This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…

In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…

With the 5th Edition of Data Analysis for Continuous School Improvement, best-selling Victoria Bernhardt has written the go-to-resource for data analysis in your school! By incorporating collaborative structures to implement, monitor, and evaluate the vision and continuous improvement plan, this book provides a framework to show learning…

Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…

As institutions cope with the difficult task of managing scarce resources to support student learning, college writing centers, like other student services, need to be able to articulate and, at times, quantify the benefits they offer the populations they serve. This study examined outcomes associated with visiting the writing center at one…

There is considerable variability in the literacy assessments taken in Kindergarten through second grade, across schools and between multilingual learners and other students, and within students over time. This makes it difficult to study changes in students' acquisition of ELA skills in these formative years, or to evaluate policies and practices…

Calls for increased monitoring and evaluation of education policies and practices have not, so far, included widespread and consistent assessments of the inclusiveness of education settings. Measuring inclusion in education has proven to be a challenging exercise, due not only to the complexity and different uses of the concept, but also to its…

The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to…

This paper reports on the findings of an ESRC funded project that contributes to the evidence base underpinning contextualised approaches to undergraduate admissions in England. We show that the bolder use of reduced entry requirements for disadvantaged learners is necessary if ambitious new widening access targets set by the Office for Students…

Large-scale assessment programs, such as the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS), employ item response theory (IRT) and marginal estimation methods to estimate student proficiency in specific subjects such as mathematics, science, or reading. Each of these…

At present, there is a huge amount of unstructured documentation that is generated by students who study the course project management and evaluation. These unstructured documents cannot be used in direct processing to extract useful information or knowledge. At the same time, make use of them to assess student achievement. In this work, we…

Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…

Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…

This study builds on a 2019 Fordham Institute report that examined the relationship between charter school enrollment share--the share of students in a community who enroll in a charter school--and the average achievement of all the students in that community, including those in traditional public schools. Like its predecessor, this report seeks…