Enhancing quality of teaching in the built environment higher education, UK

Gomis, K, Saini, M, Pathirage, C and Arif, M 2022, 'Enhancing quality of teaching in the built environment higher education, UK' , Quality Assurance in Education .

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Abstract

Purpose
The issues in the current Built Environment Higher Education (BEHE) curricula recognise a critical need for enhancing the quality of teaching. This paper aims to identify the need for a best practice in teaching within BEHE curricula and recommend a set of drivers to enhance the current teaching practices in the Built Environment (BE) education. The study focused on Section 1 of the National Student Survey (NSS) – Teaching on my course, with a core focus on improving student satisfaction, making the subject interesting, creating an intellectually stimulating environment and challenging learners.

Design/methodology/approach
The research method used in this study is the mixed method, a document analysis consisting of feedback from undergraduate students and a closed-ended questionnaire to the academics in the BEHE context. More than 375 student feedback were analysed to understand the teaching practices in BE and fed forward to developing the closed-ended questionnaire for 23 academics, including a Head of School, a Principal Lecturer, Subject Leads and Lecturers. The data was collected from Architecture, Construction Management, Civil Engineering, Quantity Surveying and Building surveying disciplines representing BE context. The data obtained from both instruments were analysed with content analysis to develop 24 drivers to enhance the quality of teaching. These drivers were then modelled using the interpretive structural modelling (ISM) method to identify their correlation and criticality to NSS Section 1 themes.

Findings
The study revealed 10 independent, 11 dependent and three autonomous drivers, facilitating the best teaching practices in BEHE. The study further recommends that the drivers be implemented as illustrated in the level partitioning diagrams under each NSS Section 1 to enhance the quality of teaching in BEHE.

Practical implications
The recommended set of drivers and the level partitioning can be set as a guideline for academics and other academic institutions to enhance the quality of teaching. This could be further used to improve student satisfaction and overall NSS results to increase the rankings of academic institutions.

Originality/value
New knowledge can be recognised with the ISM analysis and level partitioning diagrams of the recommended drivers to assist academics and academic institutions in developing the quality of teaching.

Item Type: Article
Schools: Schools > Salford Business School > Salford Business School Research Centre
Schools > Salford Business School
Journal or Publication Title: Quality Assurance in Education
Publisher: Emerald
ISSN: 0968-4883
Depositing User: M Saini
Date Deposited: 22 Jul 2022 16:03
Last Modified: 17 Aug 2022 08:45
URI: https://usir.salford.ac.uk/id/eprint/64158

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