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The purpose of this paper is to examine evaluations of teaching from viewpoints of lecturers and students to reveal perceived differences in teaching performance.

A survey is administered to lecturers and students in a large‐scale university in Taiwan. Valid samples include ten lecturers and 250 students. Upon obtaining consensuses from lecturers, 25 students in each course are randomly selected to fill out questionnaires. Lecturers are requested to fill out questionnaires designed for instructors only. Factor, cluster, and multivariate analyses of variance are applied in analyzing the survey data. Five dimensions of evaluations of teaching are extracted from students' viewpoints, including content of materials, learning condition, interaction, attitudes, and responsiveness. These five factors are used in the clustering procedure to segment courses into superior‐ and inferior‐quality.

Results indicate surveyed students in the clusters of superior‐ and inferior‐quality courses have statistical differences in seriousness of evaluations of teaching performance and how they believe the suggestions will be taken into consideration in modifications of teaching styles. However, lecturers of superior‐ and inferior‐quality courses are not statistically different in their viewpoints in how they value evaluations of teaching performance.

Survey data in this paper are obtained from a single university. Students are able to distinguish courses of different quality in various dimensions, but lecturers seem to believe that they have done well in teaching and will not know differences in teaching performance perceived by students as of superior‐or inferior‐quality.

For efficient utilization of student evaluations of teaching in educational institutions, gaps in perceived differences in teaching performance from lecturers and students need to be identified and filled.

End‐of‐term student evaluations of teaching are used in educational institutions for assessing how well instructors do in helping students to learn theoretical and practical aspects of knowledge. Findings in this paper can be used to form a baseline for educational institutions to improve applicability of student evaluations of teaching.

This article examines the perceptions of both administrators and faculty relating to the validity of student evaluations and the existence of possible biasing factors. The results indicate that administrators believe student evaluations measure teaching effectiveness to a greater degree than faculty, while faculty members believe their personality is the primary determinant of ratings on student evaluations. Faculty also believe that the type of course, the work load of a course, and the grade distribution of a course have a larger impact on student evaluations when compared with administrators’ beliefs.

Because of the potential cost savings that online teaching evaluations can deliver, many universities are converting their student evaluations of teaching to this mode of administration. In this study, we examine the effects of transitioning administration of student evaluations from paper-and-pencil to online. We use data from accounting and other departments in the College of Business Administration of a large private, research university that converted from paper to online administration of teaching evaluations. We examine the average teaching effectiveness rating and response rate for instructors who taught the same course before and after the conversion. In addition, we survey a sample of accounting students to investigate their responses to online teaching evaluations. We find a significant increase in the average effectiveness rating and a significant decrease in response rate. Furthermore, we find that those instructors with lower ratings under the paper administration experience the greatest increase in ratings when the evaluations are converted to online administration. In a follow-up survey, we find that students who are highly motivated and have higher grade point averages are more likely to complete and provide higher evaluations with the online administration. We discuss the implications of our results to accounting and business education literature.

The purpose of this paper is to propose a framework for the analysis of students’ ratings of teaching quality in higher education and the disclosure of risky issues undermining the quality of teaching and courses that require attention for continuous improvement. The framework integrates two decision-based methods: the standardized u-control chart and the ABC analysis using fuzzy weights. The control chart, using the students’ ratings, allows the identification of those courses requiring an improvement of teaching quality in the short-medium term. While the ABC analysis uses fuzzy weights to deal with the vagueness and uncertainty of students’ teaching evaluations and provides a risk map of the potential areas of teaching performances improvement in the long term. The proposed framework allows the identification of teaching and course quality aspects that need corrective actions in response to students’ criticisms in accordance with different levels of priority.

This study adopts two methods, commonly used in industrial applications, i.e. the u-control chart and ABC analysis. Combining the results of a literature review on teaching evaluation and the application of these two methods as building blocks for the assessment, a framework to detect potential risks reducing teaching quality in higher education is proposed. The application of the framework is shown through an action-based case study developed in an Italian public university.

The study proposes a framework that combines two methods, i.e. u-control chart and ABC analysis with fuzzy weights, to support the assessment of teaching and course quality. The framework is proposed as an assessment approach of the teaching performance in higher education with the purpose to continuously improve the quality of teaching and courses both in the short, medium and long term.

