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Researchers have opined that the quality of commitment to pedagogical approaches by lecturers is one of the most important factors in determining student academic success. The purpose of this paper is to analyse the mediating effect of research informed teaching on the relationship between lecturer commitment to use of pedagogical approaches and teaching quality, with a view towards enabling delivery of high quality teaching and learning in HEIs.

The research is based on an online survey of the perception of 186 undergraduate and postgraduate students in four major UK universities. Covariance-based structural equation modelling (SEM) methodology was used to quantity and clarify the influence of lecturers' pedagogical attributes on teaching quality, mediated by research-informed teaching.

Findings reveal that: lecturers' pedagogical attributes have significant positive effect on teaching quality, research-informed teaching have significant positive effect on teaching quality, lecturers' pedagogical attributes have weak positive effect on research-informed teaching, and research-informed teaching partially mediates (indirect effect) the relationship between lecturers' pedagogical attributes and teaching quality.

Structural equation models are useful for clarifying concepts in pedagogy and have implications for education managers on how to improve teaching and learning in HEIs.

The paper presents a unique quantitative model for measuring the degree of teaching quality in universities.

The purpose of this paper is to investigate value co‐creation in assessing higher education (HE) teaching quality by acknowledging the influence of all interacting parties: teachers, students and general university service. The paper questions the appropriateness of student satisfaction surveys for assessing lecturer performance.

By introducing co‐creation and interaction between several stakeholders the paper deals with a complex problem which is best addressed through multiple approaches. The paper uses a literature review of HE quality together with empirical case study research of one university based on data from documents, student surveys and interviews with lecturers. The data are interpreted in the light of the recent theory of service (S‐D) logic and many‐to‐many marketing.

The paper highlights the complexity of HE service and recommends that EHEA assumes a co‐creation perspective. Resources are provided by lecturers, students and university service which require an interactive approach through which the parties integrate these resources. The information asymmetry between lecturers and students invalidates student satisfaction surveys as an instrument to assess teaching quality. The complexity of HE teaching cannot be boiled down to a single number that forms the ground for comparison between lecturers.

The paper offers a more valid perspective on HE quality by applying the concepts of value co‐creation and resource integration. It shows that the current one‐sided student evaluation of teachers is inadequate.

This chapter starts by interrogating the notion of teaching excellence. It then moves on to discussing some of the data sources currently used in Higher Education Institutions (HEIs) to monitor and measure the quality of teaching. What do these sources actually reveal about teaching excellence and how might we make better use of them? From large-scale national censuses like the National Student Survey (NSS) to institutional data sets such as teaching observations, the contribution that each source makes to our understanding of the quality of HE teaching is underexplored and contested. It is argued that there is a need for more transparent debate across HEIs and the sector as a whole about the benefits and limitations of such data as well as greater acknowledgement of the role of collaboration over competition. The chapter concludes that teaching excellence is a marketised misconception of the complex reality of the reciprocal relationship between teaching and learning. Contrary to policy rhetoric and far from encouraging an environment of collegial improvement, it introduces an unhelpful ethos of contrived competition into what is essentially an interdependent relationship underpinned by collective collaboration. It is by focusing attention on the latter where the real gains and insights are likely to be made.

Sketches a number of issues implicated in the assessment of teaching quality in higher education. Argues that checklist approaches to measuring teaching quality have some limited value – and a more professional, developmental approach is preferred. However, the focus on teaching quality should not disguise the fact that the emphasis needs to be on enhancing the quality of student learning, and this is not simply a function of the quality of the teaching which they encounter. Discusses implications both for academic departments and for universities, the claim being that systemic action is necessary.

Australian universities have a rich history for enabling, promoting and evaluating innovation and excellence in learning and teaching. Universities have used this practice to respond to drivers from government and the changing global educational environment, as well as accommodating for the characteristics of Australian universities such as scale, equity of access and the balance of domestic and international students. Often through institutional collaborations, educators have challenged pedagogical practices and introduced and tested innovative ways to enhance student learning, which has contributed to an international reputation for quality learning and teaching. However, the recent removal of specific government funding to support innovation, the increased emphasis on student success and employability outcomes and the threat of performance-based funding means that Australian universities will need to commit to the ongoing development of learning and teaching and demonstrate the potential for learning gain.

This chapter critically examines how recent government papers and policies have informed and contextualised the new Higher Education and Research Bill (HERB) passed in April 2017. In particular, it concerns itself with the issue of ‘teaching excellence’, through what has been termed the Teaching Excellence Framework (TEF) that has emerged as a key plank of the current government’s policy for future funding of higher education (HE). It will consider the other spurs for reform in HERB, such as the desire to create a culture in HE where teaching has equal status with research, the need to ensure that universities provide better information about their courses and the experiences that they can offer students and the predictable governmental requirement for institutions to give value for money and to be clearly held accountable for any failure to provide a quality service to students. Lastly, there is also a strong emphasis on widening student participation across the sector and ‘levelling the playing field’ so that new providers can set up with the minimum of red tape. It is interesting to note how each of these additional areas for reform is clearly linked to TEF, which, this chapter will argue, will be the key vehicle used to drive them forward.

