This quantitative based applied research study examined data collected fromstudents who have withdrawnfromor completed aneducator preparation program (EPP) ina small rural public community college in WestVirginia. This study compared studentretention rates with Frontier andRemote (FAR) designation by home zip code. These data informedthe research…

In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…

Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…

Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…

Secondary schools in New Zealand use assessment data for school self-evaluation, but little research has explored exactly how schools are using these data. This case study of selected high schools explored the perspectives of teachers and school leaders whose schools had recently implemented a student assessment tracking and monitoring…

Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…

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,…

This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…

The present work describes the challenges faced during the development of a countrywide Learning Analytics study and tool focused on tracking and understanding the trajectories of Uruguayan students during their first three years of secondary education. Due to the large scale of the project, which covers an entire national educational system,…

By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction.…

Research conducted to date provides a limited understanding of the landscape of school-based screening practices across academic, behavioral, and health domains, thus providing an impetus for the current survey study. A total of 475 K-Grade 12 school building administrators representing 409 unique school districts across the United States…

In tiered instructional systems (Response to Intervention [RTI]/Multitier System of Supports [MTSS]) that rely on ongoing assessment of students at risk of experiencing academic difficulties, the ability to make informed decisions using student data is critical for student learning. Prior research has demonstrated that, on average, teachers have…

Transferring from a community college to a university is a time of uncertainty for students. Leaving a familiar environment to attend another school where everything and everyone is new creates stress. Navigating a college journey that requires cutting ties during COVID-19 is especially daunting, yet this is exactly what we expect transfer…

In 2006, the BBVA Foundation in Mexico designed a scholarship and mentoring program that targeted vulnerable lower secondary education students in municipalities with high-intensity migration rates. We follow applicants who started lower secondary education in 2009 to estimate the impact of the Program on the probability of graduating from the…

Research conducted to date provides a limited understanding of the landscape of school-based screening practices across academic, behavioral, and health domains, thus providing impetus for the current survey study. A total of 475 K-12 school building administrators representing 409 unique school districts across the United States completed an…