Predicting STEM Achievement with Learning Management System Data: Prediction Modeling and a Test of an Early Warning System

ABSTRACT Learning management systems log users' behaviors, which can be used to predict achievement in a course. This paper examines the implications of data representations (e.g., dichotomous vs. count vs. principled, per learning theory) and applies forward selection algorithms to predict achievement in a biology course. Accuracy is compared across models. The paper closes with a description of an ongoing experiment that employs the prediction model, tests how multiple versions of an early alert message impact students' access of learning resources, and compares the influence of messaging approaches related to personalization and feedback

Establishing Vibration-Based Tactile Line Profiles for Use in Multimodal Graphics

Vibration plays a significant role in the way users interact with touchscreens. For many users, vibration affords tactile alerts and other enhancements. For eyes-free users and users with visual impairments, vibration can also serve a more primary role in the user interface, such as indicating streets on maps, conveying information about graphs, or even specifying basic graphics. However, vibration is rarely used in current user interfaces beyond basic cuing. Furthermore, designers and developers who do actually use vibration more extensively are often unable to determine the exact properties of the vibration signals they are implementing, due to out-of-the-box software and hardware limitations. We make two contributions in this work. First, we investigate the contextual properties of touchscreen vibrations and how vibrations can be used to effectively convey traditional, embossed elements, such as dashes and dots. To do so, we developed an open source, Android-based library to generate vibrations that are perceptually salient and intuitive, improving upon existing vibration libraries. Second, we conducted a user study with 26 blind or visually impaired users to evaluate and categorize the effects with respect to traditional tactile line profiles. We have established a range of vibration effects that can be reliably generated by our haptic library and are perceptible and distinguishable by users