Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

This article explores the models and frameworks developed on "research impact'. We aim to provide a comprehensive overview of related literature through scoping study method. The present research investigates the nature, objectives, approaches, and other main attributes of the research impact models. It examines to analyze and classify models…

Multifactorial models of dyslexia have expanded how we consider heterogeneity within the population of children with dyslexia. These models are predicated on the idea that cognitive/linguistic risk factors are not deterministic but instead probabilistic, with the likelihood of difficulties involving an interaction between risk and protective…

We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

The Individuals with Disabilities Education Improvement Act (2004) allows alternate pathways for school districts to identify and classify students with a specific learning disability (SLD). Response to Intervention (RtI) is one of the frameworks schools can use when eliminating the use of the discrepancy model. The premise of RtI posits that…

This note raises caution that a finding of a marked pseudo-guessing parameter for an item within a three-parameter item response model could be spurious in a population with substantial unobserved heterogeneity. A numerical example is presented wherein each of two classes the two-parameter logistic model is used to generate the data on a…

Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…

Background: During the COVID-19 pandemic, online learning has played an increasingly crucial role in the educational system. Academic dishonesty (AD) in online learning is a challenging problem that represents a complex psychological and social phenomenon for learners. However, there is a lack of comprehensive and systematic reviews of AD in…

My dissertation research explored responder behaviors (e.g., demonstrating response styles, carelessness, and possessing misconceptions) that compromise psychometric quality and impact the interpretation and use of assessment results. Identifying these behaviors can help researchers understand and minimize their potentially construct-irrelevant…

In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

The dual-factor model (DFM) of mental health affords educators an expanded view of student social-emotional and behavioral functioning and may help identify students in need of school-based mental health services who would otherwise go unnoticed with traditional screening methods. With a focus on integrating subjective well-being into the…

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…

Many academic institutions have relied exclusively on traditional learning, but the sudden outbreak of COVID-19 shook all educational systems by forcing a shift to emergency remote teaching. The purpose of this study is to understand this transformation and consider the concept of an e-learning ecosystem for building sustainable education to…