Beyond Digital Skills: Work-Integrated Learning, Adaptability, and the Thresholds for Graduate Work Readiness
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| Title: | Beyond Digital Skills: Work-Integrated Learning, Adaptability, and the Thresholds for Graduate Work Readiness |
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| Language: | English |
| Authors: | Despinur Dara (ORCID |
| Source: | Higher Education, Skills and Work-based Learning. 2026 16(3):616-630. |
| Availability: | Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Work Based Learning, Education Work Relationship, Digital Literacy, Undergraduate Students, Career Readiness, Adjustment (to Environment), Technological Literacy, Employment Potential, Foreign Countries |
| Geographic Terms: | Indonesia |
| DOI: | 10.1108/HESWBL-10-2025-0446 |
| ISSN: | 2042-3896 |
| Abstract: | Purpose: This study examines how work-integrated learning (WIL) contributes to graduate work readiness (WR) by distinguishing digital literacy (DL) as an upstream enabler and technological adaptability (TA) as the proximal driver. It further identifies the minimum capability thresholds required for readiness in a developing-country context. Design/methodology/approach: Data were collected from a cross-sectional survey of 520 Indonesian final-year undergraduates with at least three months of WIL. Covariance-based structural equation modelling (SEM) with robust maximum likelihood and bootstrapped indirect effects was used to test the hypothesised pathways. Necessary Condition Analysis (NCA) identified capability thresholds, while multi-group tests compared Social Sciences and STEM cohorts. Findings: WIL significantly enhanced both DL and TA; DL also strengthened TA. When modelled jointly, TA emerged as the strongest predictor of WR, while the direct DL-WR link was negligible. Mediation occurred only through the TA. NCA revealed practical thresholds: TA ˜2.25, DL ˜2.00, and WIL exposure ˜2.80 (four-point scale). These pathways proved stable across disciplinary fields. Practical implications: WIL should be designed to ensure students cross these thresholds by incorporating practice-rich tasks, mentoring, and structured reflection. Readiness should be assessed through adaptive performance rather than tool-based checklists. In Indonesia, where only 19% of young adults hold tertiary qualifications and fewer than 1% possess advanced digital skills, these mechanisms are crucial for aligning higher education with labour-market demands. Originality/value: The study advances an Adaptive Readiness Mechanism (ARM) in which WIL cultivates TA that drives WR, with DL scaffolding TA. By combining SEM and NCA, it contributes both explanatory and threshold-based insights, offering a portable framework for curriculum design, employer engagement, and policy development in volatile digital economies. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1505982 |
| Database: | ERIC |
| Abstract: | Purpose: This study examines how work-integrated learning (WIL) contributes to graduate work readiness (WR) by distinguishing digital literacy (DL) as an upstream enabler and technological adaptability (TA) as the proximal driver. It further identifies the minimum capability thresholds required for readiness in a developing-country context. Design/methodology/approach: Data were collected from a cross-sectional survey of 520 Indonesian final-year undergraduates with at least three months of WIL. Covariance-based structural equation modelling (SEM) with robust maximum likelihood and bootstrapped indirect effects was used to test the hypothesised pathways. Necessary Condition Analysis (NCA) identified capability thresholds, while multi-group tests compared Social Sciences and STEM cohorts. Findings: WIL significantly enhanced both DL and TA; DL also strengthened TA. When modelled jointly, TA emerged as the strongest predictor of WR, while the direct DL-WR link was negligible. Mediation occurred only through the TA. NCA revealed practical thresholds: TA ˜2.25, DL ˜2.00, and WIL exposure ˜2.80 (four-point scale). These pathways proved stable across disciplinary fields. Practical implications: WIL should be designed to ensure students cross these thresholds by incorporating practice-rich tasks, mentoring, and structured reflection. Readiness should be assessed through adaptive performance rather than tool-based checklists. In Indonesia, where only 19% of young adults hold tertiary qualifications and fewer than 1% possess advanced digital skills, these mechanisms are crucial for aligning higher education with labour-market demands. Originality/value: The study advances an Adaptive Readiness Mechanism (ARM) in which WIL cultivates TA that drives WR, with DL scaffolding TA. By combining SEM and NCA, it contributes both explanatory and threshold-based insights, offering a portable framework for curriculum design, employer engagement, and policy development in volatile digital economies. |
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| ISSN: | 2042-3896 |
| DOI: | 10.1108/HESWBL-10-2025-0446 |
