In studies that generate course recommendations based on similarity, the typical enrollment data used for model training consists only of one record per student-course pair. In this study, we explore and quantify the additional signal present in course transaction data, which includes a more granular account of student administrative interactions…

Selecting courses in an open-curriculum education program is a difficult task for students and academic advisors. Course recommendation systems nowadays can be used to reduce the complexity of this task. To control the recommendation error, we argue that course recommendations need to be provided together with "statistical" confidence.…

Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…

We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Technological and informational literacies, as described in the critical literacies advancement model are essential skills in today's technology-dependent society. In this paper, we illustrate how educators, by using social media (especially memes), can help students develop these and other literacies and thinking skills. These skills can lead to…

Along with the advent of MOOCs and other online learning platforms such as Khan Academy, the role of online education has continued to grow in relation to that of traditional on-campus instruction. Rather than tackle the problem of evaluating large educational units such as entire online courses, this paper approaches a smaller problem: exploring…

Misconceptions have been an important area of study in STEM education towards improving our understanding of learners' construction of knowledge. The advent of largescale tutoring systems has given rise to an abundance of data in the form of learner question-answer logs in which signatures of misconceptions can be mined. In this work, we explore…

The purpose of this study was to investigate the effects of computerized and traditional ear training methods on the aural skills abilities of elementary music students. The sample consisted of 20 students who were randomly assigned to either an experimental or control group. The experimental group was taught for five sessions using computerized…

Questionnaire refinement and a process for selecting items for elimination are important tools for survey developers. One of the major obstacles in questionnaire refinement and elimination in surveys lies in one's ability to adequately and appropriately reconstruct a survey. Often times, surveys can be long and strenuous on the respondent,…

Online adaptive tutoring systems are increasingly being used in classrooms as a way to provide guided learning for students. Such tutors have the potential to provide tailored feedback based on specific student needs and misunderstandings. Bayesian knowledge tracing (BKT) is used to model student knowledge when knowledge is assumed to be changing…

Interactive Strategy Training for Active Reading and Thinking (iSTART) is an intelligent tutoring system that supports reading comprehension through self-explanation (SE) training. This study tested how two metacognitive features, presented in a 2 x 2 design, affected students' SE scores during training. The "performance notification"…

The goal of this paper is to use Knowledge Tracing to augment the results obtained from an experiment that investigated the effects of practice schedules using an intelligent tutoring system for fractions. Specifically, this experiment compared different practice schedules of multiple representations of fractions: representations were presented to…

In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…