Teachers often use open-ended questions to promote students' deeper understanding of the content. These questions are particularly useful in K-12 mathematics education, as they provide richer insights into students' problem-solving processes compared to closed-ended questions. However, they are also challenging to implement in educational…

This study investigates the effects of a scenario-based assessment design on students' writing processes. An experimental data set consisting of four design conditions was used in which the number of scenarios (one or two) and the placement of the essay task with respect to the lead-in tasks (first vs. last) were varied. Students' writing…

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…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…

Digital game-based assessments generate student process data that is much more difficult to analyze than traditional assessments. The formative nature of game-based assessments permits students, through applying and practicing the targeted knowledge and skills during gameplay, to gain experiences, receive immediate feedback, and as a result,…

This study uses information about in-game strategy use, identified through cluster analysis of actions in an educational video game, to make data-driven modifications to the game in order to reduce construct-irrelevant behavior. The examination of student strategies identified through cluster analysis indicated that (a) it was common for students…

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…

The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

We present "Science Assistments," an interactive environment, which assesses students' inquiry skills as they engage in inquiry using science microworlds. We frame our variables, tasks, assessments, and methods of analyzing data in terms of "evidence-centered design." Specifically, we focus on the "student model," the…

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…

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…