Aurelius School District used Curriculum Associates' i-Ready program, which was philosophically aligned to the science of reading and included i-Ready Diagnostic, i-Ready Instruction, and Teacher Toolbox, to improve Cole Middle School students' reading achievement. Because of the high monetary cost of i-Ready, the school district was considering…

Experience, whether personal or vicarious, plays an influential role in shaping human knowledge. Through these experiences, one develops an understanding of the world, which leads to learning. The process of gaining knowledge in higher education transcends beyond the passive transmission of knowledge from an expert to a novice. Instead, students…

The vast amount of data collected during online learning offers opportunities to advance newer interventions that might aid learning. One such intervention has been learning analytics dashboards, visualizations designed to translate learning-related data into usable information. However, many student-facing dashboards compare learners' performance…

While utilizing assessment data has been a pervasive practice in educational reform for decades, and teachers are expected to use assessment data to improve instruction, little is known about how the practice of requiring teachers to review test data affects their perception of effectiveness in addressing the learning gaps of student groups. This…

Educational Data Mining (EDM) is an emerging field that aims to better understand students' behavior patterns and learning environments by employing statistical and machine learning methods to analyze large repositories of educational data. Analysis of variable data in the early stages of a course might be used to develop a comprehensive…

Learning analytics researchers have been diligently integrating trace data to study Self-Regulated Learning (SRL). Compared to traditionally used survey data, trace data, such as log or clickstream data designed and interpreted to understand a certain SRL construct, are considered to be more effective in capturing dynamic SRL as fine-grained…

This phenomenological study expands upon Bean and Metzner's (1985) A Conceptual Model of Nontraditional Student Attrition framework by introducing a new Academic Variable, Learning Analytics (LA), and identifying two specific Social Integration Variables (Sense of belonging; Microaggressions). LA was not a factor in 1985 when the original model…

The purpose of this study was to explore and analyze the utilization of learning analytics data produced by a learning management system as an indicator of learners' self-regulation. In the Spring of 2021, 258 learners at a four-year, mid-Atlantic university provided access to their learning management system data. Of those 258 learners, 86…

This action research project aimed to introduce and examine the impact of Professional Learning Communities (PLCs), the Meeting Wise Process, and the Data Wise Process on teaching practices at a Chinese middle school. PLCs, a collaborative model for continuous professional development, have been widely adopted in various educational contexts but…

First-Year Engineering (FYE) programs are a critical part of engineering education, yet they are quite complex settings. Given the importance and complexity of FYE programs, research to better understand student learning and inform design and assessment in FYE programs is imperative. Therefore, this dissertation showcases various uses of data…

Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…

A major problem faced by instructors post-implementation of unsupervised online assessments is that they may lack real-time access to the students' actual learning behaviors. Limitations in student-feedback, limited know-how of accessing and analyzing log data, and large class sizes could restrict instructors' access to learners' behaviors. This…

The aim of this study was to examine the relationship between common classroom help-seeking determinants (achievement goals, self-efficacy, prior knowledge, gender, and help-seeking perceptions) and help-seeking behaviors online (hint use percentage, latency of help seeking, answer attempt percentage, feedback level percentage, and seeking help…

The purpose of this study was to examine the predictive power of Academic and Learning Analytics models on the persistence, retention, and graduation rates for students enrolled in higher education institutions in the United States. Specifically, this study is concerned with the relationships between the present usage of Academic and Learning…

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…