Enhancing Vocational Graduate Employability through Mobile Application on Advanced Quantitative Modeling of Skills and Partnerships
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| Title: | Enhancing Vocational Graduate Employability through Mobile Application on Advanced Quantitative Modeling of Skills and Partnerships |
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| Language: | English |
| Authors: | Yang Wang (ORCID |
| Source: | Turkish Online Journal of Educational Technology - TOJET. 2026 25(1):92-102. |
| Availability: | Sakarya University. Esentepe Campus, Adapazari 54000, Turkey. Tel: +90-505-2431868; Fax: +90-264-6141034; e-mail: tojet@sakarya.edu.tr; Web site: https://tojet.net/ |
| Peer Reviewed: | Y |
| Page Count: | 11 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Foreign Countries, Employment Potential, Career and Technical Education, College Students, Handheld Devices, Computer Oriented Programs, Job Skills, Soft Skills, Education Work Relationship, Career Guidance, Technological Literacy, Influences |
| Geographic Terms: | China |
| ISSN: | 1303-6521 2146-7242 |
| Abstract: | This study investigates the multidimensional factors influencing employability among vocational students in China by applying an advanced quantitative framework. Data were collected from 17 experts, 100 faculty members, and 30 students, and analyzed using a sequential process of Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). EFA extracted six constructs-Professional Skills, Soft Skills, Career Guidance, Industry-Academia Collaboration, Technological Literacy, and Employability Outcomes-explaining 72.6% of total variance. CFA confirmed measurement validity and reliability (Cronbach's [alpha] > 0.80; CR > 0.84; AVE > 0.50; HTMT < 0.85). SEM results demonstrated that all hypothesized relationships were supported, with Soft Skills ([beta] = 0.35) identified as the strongest predictor of employability, followed by Professional Skills ([beta] = 0.29), Technological Literacy ([beta] = 0.24), Industry-Academia Collaboration ([beta] = 0.21), and Career Guidance ([beta] = 0.18). Mediation analysis revealed that Career Guidance indirectly influenced employability through Soft Skills ([beta] = 0.12, p < 0.01), while moderation analysis confirmed that Industry-Academia Collaboration enhanced the effect of Professional Skills on employability ([beta] = 0.09, p < 0.05). The structural model accounted for 68% of variance (R[superscript 2] = 0.68) in employability outcomes, demonstrating strong explanatory power. The novelty of this research lies in integrating mediation and moderation mechanisms within a validated employability model, moving beyond traditional exploratory methods. Conceptually, the findings highlighted the centrality of Soft Skills in determining employability, challenging the dominance of technical training in vocational education. Practically, the study provides evidence-based recommendations for balancing technical and soft skill training, strengthening career guidance services, and deepening industry-academia partnerships to enhance graduate competitiveness in dynamic labor markets through a Mobile Application on Advanced Quantitative Modeling of Skills and Partnerships. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1497771 |
| Database: | ERIC |
| Abstract: | This study investigates the multidimensional factors influencing employability among vocational students in China by applying an advanced quantitative framework. Data were collected from 17 experts, 100 faculty members, and 30 students, and analyzed using a sequential process of Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). EFA extracted six constructs-Professional Skills, Soft Skills, Career Guidance, Industry-Academia Collaboration, Technological Literacy, and Employability Outcomes-explaining 72.6% of total variance. CFA confirmed measurement validity and reliability (Cronbach's [alpha] > 0.80; CR > 0.84; AVE > 0.50; HTMT < 0.85). SEM results demonstrated that all hypothesized relationships were supported, with Soft Skills ([beta] = 0.35) identified as the strongest predictor of employability, followed by Professional Skills ([beta] = 0.29), Technological Literacy ([beta] = 0.24), Industry-Academia Collaboration ([beta] = 0.21), and Career Guidance ([beta] = 0.18). Mediation analysis revealed that Career Guidance indirectly influenced employability through Soft Skills ([beta] = 0.12, p < 0.01), while moderation analysis confirmed that Industry-Academia Collaboration enhanced the effect of Professional Skills on employability ([beta] = 0.09, p < 0.05). The structural model accounted for 68% of variance (R[superscript 2] = 0.68) in employability outcomes, demonstrating strong explanatory power. The novelty of this research lies in integrating mediation and moderation mechanisms within a validated employability model, moving beyond traditional exploratory methods. Conceptually, the findings highlighted the centrality of Soft Skills in determining employability, challenging the dominance of technical training in vocational education. Practically, the study provides evidence-based recommendations for balancing technical and soft skill training, strengthening career guidance services, and deepening industry-academia partnerships to enhance graduate competitiveness in dynamic labor markets through a Mobile Application on Advanced Quantitative Modeling of Skills and Partnerships. |
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| ISSN: | 1303-6521 2146-7242 |
