Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

The current exploratory study used data on students in grades six through 12 in North Carolina to examine the effectiveness of their mathematics teachers. Its purpose was fourfold: (1) to identify teacher qualification indicators that are most important for predicting students' math scores; (2) to empirically identify teacher qualification…

The development of academic English proficiency and the time it takes to reclassify to fluent English proficient status are key issues in English learner (EL) policy. This article develops a shared random effects model (SREM) to estimate English proficiency development and time to reclassification simultaneously, treating student-specific random…

Educational games have become hugely popular, and educational data mining has been used to predict student performance in the context of these games. However, models built on student behavior in educational games rarely differentiate between the types of problem solving that students employ and fail to address how efficacious student problem…

The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…

District and state education leaders frequently use screening assessments to identify students who are at risk of performing poorly on end-of-year achievement tests. This study examines the use of a universal screening assessment of reading skills for early identification of students at risk of low achievement on nationally normed tests of reading…

Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

School-wide positive behavior support (SWPBS) focuses on promoting social competence through the establishment of behavior expectations that are explicitly taught and reinforced by all teachers across all settings. This study investigated the validity of using adherence to SWPBS behavior expectations as a screening tool for predicting behavior…

This study assesses the ability of a brief screening form, the Behavioral and Emotional Screening System-Student Form (BESS-SF), to predict scores on the much longer form from which it was derived: the Behavior Assessment System for Children-Second Edition Self-Report of Personality-Child Form (BASC-2-SRP-C). The present study replicates a former…

Although the simple view of reading and other theories suggest that listening comprehension is an important determinant of reading comprehension, previous research on linguistic transfer has mainly focused on the role of first language (L1) decoding skills in second language (L2) reading. The present study tested the assumption that listening…

The purpose of this study was to investigate the use of English language proficiency and academic reading assessment scores to predict the future academic success of English learner (EL) students. Data from two cohorts of middle-school ELs were used to evaluate three prediction models. One cohort of students was used to develop the prediction…

Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…

Functional roles may explain the learning performance of groups. Detecting a functional role is critical for promoting group learning performance in computer-supported collaborative learning environments. However, it is not easy for teachers to identify the functional roles played by students in a web-based learning group, or the relationship…

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…