This study compares the estimated grammar school effect in different regression models, and explains why previous evidence of the effectiveness of grammar school is mixed. Like most studies of school effectiveness evaluation, previous research on grammar school effect usually applies regression to control for confounding between-school factors and…

Research suggests that supportive programmatic structure can assist online doctoral student success, including time to complete the dissertation. However, completely online doctoral students have unique characteristics and needs and are underrepresented in the research literature; therefore, research exploring programmatic factors as related to…

Existing research on "school effectiveness" indicates that differences at the school level contribute significantly towards variation in student outcomes; however, less is known about the effectiveness of schooling in low- and middle-income countries (LMICs). This paper addresses this gap using quantitative analysis of data from two…

One of the many impacts of the COVID-19 pandemic has been the increasing prevalence and accessibility of online education. This trend has also introduced challenges for students, instructors, and institutions. This study examines factors affecting online course satisfaction, focusing on individual, instructor, and institutional level…

Business schools need to maintain student academic satisfaction. A key component of a business school's curriculum is its core or required courses. This study compared graduating business student perceptions about core course scales, their combined quantitative versus qualitative and challenging versus added value impact, on types of student…

School value-added models are widely applied to study, monitor, and hold schools to account for school differences in student learning. The traditional model is a mixed-effects linear regression of student current achievement on student prior achievement, background characteristics, and a school random intercept effect. The latter is referred to…

A compelling demonstration of implicit learning is the human ability to unconsciously detect and internalize statistical patterns of complex environmental input. This ability, called statistical learning, has been investigated in people with dyslexia using various tasks in different orthographies. However, conclusions regarding impaired or intact…

Over the past decade, identifying how schools might reduce student absenteeism has moved to the forefront of education policy. Yet little research has examined whether school type itself is important. We focus on the influence of Catholic schools using data from the past decade--the most relevant policy context for addressing absenteeism. The…

High-quality mentoring relationships help college students to achieve their academic potential and career goals. However, less is known about factors that shape the antecedents of mentoring relationships (e.g. mentor-protégé psychological similarity), or the impact of similarities on the development of high-quality mentoring relationships. The…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…

In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…

Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…

Pandemic-related policies are typically developed by districts and translated to all schools for implementation. Understanding the degree to which the pandemic impacted school-level performance would provide additional perspective for researchers looking to help district and school officials move forward. The main purpose of this study is to…

Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking high school, college, and earnings registries spanning the state of Texas, we identify relative college value-added…