According to the United States Department of Education (2012, 2016), degree completions are a vital measure of overall institution success. Significantly, declining student persistence rates and low degree completions are consistent problems in public colleges throughout the United States. Not only are diminishing retention and incomplete degrees…

Analogy is a powerful learning mechanism for children to learn novel, abstract concepts from only limited input, yet also requires cognitive supports. My dissertation sought to propose and examine number lines as a mathematical schema of the number system to facilitate both the development of rational number understanding and analogical reasoning.…

A multiple case study was designed to examine the components of data literacy used by formal and informal leaders to support the work of Data Teams. Nine formal leaders and ten informal leaders constituted the participants. One overarching central question and seven subquestions guided the research. The answer to the central question, How do…

With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This exploratory design-based research (DBR) study implemented a data-driven approach to identify secondary school…

Skills, such as critical thinking, problem-solving, and innovation are necessary for the 21st Century. The economy and the forums of international business and globalization demand skilled workers. Some schools in the United States are producing such workers, however it is unclear the programs and practices these schools utilize. This study…

This study describes a procedure one school district used to increase students' reading abilities through reviewing data and adjusting the instruction to give students intensive services, as needed. This school worked in a problem-solving team approach to develop a comprehensive team that followed the progression of student achievement.…

A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…

This study sought to compare a data-rich learning (DRL) environment that utilized online data as a tool for teaching about renewable energy technologies (RET) to a lecture-based learning environment to determine the impact of the learning environment on students' knowledge of Science, Technology, Engineering, and Math (STEM) concepts related…