Feedback is integral to second language (L2) writing instruction. However, large class sizes and limited teacher time often challenge the delivery of personalized feedback, prompting interest in AI-powered solutions such as ChatGPT (Escalante et al., 2023; Huete-García & Tarp, 2024; Steiss et al., 2024; Yoon et al., 2023; Zhang, 2024). This study evaluates a task-customized GPT model, “Belinda,” trained to assess A1-level Spanish learners’ writing and provide feedback. Two research questions guided the investigation: (1) Can Belinda accurately score beginner Spanish writing using a provided rubric? (2) Can Belinda deliver constructive qualitative feedback? Human and GPT-generated scores were compared for inter- and intrarater reliability, and qualitative analyses categorized the feedback for usability in the classroom. Results revealed moderate alignment between Belinda’s scores and human raters, though reliability of the GPT fell short of calibration benchmarks. Feedback quality varied, with Belinda often providing vague, incomplete, or inaccurate suggestions. Despite iterative training, the GPT struggled to balance error correction with encouragement, a critical need for novice learners. Additionally, inconsistencies in identical GPT versions raised concerns about reliability. While Belinda showed potential in automating feedback, its limitations in accuracy, contextual understanding, and positivity suggest it is not yet a viable substitute for human evaluation by itself. These findings emphasize the challenges of integrating AI into L2 instruction and call for the need for extensive datasets, robust training, and human–AI collaboration to achieve pedagogically sound outcomes. Future research should explore hybrid feedback models and scalable solutions to enhance AI’s role in language education without compromising learner progress or confidence.

The provision of high-quality feedback is crucial to student experience, but it is increasingly challenging for academic staff to fully meet student expectations. One response is to use simple, freely available screen capture technology to offer individual video assessment feedback at no extra cost to staff time. This article will outline exactly how this relatively new technology can be harnessed and how students have responded to feedback delivery in this form at the University of Reading. The article will argue that screen capture software has significant potential to enhance the student experience of feedback provision but is currently highly underutilised in UK Higher Education.

Existing literature has focused on the influence of organizational settings on volunteers’ intention to remain but failed to explore the effects of external feedback. From an integrated perspective of task design and feedback, this study, based on the affective events theory, explored the influencing mechanism of illegitimate tasks, recipients’ feedback, and emotional exhaustion on volunteers’ intention to remain. This study collected 649 cases from poverty alleviation volunteers. Results showed that illegitimate tasks have had a negative impact on their intention to remain with emotional exhaustion taking a certain mediating effect. It has also been noted that the moderating effect of recipients’ feedback is significant, which can alleviate the negative impact of emotional exhaustion on the intention to remain. This study indicated the positive effects of positive and negative feedback, enriched the research on the influencing factors of volunteers’ intention to remain, and provided suggestions for organizations to retain volunteers from an integrated perspective of task design and feedback.

The use of simulations in European Studies is becoming more widespread, given the possibilities of immersing students in complex issues and building substantive knowledge and affective understanding. We identify a number of barriers to the full realisation of this potential. Drawing on observations from various games, it is suggested that for a successful simulation there must be: learning objectives clear to all participants; alignment between those objectives, game play and assessment; and a meaningful feedback process.

There is now a rich pedagogical literature that attests to the absolute centrality of assessment and feedback in effective student learning at undergraduate and postgraduate levels. And yet – despite this consensus in the pedagogical literature over the crucial importance of assessment and feedback – they are not, it seems, fulfilling their purpose or potential for students or lecturers alike. This symposium starts from the premise that assessment and feedback matter, that they are not working at present and that we need to find ways to do them differently. The symposium brings together five original articles from contributors who all want to explore alternative ways of thinking about, and doing, assessment and/or feedback so that they work better both for our students and for us as their lecturers.

This article evaluates the use of audio feedback on assignments through the case study of a politics course and argues that audio feedback provides a more personal feel to feedback. Criticism, it appears, is easier to accept in the spoken word. In addition, the article highlights the chief practical benefit of audio feedback, namely that it reduces the overall time spent by lecturers in providing comments. But while the article is positive in favour of audio feedback, it also discusses some potential challenges that include anonymous marking and the fact that one size does not fit all, with different students preferring different types of feedback. Finally, the article identifies a number of practical tips that relate to the adoption of this method of feedback.

Research undertaken on student feedback has pointed to the difficulties that students have in understanding written feedback. However, little attention has been given to understanding student views on verbal feedback. This article aims to fill this gap by reporting on the findings of verbal feedback practices among 114 History, Politics and International Relations students obtained from a questionnaire survey. These findings were supported by five in-depth semi-structured interviews. The findings show variance in student views with regard to different aspects of verbal feedback. The research outlines a number of suggestions that assist in developing verbal feedback opportunities further. It is argued that ‘feedback-dialogues’ provide a mechanism for improving student understanding of feedback.

Despite attempts by higher education institutions to improve the quality of feedback on assessed work, dissatisfaction expressed by students remains visible. This article draws upon the preliminary findings of a Higher Education Academy Collaborative Research Project on assessment feedback within two large political science and international relations departments. It offers a critical review of current feedback practices and processes and identifies four key issues – negativity, transferability, intelligibility, and consistency – that require attention in order to deliver more effective assessment feedback. The article also suggests practical ways forward in addressing these issues, highlighting in particular the importance of both structure and timing in helping to produce high-quality feedback efficiently.

With research showing the benefits of feedback, teachers have come under increasing pressure to provide more, including more personalised, and more detailed responses to students. This often places heavy demands on teachers and with ever-larger class sizes and heavier workloads, teacher fatigue and burn-out are common. Automation has the potential to change all this and new digital resources have already proven to be valuable in supporting L2 writing. In this paper I look at the contribution of Automated Writing Evaluation (AWE) programmes and Generative Artificial Intelligence (GenAI) to feedback. The ability to provide instant local and global feedback across multiple drafts targeted to student needs and in greater quantities promises to increase learner motivation and autonomy while relieving teachers of hours of marking. But haven’t we heard this all before? Are these empty claims which raise our expectations of removing some of the drudgery of mundane grammar correction? Most importantly, what is the role of teachers in all this, and can AI really improve writers and not just texts?

In recent years, there has been an increasing interest in motivated memory as a psychological determinant of economic outcomes. According to motivated memory, people tend to better recall pleasant information because it serves their psychological needs. Another phenomenon, however, predicts the same pattern: According to mood congruence, pleasant information is easier to recall for individuals in nonnegative mood, regardless of any psychological needs. Since most people tend to have some need for self-esteem and to experience more positive than negative feelings during the day, the two phenomena predict similar outcomes in most ordinary situations, but not all. To test the predictive power of these two phenomena, we collect data from a laboratory experiment and from a nationally representative survey. We study how individuals in a temporarily induced negative mood (via a video clip) or those who report a low baseline mood (relative to the population) recall negative feedback. Our results meet the predictions of motivated memory: Individuals better recall positive than negative feedback, even when they are in negative mood. Motivated memory is not just a matter of mood.

While research shows that public preferences across policy domains tend to move in parallel, the mechanisms behind this dynamic remain unclear. We examine four explanations: (1) alignment in preferred policy levels; (2) parallel policy movement combined with domain-specific thermostatic feedback; (3) feedback to global policy across domains; and (4) responsiveness to presidential partisanship. These mechanisms matter for how we interpret public opinion change and policy responsiveness. We develop and test a theoretical model using data on four social spending domains in the USA. Our findings suggest that spending mood reflects both parallelism in preferred policy levels and responsiveness to overall social spending and presidential party affiliation.