Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

The Occupation-Centered Intervention Assessment (OCIA) was developed as a reflective tool for students to improve their comprehension of occupation-centered practice. Finding new and innovative ways to incorporate occupation-centered assignments can serve as a strategy to develop student integration of occupation-centered practice and allow…

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using…

English language learning students in China often feel challenged to learn English due to lack of motivation and confidence, pronunciation and grammar difference, lack of practice and people to communicate with etc., which affects students mental health. Adopting Big data and AI will help in overcoming these limitations as it provides personalized…

The Tribal-Academic partnership model described in this article uses Community-Based Participatory Research (CBPR) approaches to foster collaboration between community partners and academic researchers throughout study design, implementation, data collection, interpretation, and dissemination. Literature highlights the importance of community…

The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…

The dataset used in this report was created by combining Bridge to Finish intervention records, provided by the United Way of King County (UWKC), with student information provided by the State Board for Community and Technical Colleges (SBCTC). The intervention records span the terms from summer 2018 through fall 2021. SBCTC data include these…

Background: In many settings internationally, initial teacher education (ITE) relies on cooperation between schools and universities. When these institutions collaborate on teacher education, the shared work can form a basis for community building. This article focuses on experiences in Norwegian ITE of the Change Laboratory (CL), a form of…

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…

This study presents a systematic review of the literature on the predicting student retention in higher education through machine learning algorithms based on measures such as dropout risk, attrition risk, and completion risk. A systematic review methodology was employed comprised of review protocol, requirements for study selection, and analysis…

The purpose of study was gain insight into pre-service teachers' experiences in using classroom data to make learning and teaching decisions. The qualitative study is based on the reflections and recommendations of three pre-service teachers' that participated in a data-driven decision-making intervention whilst on an immersive 10-week…

Higher education institutions often examine performance discrepancies of specific subgroups, such as students from underrepresented minority and first-generation backgrounds. An increase in educational technology and computational power has promoted research interest in using data mining tools to help identify groups of students who are…

Over the past two decades, education underwent a "big data" revolution as states began tracking individual student performance and interim assessments and educational software allowed for a greater granularity of data on students, teachers, and schools. Despite this plethora of new data, considerable gaps in data on early childhood…

The article shares collaborating educators (authors') experiences in supporting a group of student-teachers' interventions to improve learning practices as part of an action research course in a teacher education setting. The authors engaged in a series of reflective discussions in making sense of and improving the course process. Facilitation and…