Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in prior courses), the task of student's performance prediction is to predict a student's grades in future…

This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…

Faced with increasing demands for accountability, teachers are having to base their instructional decisions and choice of interventions on data on student performance. This book shows how to make this otherwise daunting task much more manageable by means of case studies and countless evidence-based forms and graphs. Although this book often refers…

The ongoing collection and documentation of evidence of students' performance in the classroom is a fundamental component of formative instructional practices, essential for ensuring student success. Multiple methods of collecting and documenting evidence of students' academic performance in the classroom are described. These methods include…

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

This article discusses procedures that have been developed to empower students with disabilities to take responsibility for graphing data reflecting their own academic performance. It discusses training methods for teaching students self-graphing and the benefits of self-monitoring. Examples are provided of different types of computer graphs.…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

This survey of 510 special education teachers found that most teachers collect, record, and use data on student performance to determine instructional effectiveness, appropriate time to move students to the next skill, and which objectives have been met. Only one-third of teachers used graphs for displaying and interpreting data. (Author/JDD)

In statistical terms, transfer rates require two components: a numerator that represents community college students who transfer and a denominator that approximates the pool of potential transfer students. The California Task Force adopted a set of criteria to judge the appropriateness of prospective pairs of numerators and denominators. Its form…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…