Kasun Gomis, M. Saini, C. Pathirage, Mohammed Arif
{"title":"提高英国高等教育建筑环境中的教学质量","authors":"Kasun Gomis, M. Saini, C. Pathirage, Mohammed Arif","doi":"10.1108/qae-03-2022-0072","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe 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.\n\n\nDesign/methodology/approach\nThe 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.\n\n\nFindings\nThe 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.\n\n\nPractical implications\nThe 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.\n\n\nOriginality/value\nNew 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.\n","PeriodicalId":46734,"journal":{"name":"QUALITY ASSURANCE IN EDUCATION","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Enhancing quality of teaching in the built environment higher education, UK\",\"authors\":\"Kasun Gomis, M. Saini, C. Pathirage, Mohammed Arif\",\"doi\":\"10.1108/qae-03-2022-0072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe 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.\\n\\n\\nDesign/methodology/approach\\nThe 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.\\n\\n\\nFindings\\nThe 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.\\n\\n\\nPractical implications\\nThe 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.\\n\\n\\nOriginality/value\\nNew 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.\\n\",\"PeriodicalId\":46734,\"journal\":{\"name\":\"QUALITY ASSURANCE IN EDUCATION\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"QUALITY ASSURANCE IN EDUCATION\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/qae-03-2022-0072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"QUALITY ASSURANCE IN EDUCATION","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/qae-03-2022-0072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Enhancing quality of teaching in the built environment higher education, UK
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.
期刊介绍:
QAE publishes original empirical or theoretical articles on Quality Assurance issues, including dimensions and indicators of Quality and Quality Improvement, as applicable to education at all levels, including pre-primary, primary, secondary, higher and professional education. Periodically, QAE also publishes systematic reviews, research syntheses and assessment policy articles on topics of current significance. As an international journal, QAE seeks submissions on topics that have global relevance. Article submissions could pertain to the following areas integral to QAE''s mission: -organizational or program development, change and improvement -educational testing or assessment programs -evaluation of educational innovations, programs and projects -school efficiency assessments -standards, reforms, accountability, accreditation, and audits in education -tools, criteria and methods for examining or assuring quality