Virtual reality simulation has had a significant impact on training of psychomotor surgical skills, yet there is still a lack of work on its use to teach surgical decision making. This is particularly noteworthy given the recognized importance of decision making in achieving positive surgical outcomes. With the objective of filling this gap, we…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

Multilayer perceptron neural networks, Gaussian naive Bayes, and logistic regression classifiers were compared when used to make early predictions regarding one-year college student persistence. Two iterations of each model were built, utilizing a grid search process within 10-fold cross-validation in order to tune model parameters for optimal…

In 2015, the Australian Government's Excellence in Research for Australia (ERA) assessment of research quality declined to rate 1.5 per cent of submissions from universities. The public debate focused on practices of gaming or "coding errors" within university submissions as the reason for this outcome. The issue was about the…

C-tests are gap-filling tests widely used to assess general language proficiency for purposes of placement, screening, or provision of feedback to language learners. C-tests consist of several short texts in which parts of words are missing. We addressed the issue of local dependence in C-tests using an explicit modeling approach based on testlet…

Evidence evaluation is a crucial process in many human activities, spanning from medical diagnosis to impression formation. The present experiments investigated which, if any, normative model best conforms to people's intuition about the value of the obtained evidence. Psychologists, epistemologists, and philosophers of science have proposed…

E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…

Identifying collaboration between learners in a course is an important challenge in education for two reasons: First, depending on the courses rules, collaboration can be considered a form of cheating. Second, it helps one to more accurately evaluate each learners competence. While such collaboration identification is already challenging in…

The changes of learning environments and the advancement of learning theories have increasingly demanded for feedback that can describe learning progress trajectories. Effective assessment should be able to evaluate how learners acquire knowledge and develop problem solving skills. Additionally, it should identify what issues these learners have…

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…