A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

Deep-sea research is rarely available to undergraduate students. However, as telepresence technology becomes more available, doors may open for more undergraduates to pursue research that includes remote fieldwork. This descriptive case study is an initial investigation into whether such technology might provide a feasible opportunity for…

Of the many inequities in the education system, gaps in access to strong teaching have proven to be among the most stubborn. That is not to say that there are not excellent teachers in high-poverty schools. Research shows an indisputable and wide-spread pattern in schools and districts across the country: Low-income children and children of color…

The No Child Left Behind (NCLB) Act of 2001 requires states to ensure that all students make adequate yearly progress in achieving proficiency in English language arts and math. This study examines how six diverse schools have responded to the challenge of educating their students in math, particularly students with disabilities and other…

New software tools for data analysis provide rich opportunities for representing and understanding data. However, little research has been done on how learners use these tools to think about data, nor how that affects teaching. This paper describes several ways that learners use new software tools to deal with variability in analyzing data,…