Teaching and unit evaluations surveys are used to assess the quality of teaching and the quality of the unit of study. An analysis of teaching and unit evaluation survey practices in Australian universities suggests significant changes. One key change discussed in the paper is the shift from voluntary to mandatory use of surveys with the results used to assess and reward academic staff performance. The change in the direction is largely driven by the introduction of performance‐based funding as part of quality assurance arrangements. The paper aims to outline the current trends and changes and the implications in the future such as increased scrutiny of teaching and intrusion to academic autonomy.

The paper is based on the analysis of current teaching and unit evaluation practices across the Australian university sector. The paper presents the case of an Australian university that has introduced performance‐based reward using various measures to assess and reward academic staff such as the outcome of student satisfaction surveys. The analysis of external quality audit findings related to teacher and unit evaluations is also presented.

The findings suggest a shift in trend from the use of voluntary to mandatory tools to assess and reward quality teaching. The case of an Australian university outlined in the paper and the approach taken by seven other universities is largely driven by performance‐based funding. One of the key concerns for many in higher education is the intrusion of academic autonomy with increased focus on outcomes and less emphasis on resources needed to produce excellence in learning and teaching and research. The increased reliance on student happiness as a measure of educational quality raises the questions on whether high student satisfaction would strengthen academic rigour and student attainment of learning outcomes and generic skills which are seen as key factors in graduate exit standards.

The renewal of quality assurance and performance‐based funding using student satisfaction as a measure of educational quality will result in increased use of student voice to assess learning and teaching outcomes. Such direction will increase the accountability on academics to improve student experience and the measures will be used to assess academic staff performance.

The paper outlines the trends and changes in the teacher and unit evaluations in Australian universities and its implications in the future. The paper also provides a case of an Australian university that has recently made teacher and unit evaluations compulsory with the results used in academic staff annual performance review and linking reward with performance outcomes.

This paper explores some management concepts and how applying these concepts from business to higher education can be problematic, let alone incompatible, particularly in relation to measuring quality in higher education.

It provides a conceptual understanding of the literature on quality in the higher education context. It does so by examining the literature on students as customers, customer expectations, customer satisfaction and other management theories that have been applied to higher education.

It argues that the current bases for perceiving quality such as meeting customer expectations, satisfying the customer, ensuring quality control, meeting standards and assessing the cost associated with poor quality are in disagreement with the principal aims and measures of quality in higher education.

This paper can certainly benefit from many other concepts in business that have been applied in higher education, which it lacks. It only focussed on a number of key and popular ideas in management theory that have been used in higher education more broadly.

Student-focussed quality initiatives can be devoid of the student as customer concept. How programs, subjects and experiences are curated can be solely for the purpose of continuous improvement. Second, universities that choose to treat the student as a customer may find it beneficial to apply a relationship marketing approach to higher education. Lastly, those against the student as customer concept may focus on the long-term impact of quality initiatives such as promoting lifelong learning, building long-term relationships with alumni and employers and those that further promote academic integrity.

Some considerations have been offered. These considerations revisit the basic notions of teaching and learning in higher education. It puts an emphasis on sidestepping the student as customer metaphor, that learning is not expressed in dollar terms, and that the quality of the student experience cannot be measured by student evaluation alone because it is felt much later in life.

This paper aims to establish an 11‐step “improvement decision model” to enhance learning satisfaction.

This model integrates Kano's model and the relevant concepts for decision making, and puts forward an “improvement decision diagram and principles”. This paper also establishes “constructs of the learning satisfaction measurement” and a “teaching quality management cycle” to make it easy for instructors, administrators and students to jointly upgrade teaching quality.

The “improvement decision model” can effectively assist teachers to enhance their instructional materials and elevate student's learning satisfaction.

With enthusiastic participation of four instructors, the results of the case study are found to be satisfactory and support the applicability of the model proposed in this paper.

This study explored the effect of mathematics teaching quality on mathematics achievement among undergraduate students, using the SERVQUAL model.

The sample comprised of 320 first-year undergraduate students of a public university in Ghana. Structural equation modeling (SEM) was run in Amos (v.23) to test the various hypotheses.

The study concluded that the tangible aspect of the SERVQUAL model (service quality), which is very instrument in some service industries such as the airline, had no significant effect on mathematics achievement. Mathematics teaching reliability, responsiveness, assurance and empathy, however, had significant positive effects on mathematics achievement among undergraduate students.

The study assessed the effects of the individual dimensions of SERVQUAL on mathematics achievement, and it was realized that the tangible dimension had no significant effect. Tangibles may however compliment the other dimensions and is therefore imperative to also assess the effect of service quality (as a higher/second order variable) with the five dimensions as its first-order variables.

Human resources (lecturers) were seen as a strategic tool in enhancing students' academic performance and mathematics performance to be specific. Management of universities is therefore expected to invest in building, training and developing their human resources for an enhanced academic performance of students, especially in mathematics.

Although some past studies have applied SERVQUAL to teaching and learning researches, attention was largely focused on the measurement or assessment of teaching quality using SERVQUAL, with little attention on the effect of SERVQUAL on an outcome variable.