUCTURAL EQUATION MODEL

Wang, Jingying; Yang, Mingyue; Lv, Beibei; Zhang, Feixiong; Zheng, Yonghe; Sun, Yongqiang

doi:10.33225/jbse/20.19.675

Cited by 16 publications

(10 citation statements)

References 40 publications

(47 reference statements)

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“…First of all, this study found that ILE, such as visiting STEM related museums, participating in STEM related clubs, competitions and summer camps can promote ISC significantly, which is consistent with previous research results (Kitchen et al, 2018;Maiorca et al, 2021;Nugent et al, 2015). Secondly, students with higher STEM self-efficacy are more confident that they have the ability to engage in STEM careers and achieve good results, and thus more interested in STEM careers (Mohtar et al, 2019;Wang et al, 2020). Thirdly, the clearer the knowledge about STEM career prospects, skills required, and self-development, the more likely students are to make sober and wise decisions.…”

Section: Discussionsupporting

confidence: 89%

“…This is supported by theory-based models, such as SCCT (Lent, 1994). Many studies (Halim et al, 2018;Maiorca et al, 2021;Mohtar et al, 2019;Nugent et al, 2015;Wang et al, 2020) have demonstrated that SSE is an important factor for individuals to pursue STEM careers. In this study, SSE was assessed by students' confidence in their own abilities and performance in the four subjects of STEM (Mohtar et al, 2019).…”

Section: Stem Self-efficacy (Sse)mentioning

confidence: 87%

“…Teaching strategies (such as student-centered teaching, project-based learning, and inquiry-based teaching) can also affect students' ISC (Lou et al, 2011;Wyss et al, 2012;Zhou et al, 2019). As such, with deliberate structures and intentions to engage students with inquiry ways of learning, formal education can be designed to affect students' STEM self-efficacy and STEM careers perceptions, as well as their ISC (Mohtar et al, 2019;Wang et al, 2020).…”

Section: Learning Experiences (Le)mentioning

confidence: 99%

See 2 more Smart Citations

The Effect of Learning Experiences on Interest in Stem Careers: A Structural Equation Model

Wang

Tan

Xiao

et al. 2021

JBSE

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Learning experiences can affect students' interest in STEM (science, technology, engineering, and mathematics) careers. Applying the social cognitive career theory, this study tested and compared the effect size and effect mechanism of formal learning experiences (FLE) and informal learning experiences (ILE) on 1133 tenth-grade students' interest in STEM careers (ISC) through a paper questionnaire survey. The results of structural equation model analysis showed that: 1) The total effect of ILE on students' ISC is much greater than that of FLE; 2) ILE, STEM self-efficacy (SSE) and STEM careers perceptions (SCP) can directly affect students' ISC; FLE and ILE can also indirectly affect students' ISC through the mediating role of SSE and SCP. The analyses suggest that in order to improve students' ISC, STEM education (especially informal STEM education) should be strengthened, both formal and informal education should pay attention to the cultivation of students' SSE and SCP. Keywords: interest in STEM careers, learning experiences, social cognitive career theory, STEM careers perceptions, STEM self-efficacy, structural equation model

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Section: Discussionsupporting

confidence: 89%

Section: Stem Self-efficacy (Sse)mentioning

confidence: 87%

Section: Learning Experiences (Le)mentioning

confidence: 99%

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The Effect of Learning Experiences on Interest in Stem Careers: A Structural Equation Model

Wang

Tan

Xiao

et al. 2021

JBSE

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“…Selection of the subject for a better career of a student is a vital task since it is concerned with future employment which influences the whole life of the student and ultimately leads to social development. It is a delegate decision for the students as they are ambitious about it (Batool et al, 2020, Van Dinh et al, 2019, Pratiwi et al, 2020, McKenzie et al, 2020, Wang et al, 2020, Babajide et al, 2020, Orewere et al, 2020. Some students are in confusion or careless to choose a stream.…”

Section: Introductionmentioning

confidence: 99%

Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory

Sahu

Dash

Das

2021

Decis. Mak. Appl. Manag. Eng.

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Since the future of the society depends upon the role of students, so suitable career selection methods for the students are considered to be an important problem to explore. It is assumed that if a student has the required capability and positive attitudes towards a subject, then the student will achieve more in that subject. To consider the uncertain issues involved with students’ career selection, picture fuzzy set (PFS) and rough set based approaches are proposed in this study as they are found to be appropriate due to their inherent characteristics to deal with incomplete and imprecise information. For the purpose of selecting a suitable career, the article analyzes student's features in terms of career, memory, interest, knowledge, environment and attitude. We propose two hybridized distance measures using Hausdorff, Hamming and Euclidian distances under picture fuzzy environment where the evaluating information regarding students, subjects and student's features are given in picture fuzzy numbers. Then we present an algorithmic approach using the proposed distance measures and rough set theory. We apply rough set theory to determine whether a particular subject is suitable for a student even if there is controversy to select a stream. Lower and higher approximation with boundary region of rough set theory is used to manage the inconsistent situations. Finally, two case studies are demonstrated to validate the applicability of the proposed idea.

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“…It has clear purpose, objective reality, strong comprehensiveness, profound inspiration, highlights practice, student-centered, dynamic process, and the results are diversified. Since being introduced to China as a new teaching method in the mid-1980s, case teaching method has gradually been accepted by more and more people, and it has been proved to be an effective and special effect in teaching practice [1]. e participants in the classroom case teaching process include teachers and students.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Influencing Factors of Teaching Effect Based on Structural Equation Model

2021

Complexity

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Structural equation model is a multivariate statistical analysis method. It can not only test some unpredictable abstract ideas, but also design parameters for the causal connection model between independent variables and dependent variables. Among them, the analysis of various latent variables is based on the verification factor analysis technology. The research first collects various relevant data, derives the latent variables and measurement variables, then composes the measurement model, and then verifies the adaptability of the measurement model structure mode through actual data collection. When such suitable factors are determined, a causal model based on path analysis technology for latent variables, that is, a structural model, can be used for parameter design. This article uses the structural equation model as an analysis tool, starting from the three aspects of teachers, cases, and students to evaluate the application effect of the case teaching method in the classroom teaching of intellectual property law course and construct a structural equation model of the influencing factors of the case teaching effect. To understand students’ satisfaction with case teaching effects and related influencing factors, the research results show that the effect of case teaching is jointly affected by the level of teachers, case selection, and student response. Among them, teacher factors have the greatest impact on case teaching effects, followed by case factors, and students have the least.

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INFLUENCING FACTORS OF 10th GRADE STUDENTS’ SCIENCE CAREER EXPECTATIONS: A STRUCTURAL EQUATION MODEL

Cited by 16 publications

References 40 publications

The Effect of Learning Experiences on Interest in Stem Careers: A Structural Equation Model

The Effect of Learning Experiences on Interest in Stem Careers: A Structural Equation Model

Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory

Analysis of Influencing Factors of Teaching Effect Based on Structural Equation Model

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