ETS scientists developed a human-centered AI (HAI) framework that combines data on how students interact with assessments--such as task navigation and time spent--with their performance, providing deeper insights into student performance in large-scale assessments.

This dissertation aimed to explore the use of machine learning (ML) models in in-patient clinical settings. A literature review was conducted to identify existing guidelines and frameworks for such models, and an in-depth study was conducted on ML-based models to understand their behavior and implications on patient outcomes. A conceptual…

This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…

Anonymous assessment, introduced to higher education over the last twenty-five years to reduce attainment gaps, is a now common place. This paper suggests some ways in which anonymous assessment could be reconceptualised. We argue that there is scant empirical evidence of anonymity having worked in reducing attainment gaps in higher education. It…

Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…

Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…

In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…

The arrival of ChatGPT and other artificial intelligence (AI) has caused considerable concern for educators worldwide, many of whom are still recovering from the impact of the COVID-19 pandemic. Although the debate continues around the use of AI in education, one approach to ensure students are achieving their learning objectives, the oral exam or…

Online education has been expected to be the future of learning; it will never replace the value of traditional classroom experiences fully. Technical problems have less impact on offline education, which gives students more freedom to plan their time and stick to it. In addition, teachers cannot observe their students' behavior and activities…

Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Shapley values and its computationally efficient variant Kernel SHAP may be employed for this aim, similarly to other existing methods, the latter makes…

Assessment holds the key to unlocking for the teacher a child's past (what he already knows), present (what he is learning), and future (what he still needs to learn) to inform teaching. Despite the benefits of assessment for informing teaching practice and enhancing student learning, it remains one of the most challenging and time-consuming tasks…

In today's fast-paced digital world, understanding Artificial Intelligence (AI) is crucial for management students. This paper explores using the Turing test, a famous method to see if AI can act like a human, as a key tool in management education. The focus is on how this test can help students learn about AI more deeply. This paper introduces an…

The rapid development of higher education in China has significantly advanced physical education within universities, contributing to students' comprehensive development and national health improvement. However, the expansion of university enrollment has introduced challenges such as a decrease in per capita sports resources and declines in…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

Generative AI (GenAI) challenges assessment validity by enabling students to complete tasks without demonstrating genuine capability. In response to this challenge, institutions have developed and implemented various approaches that aim to communicate permissible AI use to students. Familiar examples include the 'traffic light' approach now…