Background: Generative artificial intelligence (AI) represents a potentially powerful, time-saving tool for grading student essays. However, little is known about how AI-generated essay scores compare to human instructor scores. Objective: The purpose of this study was to compare the essay grading scores produced by AI with those of human…

AI-enabled assessment of student papers has the potential to provide both summative and formative feedback and reduce the time spent on grading. Using auto-ethnography, this study compares AI-enabled and human assessment of business student examination papers in a law module based on previously established rubrics. Examination papers were…

Human essay grading is a laborious task that can consume much time and effort. Automated Essay Scoring (AES) has thus been proposed as a fast and effective solution to the problem of grading student writing at scale. However, because AES typically uses supervised machine learning, a human-graded essay corpus is still required to train the AES…

Two of the central issues in comparative judgement (CJ), which are perhaps underexplored compared to questions of the method's reliability and technical quality, are "what processes do judges use to make their decisions" and "what features do they focus on when making their decisions?" This article discusses both, in the…

This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…

Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…

This study conducts a comprehensive analysis of the assessment of journal writing in English as a Foreign Language (EFL) at the secondary school level, comparing the performance of a Generative Artificial Intelligence (GenAI) platform with two human graders. Employing a convergent parallel mixed methods design, quantitative data were collected…

The advent of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, has significantly impacted the educational landscape, offering unique opportunities for learning and assessment. In the realm of written assessment grading, traditionally viewed as a laborious and subjective process, this study sought to…

This article discusses and challenges the increasing use of plagiarism detection services such as Turnitin and Grammarly by students, arguing that the increasingly online nature of composition is having a profound effect on student composition processes. This dependence on the Internet is leading to a strategy I term 'de-plagiarism', in which…

Email has become the most preferred form of business communication. Writing "good" email has become an essential skill required in the industry. "Good" email writing not only facilitates clear communication, but also makes a positive impression on the recipient, whether it be one's colleague or a customer. The aim of this paper…

We report on a study comparing peer feedback with feedback written by tutors on a large, undergraduate software engineering programming class. Feedback generated by peers is generally held to be of lower quality to feedback from experienced tutors, and this study sought to explore the extent and nature of this difference. We looked at how…

This article investigates the support e-learning can provide for the management and marking of assignments. The work is contextualised in the importance of assessment with assignments in tertiary education, in the theories about high quality marking of assignments, and the practical experiences of academics at tertiary institutions. The tasks that…

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

Computer-based assessment of exams provides teachers and students with two main benefits: fairness and effectiveness in the evaluation process. This paper proposes a fully automatic evaluation tool for the Graphic and Virtual Design (GVD) curriculum at the First School of Architecture of the Politecnico di Torino, Italy. In particular, the tool is…

Technological developments are impacting upon UK assessment practices in many ways. For qualification awarding bodies, a key example of such impact is the ongoing shift towards examiners marking digitally scanned copies of examination scripts on screen rather than the original paper documents. This digitisation process has obvious benefits,…