The study provides an original contribution to the understanding of how to analyze students’ evaluation of teaching performance in order to take proper and timely decisions on corrective actions in response to the need of continuously improving the level of teaching and course quality.

This chapter offers a discussion of the increasingly widespread use of student evaluations in higher education. It critiques the extent to which these student evaluations are now regarded by governments and higher education management as an authoritative source of information on all aspects of HE provision, with a particular focus on their use to rank and evaluate teaching excellence through the Teaching Excellence Framework. It provides an overview of research looking into how student perceptions of teachers' teaching excellence, or otherwise, play out very differently depending on the gender, age and social class of the lecturers doing the teaching. This chapter argues that these differences make it difficult to ensure that students' assessment of higher education teaching are fair and/or consistent with regard to the teaching they are experiencing across different courses, disciplines and institutions. It concludes that acknowledging how inequalities will inevitably play a part in any evaluative processes is a more productive way of thinking about how more informed indices of teaching quality might be more usefully understood and operationalised in higher education. This approach, however, requires HEI's to recognise the ways in which existing racialised, sexualised and gendered patterns reoccur and sustain inequalities currently in the UK higher education sector. (199)

Investigates the factors affecting student evaluation of teaching (SET). A total of 170 teaching evaluations conducted at the Nanyang Business School (Singapore) were analysed by regressing the overall teaching index on the following variables: subject characteristics (stream, year and type), class characteristics (format, size, time and day), evaluation characteristics (response, time and day), and teacher characteristics (age, gender and rank). Indicates that better teaching evaluation is associated with a smaller class size and a larger number of evaluation responses. Also, teachers of middle‐level subjects receive relatively poorer SET results. Further, SET administered in the later part of the week attract better student evaluation. Finds that teacher characteristics have no significant impact on SET results. Confirms the existence of potential biasing factors, hence, SET should be used with caution and not be the only method of evaluating teachers.

To report study findings on teaching effectiveness and feedback mechanisms in Kenyan universities, which can guide management in developing a comprehensive quality control policy.

The study adopted an exploratory descriptive design. Three public and two private universities were randomly selected to participate in the study. A random sampling procedure was also used to select 79 respondents to participate in the research. A questionnaire administered in all participating universities was the main instrument for data collection.

There was no clear university policy on the evaluation of teaching effectiveness, despite its importance in quality control. Student evaluation of teaching effectiveness (SETE) was found to be unreliable, although widely used where evaluation existed, without other evaluation support systems. Feedback from the evaluation, though crucial in professional improvement, was not made available to the respondents.

The study examined the evaluation of teaching effectiveness from the lecturers' perspectives. Further research may provide insights into the contribution of SETE to teaching effectiveness from the students' standpoint.

Use of a variety of evaluation tools (e.g. self, peer) rather than relying solely on SETE is necessary. Comprehensive and usable information may be provided for effective teaching. Universities should provide clear policy guidelines on quality control for faculties to develop multiple teaching effectiveness evaluation instruments.

Teaching evaluation is important in order to bring about an improvement in areas such as student achievement, and use of public funds or educational materials. The findings provide critical information for management decision making to assist universities to translate the resources at their disposal into learning outcomes.

This paper aims to take Chinese university teachers as the research objects to examine their self-evaluation of online teaching and analyze the main factors influencing their evaluation during COVID-19.

According to the theory of educational ecology, the factors influencing teachers' self-evaluation of online teaching in this paper include university background, courses background and teachers' personal background from the macro- to micro-levels. Through exploratory factor analysis, independent sample T-test and one-way analysis of variance (ANOVA), the self-evaluation of online teaching of 13,997 teachers from 334 universities and their relationship with teachers' background have been subject to data statistics and analysis.

Teachers' self-evaluation of online teaching mainly includes three dimensions: online teaching methods, online teacher–student interaction and online teaching techniques. There are significant differences in these three dimensions among teachers with different background characteristics, including regions, the types of universities, the nature of universities in macro background levels, the types and numbers of online courses in meso background levels, and the gender, years of teaching, professional titles and disciplines in micro background levels.

To improve teachers' self-evaluation of online teaching, it is suggested to build an online teaching self-evaluation system for teachers, strengthen university support and guarantee, strengthen online teaching training and improve the information accomplishments of teachers.

This large-scale empirical survey of online teaching evaluation of Chinese teachers can provide scholars with a deeper understanding of the implementation of online teaching in China and the self-evaluation of online teaching by teachers.