An Equation Model on the Professional Knowledge and Confidence for Future Employment of Students in Programs Supported With Emerging Technologies

Students enrolled in interdisciplinary programs supported with modern information technologies may face more challenges in learning, because they must learn from at least two curricula, including courses of big data, new media technologies and intelligent platform use, etc. Taking students in these programs as an example, this study aims to investigate relationships among eight variables related to student career development. The research employed the quantitative method of Pearson bivariate analysis, ANOVA and Hayes (2017) regression procedure to test the direct and indirect relationship among variables. The researcher developed a moderated mediation model visualizing the relationship between professional knowledge and confidence for successful employment. Recommendations of early intervention targeting first-year students and different curriculum designing were proposed to facilitate planning in the acquisition of professional knowledge and the establishment of career goals, aiming to enhance the career development and success of tertiary vocational college students.

Authors

Publication Details

Journal
International Journal of Information Technology and Web Engineering
Published
2024-10-26
DOI
https://doi.org/10.4018/ijitwe.357698
Primary Topic
Higher Education and Employability
Type
article
Field-Weighted Citation Impact
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article

An Equation Model on the Professional Knowledge and Confidence for Future Employment of Students in Programs Supported With Emerging Technologies

Xifeng Liao
International Journal of Information Technology and Web Engineering
Higher Education and Employability
article

An Equation Model on the Professional Knowledge and Confidence for Future Employment of Students in Programs Supported With Emerging Technologies

Xifeng Liao
article en

Abstract

Students enrolled in interdisciplinary programs supported with modern information technologies may face more challenges in learning, because they must learn from at least two curricula, including courses of big data, new media technologies and intelligent platform use, etc. Taking students in these programs as an example, this study aims to investigate relationships among eight variables related to student career development. The research employed the quantitative method of Pearson bivariate analysis, ANOVA and Hayes (2017) regression procedure to test the direct and indirect relationship among variables. The researcher developed a moderated mediation model visualizing the relationship between professional knowledge and confidence for successful employment. Recommendations of early intervention targeting first-year students and different curriculum designing were proposed to facilitate planning in the acquisition of professional knowledge and the establishment of career goals, aiming to enhance the career development and success of tertiary vocational college students.

International Journal of Information Technology and Web EngineeringVol. 19(1)
Openalex Percentile: Top 74%
Higher Education and Employability
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