This case study examines the critical role school leaders play in teacher data use. Aligned with previous literature, we find that educators perceive high levels of support for data use and prefer formative data; however, observations showed a data use method unlike previously described inquiry cycles. From these findings we propose a new data use…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…

The COVID-19 pandemic forced widespread school closures and a shift to remote learning. A growing body of research has examined the effects of remote learning on student outcomes. But the accuracy of the school modality measures used in these studies is questionable. The most common measures--based on self-reports or district website…

Statistics Canada releases data on the labour market outcomes of college and university graduates using data from the Education and Labour Market Longitudinal Platform (ELMLP). Statistics Canada has developed the ELMLP in collaboration with the provincial and territorial ministries of education, Employment and Social Development Canada (ESDC), and…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

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 the profession of education, predicting students' academic success is an essential responsibility. This study introduces a novel methodology for predicting students' pass or fail outcome in certain courses. The system utilises academic, demographic, emotional, and VLE sequence information of students. Traditional prediction methods often…

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…

Government investment in early childhood education and care (ECEC) supports children's ongoing development, learning and wellbeing, and delivers the skills and knowledge required for a thriving society and economy. Assessing the efficiency of this investment, as well as methods for ongoing monitoring are important steps in delivering effective…

This study presents a data mining approach to predict academic success of the first-year students. A dataset of 10 academic years for first-year bachelor's degrees from a Portuguese Higher Institution (N = 9652) has been analysed. Features' selection resulted in a characterising set of 68 features, encompassing socio-demographic, social origin,…

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…

Objective/Research Question: Community college graduation rates are typically quite low, and developmental mathematics enrollment and coursetaking patterns may constrain academic outcomes. To identify ways in which community college graduation rates may be improved, decision trees were utilized to examine the STEM coursetaking patterns of N =…

Teacher-level factors are theoretically linked to student outcomes in data-based instruction (DBI; Lembke et al., 2018). Professional development and ongoing support can increase teachers' knowledge, skills, and beliefs related to DBI, as well as their instructional fidelity (McMaster et al., 2020). However, less is known about how each of these…