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Assessment of Quantity Surveying Student Readiness for Industry through Students’ Industrial Work Experience Scheme (SIWES)

Taiwo Fadeke Adegbembo&, Oluwaseun Israel Olowo, Ibukun Oluwadara Famakin

  1. Department of Construction Mangement and Quantity Surveying, University of Johannesburg, South Africa; Department of Quantity Surveying, Federal University of Technology Akure, Ondo State, Nigeria

SURE-Built 2026 — 2nd Global Scholarship for Sustainable Built Environment Research Conference · Education in the Built Environment · September 3, 2026

Abstract

The readiness of students for professional practice in quantity surveying has become a central concern in bridging the gap between academia and industry. The purpose of this research is to assess the impact of Students’ Industrial Work Experience Scheme (SIWES) on Industry readiness of quantity surveying students in Nigeria. The study adopted quantitative research design approach where data for the study was collected using a structured questionnaire. This was administered to students, and industry professionals. The respondents were conveniently sampled and responses where gathered both physically and via Google forms. 180 questionnaires were distributed, out of which 134 were received; giving a response rate of 74.44%. The data gathered were analysed using descriptive and inferential statistical tools such as mean item score, standard deviation, t-test, while Cronbach's Alpha was employed to test reliability. The results of the analysis indicated that SIWES significantly enhances student readiness, particularly in core technical and workplace skills such as billing knowledge, teamwork, and the ability to carry out expected tasks, though areas such as problem-solving and taking constructive criticism require further strengthening. The findings of this study reveal that universities and industry stakeholders strengthen practical exposure, research partnerships, and policy-level collaborations to enhance the professional readiness of future quantity surveyors. Impact of GenAI-Powered Adaptive Learning Environments on Student-

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