Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…

Concerns over students engaging in various forms of academic misconduct persist, especially with the post-COVID-19 rise in online learning and assessment. Research has demonstrated a clear role of the personality trait psychopathy in cheating, yet little is known about why this relationship exists. Building on the research by Curtis et al.…

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…

Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning…

This study examines the growing issue of academic dishonesty in online assessments, a challenge intensified by the expansion of digital learning platforms. Specifically, it investigates the relationship between students' online engagement and their performance in online versus traditional paper-and-pencil tests. Employing a cross-sectional…

The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end-of-year proficiency in reading and math. Participants included 13,009 students in Grades 3-8 who had at least one fall screening score and end-of-year…

Predicting academic performance for students majoring in computer science has long been a significant field of research in computing education. Previous studies described that accurate prediction of students' early-stage performance could identify low-performing students and take corrective action to improve performance. Besides, adopting machine…

Many instructors use a syllabus quiz to ensure that students learn and understand the content of the syllabus. In this project, I move beyond this exercise's primary function and examine students' syllabus quiz scores to see if they can predict how well students perform in the course overall. Using data from 495 students enrolled in 18 sections of…

This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

One perceived advantage of computer-based testing is that accessibility tools can be embedded within the testing format, allowing students with disabilities to use them when necessary to remove unique barriers within testing. However, an important assumption is that students activate and use the tools when needed. Initial data from large-scale…

Online formative quizzes have been shown to be an effective tool for improving students' academic achievement. This quasi-experimental study investigated the effects of students' engagement in online formative quizzes on academic achievement in an undergraduate engineering course, employing a one-group post-test research design. Participants (n =…

Traditional static tests of reading and reading-related skills offer some ability to predict future reading performance, though such screeners may misclassify children with or at risk of reading disorder (RD). Dynamic assessment (DA) is an alternative approach that measures learning potential and may be less dependent on learning background. A…

Online quizzes and learning platforms provided by textbook publishers have become common components of undergraduate education. Here, I examine how participation in these formative assessments related to student course performance. Over multiple semesters, students completed either free online unlimited attempt quizzes or assignments from a…

Purpose: The aim of the study is to examine the intention of students toward the online education system with emphasis on online examination in higher education. The study investigated different constructs that have an influence on the use of the online platform for learning to the specific domain that mitigates the personal needs of the learners…