Reliability that can be proved by numeric indicators in quantitative studies has become a very discussible issue. The reason for this is to be thought that in qualitative researches, reliability is not based on positive perspective and those forming reliability criteria is difficult. However, for testing the reliability of a qualitative study or…

Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…

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 project explored the reliability and utility of transcription in coding qualitative data across two studies in a program evaluation context. The first study tested the method of direct audio coding, or coding audio files without transcripts, using qualitative data software. The presence and frequency of codes applied in direct audio coding…

This study aims to develop a robust rubric for evaluating artificial intelligence (AI)--assisted essay writing in English as a Foreign Language (EFL) contexts. Employing a modified Delphi technique, we conducted a comprehensive literature review and administered Likert scale questionnaires. This process yielded nine key evaluation criteria,…

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…

Purpose: Assessment of strained voice quality is difficult due to the weak reliability of auditory-perceptual evaluation and lack of strong acoustic correlates. This study evaluated the contributions of relative fundamental frequency (RFF) and mid-to-high frequency noise to the perception of strain. Method: Stimuli were created using recordings of…

To determine the impacts of using ChatGPT to assist English as a foreign language (EFL) English college majors in revising essays and the possibility of leading to higher scores and potentially causing unfairness. A prospective, double-blinded, paired-comparison study was conducted in Feb. 2023. A total of 44 students provided 44 original essays…

This study evaluates whether early vocalizations develop in similar ways in children across diverse cultural contexts. We analyze data from daylong audio recordings of 49 children (1-36 months) from five different language/cultural backgrounds. Citizen scientists annotated these recordings to determine if child vocalizations contained canonical…

Background: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can decrease the time and burden by automating the process, but evidence validating such software is…

How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…

Comparative Judgement (CJ) has emerged as a technique that typically makes use of holistic judgement to assess difficult-to-specify constructs such as production (speaking and writing) in Modern Foreign Languages (MFL). In traditional approaches, markers assess candidates' work one-by-one in an absolute manner, assigning scores to different…

This paper explores the concept of dynamically generating definitions using a deep-learning model. We do this by creating a dataset that contains definition entries and contexts associated with each definition. We then fine-tune a GPT-2 based model on the dataset to allow the model to generate contextual definitions. We evaluate our model with…

This study searched for open-source semantic similarity tools and evaluated their effectiveness in automated content scoring of fact-based essays written by English-as-a-Foreign-Language (EFL) learners. Fifty writing samples under a fact-based writing task from an academic English course in a Japanese university were collected and a gold standard…

Although artificial Intelligence (AI) is prevalent and impacts facets of daily life, there is limited research on responsible and humanistic design, implementation, and evaluation of AI, especially in the field of education. Afterall, learning is inherently a social endeavor involving human interactions, rendering the need for AI designs to be…