Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

Big data is an essential aspect of innovation which has recently gained major attention from both academics and practitioners. Considering the importance of the education sector, the current tendency is moving towards examining the role of big data in this sector. So far, many studies have been conducted to comprehend the application of big data…

Procrastination is a well-known phenomenon experienced by a lot of people in everyday life. People sometimes intentionally, sometimes unintentionally put off their tasks even though they might be worse off due to the delay (e.g., not paying bills due, even though they have sufficient funds in their bank account). It is safe to say everybody…

In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…

Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…

The literature linking adulthood criminality to cumulative disadvantage and early school misbehavior demonstrates that understanding the mechanisms underlying student behavior and the responses of teachers and administrators is crucial in comprehending racial/ethnic disparities in actual or perceived school misbehavior. We use data on 19,160 ninth…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…

School closures in response to the COVID-19 pandemic have dramatically changed the conditions in which students learn and experience schooling. Disparities in students' access to learning and in their academic outcomes are likely to exacerbate longstanding challenges and inequities. Now more than ever, educators need information that will help…

Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…

A recent qualitative study by a team of researchers looked into how grade-level teams of teachers are thinking about causes and strategies based on looking at student performance data. What is interesting in these findings is how infrequently teachers attribute student results to instruction -- just 15% of the time. Teachers in this study were…

Using data for decision-making is critical for schoolwide leadership teams and has been shown to enhance both social and academic outcomes for students (Faria et al., 2017). Using data effectively, however, requires that teams have a clear vision about the type of data, format of data presentation, and process for using data. To avoid expending…

A substantial achievement gap, with culturally and linguistically diverse (CLD) students falling behind native-English-speaking White peers, has been widely documented in research as well as government reports. However, a corresponding discipline gap has not been evident due to the various labels and methods used for identifying specifically…

The TELL Survey utilizes items representative of twenty different factors, or variables, within the domain of campus climate and culture. However, since the district began using the TELL Survey, a thorough examination of these factors and the items within each of these factors has not been conducted. This brief report aims to uncover the factor…

This report provides information for administrators, researchers, and student support staff in local education agencies who are interested in identifying students who are likely to have near-term academic problems such as absenteeism, suspensions, poor grades, and low performance on state tests. The report describes an approach for developing a…