Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

Models of word reading that simultaneously take into account item-level and person-level fixed and random effects are broadly known as explanatory item response models (EIRM). Although many variants of the EIRM are available, the field has generally focused on the doubly explanatory model for modeling individual differences on item responses.…

Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…

Conceptual modeling of databases is a complex cognitive activity, particularly for novice database designers. The current research empirically tests a new pedagogy for this activity. It examines an instructional approach that stresses visualizing gradual transitions between levels of abstraction in different hierarchic levels of a relational…

The present study set out to explore the locus of the poorly understood but frequently reported and comparatively large practice effect in sustained attention tests. Drawing on a recently proposed process model of sustained attention tests, several cognitive tasks were administered twice in order to examine which specific component of test…

This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…

Research indicates that learning from erroneous examples (EE) is superior to correct examples because errors may provide students with a stimulus to spontaneously produce more self-explanations, leading to better learning outcomes. However, because most studies were conducted in individual settings, it remains an open question whether the…

The central dogma of molecular biology, a model that has remained intact for decades, describes the transfer of genetic information from DNA to protein though an RNA intermediate. While recent work has illustrated many exceptions to the central dogma, it is still a common model used to describe and study the relationship between genes and protein…

Today's students exhibit generational differences in the way they search for information. Observations of first-year students revealed a proclivity for simple keyword or phrases searches with frequent misspellings and incorrect logic. Although no students had strong mental models of search mechanisms, those with stronger models did construct more…

An information-processing model was tested for a laboratory visualization task that represents one adaptation of a standardized spatial ability test. The pattern of results suggests that individual differences are a function of differences in the accuracy and/or quality of the mental representation, not just speed of processing. (Author/BW)

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…