First impressions can influence rater-based judgments but their contribution to rater bias is unclear. Research suggests raters can overcome first impressions in experimental exam contexts with explicit first impressions, but these findings may not generalize to a workplace context with implicit first impressions. The study had two aims. First, to…

With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…

This study examines the feasibility and potential advantages of using large language models, in particular GPT-4o, to perform partial credit grading of large numbers of student written responses to introductory level physics problems. Students were instructed to write down verbal explanations of their reasoning process when solving one conceptual…

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…

The Canadian Agility and Movement Skill Assessment (CAMSA) is a valid and reliable circuit-based test of motor competence which can be used to assess children's skills in a live or recorded performance and then coded. We aimed to analyze the intrarater reliability of the CAMSA scores (total, time, and skill score) and time measured, by comparing…

In this study, I compare the accuracy of automatic speech recognition (ASR) transcription against two measures of intelligibility provided by human listeners. The data came from readings of five texts recorded by 15 language learners of French. Human understanding was gauged by (i) asking a group of 36 naïve first language (L1) speakers of French…

Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…

Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…

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…

This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…

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…

In this paper we use novel data to test the direct and indirect paths between teacher self-efficacy and student outcomes. This includes how teacher self-efficacy is linked to student, teacher, and expert rater views of lesson quality. Our results illustrate how the link between teacher self-efficacy and instructional quality is sensitive to how…

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…

Previous research that explores the effect of ethnicity in the perception of speaker accentedness and personality traits often finds that Asian appearance contributes to a more accented and less competent impression. Importantly, most of the work done to date employed only Caucasian first language-speaking listeners; moreover, ethnicity and gender…