A FRAMEWORK TO SUPPORT ENGINEERING STUDENTS' LEARNING FOR INDUSTRY 4.0

Tan, SY (2025) A FRAMEWORK TO SUPPORT ENGINEERING STUDENTS' LEARNING FOR INDUSTRY 4.0. Doctoral thesis, Liverpool John Moores University.

Preview

Text 2025tanphd.pdf - Published Version Available under License Creative Commons Attribution Non-commercial. Download (2MB) | Preview

Abstract

Industry has been undergoing intensive technological developments, such as sensors, autonomous robots and intelligent networks, at an unprecedented pace over the last few decades. This rapidly changing world requires higher education institutions and industrial organisations to adapt. Considering this challenge, this thesis highlighted a mismatch between industry’s expectations, Engineering students’ expectations and graduates’ readiness in the United Kingdom. The current technological landscape has made student readiness a critical issue, prompting an investigation into the factors that contributed to the readiness of Engineering students for industry 4.0. The research methodology used to guide the research is Design Science Research. This research used pragmatic approach and mixed-method research to find out the different criteria that contribute to the readiness of students for industry 4.0. This study introduced “ASK SUMA” as a novel learning framework designed to facilitate integration with industry 4.0 by focusing on learning processes. Specifically, ASK SUMA used self-directed learning, a key pillar of active learning, to support students in analysing their needs and monitoring their progress through self-review. This framework also assessed technical skills and attitude using maturity levels. The research found out that readiness of Engineering students for industry 4.0 could be enhanced if students had high level of skills and positive learning attitude. The findings were then translated into a framework and data on skill levels were collected before and after implementing the framework. Findings revealed that the proposed framework supported individual learners by focusing on their self-directed learning and awareness. In addition, the proposed learning process was essential for students’ development as future graduates, supporting them to emerge as flexible, proactive, and adaptive professionals in a workplace defined by constant change. Future work will involve implementing the ASK SUMA framework with lecturers and will also investigate integrating this framework with artificial intelligence.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	industry 4.0; learning framework; self-directed learning; skills; attitude
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science and Mathematics
Date of acceptance:	27 May 2025
Date of first compliant Open Access:	25 June 2025
Date Deposited:	25 Jun 2025 12:04
Last Modified:	25 Jun 2025 12:04
DOI or ID number:	10.24377/LJMU.t.00026610
Supervisors:	Al-Jumeily OBE, D and Assi, S
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26610

View Item