Teacher data use is often centered around standardized testing. Such data use that is commonly centered on standardized tests and used during professional development does not necessarily transform teacher practice toward equity and fails to change teacher conceptualizations of students while also perpetuating inequitable practices. Conversely,…

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…

A distinctive feature of game-based learning environments is their capacity to create learning experiences that are both effective and engaging. Recent advances in sensor technologies (e.g., facial expression analysis and gaze tracking) and natural language processing have introduced the opportunity to leverage multimodal data streams for learning…

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…

This experimental research study examined the effects of using a mobile learning environment (MLE) that provided scaffolded assistive tutoring on student achievement in a Circuit Analysis (Network Theory) course. It also aimed to examine the relationships between students' user learning analytics and their learning outcomes. The design and…

The goal of learning analytics is to optimize learning and the environments in which it occurs. Since 2011, when learning analytics was defined as a separate and distinct area of academic inquiry, the literature has identified a need for research that presents evidence of effective learning analytics, as well as, learning analytics research that…

The purpose of this study was to examine and describe the nature of the research to practice gap in learning analytics applications in K12 educational settings. It was also the purpose of this study to characterize how learning analytics are currently implemented and understood. A secondary objective of this research was to advance a preliminary…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

A lack of fundamental information literacy skills for college students can be a barrier to academic success. This study sought to investigate how the availability of asynchronous and mobile-friendly learning modules in Canvas impacts students' information literacy learning and to improve students' information literacy skills at a community college…