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…

RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…

Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…

Behavior analysts typically rely on visual inspection of single-case experimental designs to make treatment decisions. However, visual inspection is subjective, which has led to the development of supplemental objective methods such as the conservative dual-criteria method. To replicate and extend a study conducted by Wolfe et al. (2018) on the…

Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…

The current paper intends to exploit the Many Facet Rasch Model to investigate and compare the impact of situations (items) and raters on test takers' performance on the Written Discourse Completion Test (WDCT) and Discourse Self-Assessment Tests (DSAT). In this study, the participants were 110 English as a Foreign Language (EFL) students at…

As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…

This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student…

In many performance assessments, one or two raters from the complete rater pool scores each performance, resulting in a sparse rating design, where there are limited observations of each rater relative to the complete sample of students. Although sparse rating designs can be constructed to facilitate estimation of student achievement, the…

Teacher performance scores inform education leaders' management of teacher human resources. However, prior research has implied that different interpretations of performance criteria between teachers and their evaluators suppress teacher development. Although research has examined teacher perceptions of performance scores and compared teacher…

In Comparative Judgement (CJ) exercises, examiners are asked to look at a selection of candidate scripts (with marks removed) and order them in terms of which they believe display the best quality. By including scripts from different examination sessions, the results of these exercises can be used to help with maintaining standards. Results from…

Experiential education partnered with guided reflection is thought to support students with higher-order thinking skills. In this study, 44 reflections from two university-level sustainability courses were compared. In both courses students were asked to write a reflection, but only one course used the Reflective Learning Framework (RLF). Tests of…

Automated essay scoring (AES) has emerged as a secondary or as a sole marker for many high-stakes educational assessments, in native and non-native testing, owing to remarkable advances in feature engineering using natural language processing, machine learning, and deep-neural algorithms. The purpose of this study is to compare the effectiveness…

In this article, I report on examiners' views and experiences of using Pairwise Comparative Judgement (PCJ) and Rank Ordering (RO) as alternatives to traditional analytical marking for GCSE English Language essays. Fifteen GCSE English Language examiners took part in the study. After each had judged 100 pairs of essays using PCJ and eight packs of…

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…