Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

The current study uncovers secondary school students' actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learning strategy profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15…

Digital games can make unique and powerful contributions to K-12 science education, but much of that potential remains unrealized. Research evaluating games for learning still relies primarily on pre- and post-test data, which limits possible insights into more complex interactions between game design features, gameplay, and formal assessment.…

In the present study, complex dynamic systems theory and interpersonal theory are combined to describe the teacher-student interactions of two teachers with different interpersonal styles. The aim was to show and explain the added value of looking at different steps in the analysis of behavioral time-series data (i.e., observations of teacher and…

Monitoring bullying behaviours is the key aspect of a successful anti-bullying intervention. Questionnaires among pupils and principals of the same schools were utilised to measure the agreement between pupil-reported frequency and principals' estimations of the prevalence of frequent bullying in the same schools and to identify monitoring methods…

The Multi-Tiered System of Support (MTSS) framework, which uses a systems approach to promote school improvement and support all students in improving academics and behavior using data-based problem-solving, is a key part of the Wake County Public Schools System (WCPSS) Strategic Plan. As of 2017-18, MTSS schools were at the initial stages of MTSS…

Based on eighth-grade writing assessment data from the 1998 (N = 20,586) and 2007 (N = 139,900) National Assessment of Educational Progress (NAEP), this study examines the relationships among students' writing attitudes, learning-related behaviors, and gender in relation to writing performance. Overall, the effects of attitudes were slightly…

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Federal and state initiatives (No Child Left Behind, 2001) require schools and districts to set high standards for student growth and achievement. Currently, student growth and progress are measured in Louisiana via statewide achievement tests. In 4th and 8th grades these assessments are considered to be 'high-stakes', as promotion and retention…

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…

We present a method for assessing science inquiry performance, specifically for the inquiry skill of designing and conducting experiments, using educational data mining on students' log data from online microworlds in the Inq-ITS system (Inquiry Intelligent Tutoring System; www.inq-its.org). In our approach, we use a 2-step process: First we use…

Purpose/Objectives: The purpose of the "Montana Recess Before Lunch Survey" was to explore benefits, challenges, and factors associated with successful implementation of Recess Before Lunch (RBL), from the perspective of school principals. Methods: An online written questionnaire was distributed to all (N = 661) Montana elementary and…

Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…

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…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…