Evaluation of Soft Skills and Hard Skills in Readiness Testing among Electrical Engineering Education Students: A Quantitative Study on Engineering Students.

Saved in:

Bibliographic Details
Title:	Evaluation of Soft Skills and Hard Skills in Readiness Testing among Electrical Engineering Education Students: A Quantitative Study on Engineering Students.
Authors:	Rijanto, Tri¹ tririjanto@unesa.ac.id, Yudha, Rivo Panji¹ rivoyudha@unesa.ac.id
Source:	Educational Sciences: Theory & Practice. Jan2026, Vol. 26 Issue 1, p16-32. 17p.
Subject Terms:	Electrical engineering education, Technical education, Preparedness, Problem solving, Soft skills, Industry 4.0, Quantitative research
Geographic Terms:	Indonesia
Abstract:	This study evaluates the relationship between soft skills and hard skills readiness among Electrical Engineering Education students at Universitas Negeri Surabaya (UNESA), Indonesia, addressing the critical gap in quantitative assessment of these competencies within the Indonesian engineering education context amid Industry 4.0 demands. Rationale: The rapid technological transformation of Industry 4.0 necessitates comprehensive readiness assessment frameworks that evaluate both technical proficiencies and transferable competencies, yet existing literature reveals a scarcity of quantitative studies examining the specific interaction between soft and hard skills among engineering students in Indonesia. Methods: Using a causal correlational design grounded in Human Capital Theory and the Integrated Skills Framework, data were collected from 153 third and fourth-year students (95.6% response rate) through stratified random sampling. Two validated instruments the Soft Skills Measurement Instrument (IPSS, 35 items, a = 0.89) and Hard Skills Measurement Instrument (IPHS, 40 items, a = 0.87) were administered. Data analysis employed descriptive statistics, Pearson correlation, multiple regression, MANOVA, and Structural Equation Modeling (SEM) using Jamovi and LISREL software. Results: Professional ethics (M = 81.53) and teamwork (M = 78.91) emerged as the strongest soft skills, while electrical fundamentals (M = 75.47) was the strongest hard skill. Programming demonstrated the lowest readiness (M = 63.51) with highest variability. Cognitive soft skills particularly problem-solving (ß = 0.37, p < .001) and critical thinking (ß = 0.29, p = .004) significantly predicted technical competence, explaining 46.1% of variance in hard skills performance. Students with internship experience demonstrated significantly higher proficiency across both domains (p < .01). The SEM revealed cognitive soft skills directly influenced all hard skills dimensions (ß = 0.39 to 0.53, p < .001), with the model explaining 67.3% of variance in overall workplace readiness. Limitations: The cross-sectional design limits causal inference; the single-institution sample may constrain generalizability to other Indonesian universities. Recommendations: Engineering curricula should integrate problem-solving development within technical courses, expand internship opportunities, and strengthen programming instruction. Future research should employ longitudinal designs and multi-institutional samples. [ABSTRACT FROM AUTHOR]
	Copyright of Educational Sciences: Theory & Practice is the property of EDAM- Education Consultancy Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Education Research Complete

Description
Abstract:	This study evaluates the relationship between soft skills and hard skills readiness among Electrical Engineering Education students at Universitas Negeri Surabaya (UNESA), Indonesia, addressing the critical gap in quantitative assessment of these competencies within the Indonesian engineering education context amid Industry 4.0 demands. Rationale: The rapid technological transformation of Industry 4.0 necessitates comprehensive readiness assessment frameworks that evaluate both technical proficiencies and transferable competencies, yet existing literature reveals a scarcity of quantitative studies examining the specific interaction between soft and hard skills among engineering students in Indonesia. Methods: Using a causal correlational design grounded in Human Capital Theory and the Integrated Skills Framework, data were collected from 153 third and fourth-year students (95.6% response rate) through stratified random sampling. Two validated instruments the Soft Skills Measurement Instrument (IPSS, 35 items, a = 0.89) and Hard Skills Measurement Instrument (IPHS, 40 items, a = 0.87) were administered. Data analysis employed descriptive statistics, Pearson correlation, multiple regression, MANOVA, and Structural Equation Modeling (SEM) using Jamovi and LISREL software. Results: Professional ethics (M = 81.53) and teamwork (M = 78.91) emerged as the strongest soft skills, while electrical fundamentals (M = 75.47) was the strongest hard skill. Programming demonstrated the lowest readiness (M = 63.51) with highest variability. Cognitive soft skills particularly problem-solving (ß = 0.37, p < .001) and critical thinking (ß = 0.29, p = .004) significantly predicted technical competence, explaining 46.1% of variance in hard skills performance. Students with internship experience demonstrated significantly higher proficiency across both domains (p < .01). The SEM revealed cognitive soft skills directly influenced all hard skills dimensions (ß = 0.39 to 0.53, p < .001), with the model explaining 67.3% of variance in overall workplace readiness. Limitations: The cross-sectional design limits causal inference; the single-institution sample may constrain generalizability to other Indonesian universities. Recommendations: Engineering curricula should integrate problem-solving development within technical courses, expand internship opportunities, and strengthen programming instruction. Future research should employ longitudinal designs and multi-institutional samples. [ABSTRACT FROM AUTHOR]
ISSN:	26305984
DOI:	10.12738/jestp.2026.1.02