Today's language models can produce syntactically accurate and semantically coherent texts. This capability presents new opportunities for generating content for language assessments, which have traditionally required intensive expert resources. However, these models are also known to generate biased texts, leading to representational harms.…

Formative assessment plays a critical role in improving learning outcomes by providing feedback on student mastery. Open-ended questions, which require students to produce multi-word, nontrivial responses, are a popular tool for formative assessment as they provide more specific insights into what students do and do not know. However, grading…

Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…

American education has focused on reading and literacy skills for decades, but the ongoing reading wars have had little effect on student performance. Authors Rick Ginsberg and Yong Zhao suggest that the growth of artificial intelligence makes this hyperfocus on reading especially misguided because it's becoming increasingly easy to access…

This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…

The ability to comprehend reading material is a crucial skill for academic and professional success, yet many students struggle with it, negatively impacting their academic performance. This study aimed to assess the effectiveness of AI-based personalised reading platforms in improving reading comprehension among senior high school students. The…

This study explores the effectiveness of machine learning and eye movement features in predicting Chinese reading proficiency. Unlike previous research, which focused on one or two specific levels of eye movement features, this study integrates passage-, sentence- and word-level eye movement features to predict reading proficiency. By analyzing…

Reading assessments are essential for enhancing students' comprehension, yet many EdTech applications focus mainly on outcome-based metrics, providing limited insights into student behavior and cognition. This study investigates the use of multimodal data sources -- including eye-tracking data, learning outcomes, assessment content, and teaching…

Purpose: Researchers have developed a constellation model of decodingrelated reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation…

Advances in artificial intelligence (AI) are ushering in a large and rapid technological transformation. Understanding how AI capabilities relate to human skills and how they develop over time is crucial for understanding this process. In 2016, the OECD assessed AI capabilities with the OECD's Survey of Adult Skills (PIAAC). The present report…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

This experimental study investigates the impact of ChatGPT-simplified authentic texts on university students' reading comprehension, inferencing, and reading anxiety levels. A within-subjects design was employed, and 105 undergraduate English as a foreign language (EFL) students engaged in both original and ChatGPT-simplified text readings,…

This study examined the integration of artificial intelligence-powered speech recognition technology within early reading assessments in Morocco's Teaching at the Right Level (TaRL) program. The purpose was to evaluate the effectiveness of an automated speech recognition tool compared to traditional paper-based assessments in improving reading…

Purpose: The advent of ChatGPT has fundamentally changed the way people approach and access information. While we are encouraged to embrace the tool for its various benefits, it is yet to be known how to drive people to adopt this technology, especially to improve their life skills. Using implicit self-theories, the current research delineated the…

This paper describes a new automated disengagement tracking system (DTS) that detects learners' maladaptive behaviors, e.g. mind-wandering and impetuous responding, in an intelligent tutoring system (ITS), called AutoTutor. AutoTutor is a conversation-based intelligent tutoring system designed to help adult literacy learners improve their reading…