Student evaluation of teaching (SET) is important for assessing university instructors' performance. However, this system seems biased as students' grade expectations result in rewards or penalties in SET. As a fair evaluation of grades became difficult during the COVID-19 pandemic, universities implemented a relaxed grade policy that expanded the…

Across the international higher education sector, existing studies highlight that student evaluations of courses and teaching are biased and prejudiced towards academics and can cause mental distress. Yet student evaluation data is often used as part of faculty hiring, firing, promotion, award and grant decisions. That a data source known to be…

For students to sustain their learning beyond higher education, it is important for them to develop their evaluative judgement. Although the importance of evaluative judgement is well-established, the process through which students make such judgements remains contested. This study explores students' evaluative judgement process by asking 20…

This paper explores institutional leaders' perceptions of learning and teaching involved in facilitating and assessing Student Evaluations of Teaching (SET) survey instruments across Australian regional universities. It focuses on how they understand the function of SET, strategies used to mitigate bias, and potential residual harm. Through…

Student evaluations of teaching may be subject to halo effects, where answers to one question are contaminated by answers to the other questions. Quantifying halo effects is difficult since correlation between answers may be due to underlying correlation of the items being tested. We use a novel identification procedure to test for a halo effect…

Despite its name, the halo effect in student evaluation of teaching (SET) response is not mystical. Halo in SET results from psychological processes that undermine SET validity, particularly for summative evaluation (pay decisions, etc.). These processes span psychological concepts of cognition, motivation and affect. This paper demonstrates that…

Scholarly debate about student evaluations of teaching (SETs) often focuses on whether SETs are valid, reliable and unbiased. In this article, we assume the most optimistic conditions for SETs that are supported by the empirical literature. Specifically, we assume that SETs are moderately correlated with teaching quality (student learning and…

Much is made of students generally rating assessment lower than other aspects of their educational experience. It is frequently cited in research literature as evidence for a general crisis in assessment, and it strongly influences institutional enhancement efforts and media coverage of student feedback. Focusing on the UK's National Student…

The method of normalisation combined with peer ratings is utilised to provide the solution to the biased rating problem of mapping group work marks to individual marks. We critically evaluate the method of normalisation following the findings of an article which argued against the use of self and/or peer rating mechanism. We demonstrate that the…

Research project modules are a key part of UK undergraduate and postgraduate bioscience degree programmes. Report marking invariably uses two assessors, but marking models are mixed with some institutions using two independent markers and others using the project supervisor as one of the assessors. This latter model is controversial with critics…

Quantitative student evaluations of teaching (SET) and assessments are widely used in higher education as a proxy for teaching quality. However, SET are a function of individual rating behaviours resulting from student background, knowledge and personalities, as well as the learning experience being rated. SET from three years of data from a…

Assessment and learning analytics both collect, analyse and use student data, albeit different types of data and to some extent, for various purposes. Based on the data collected and analysed, learning analytics allow for decisions to be made not only with regard to evaluating progress in achieving learning outcomes but also evaluative judgments…

This article presents the first-ever big data study of the student evaluation of teaching (SET) using artificial intelligence (AI). We train natural language processing (NLP) models on 1.6 million student evaluations from the US and the UK. We address two research questions: (1) are these models able to predict student ratings from the student…

To advance the discussion on the validity of student evaluations of university teaching, student ratings of two teaching dimensions -- student involvement and rapport -- were compared with corresponding observer ratings. Seven potential bias variables were tested with regard to their impact on the students' teaching assessment: three teacher…

Group projects are widely used in higher education, but they can be problematic if all group members are given the same grade for a project to which they might not have contributed equally. Most scholars recommend addressing these problems by awarding individual grades, computing some kind of individual weighting factor (IWF) from peer and…