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Building a student performance prediction model that is both practical and understandable for users is a challenging task fraught with confounding factors to collect and measure. Most current prediction models are difficult for teachers to interpret. This poses significant problems for model use (e.g. personalizing education and intervention) as well as(More)
Neuronal activity-dependent gene transcription is a key feature of long-lasting synaptic strengthening associated with learning and memory, as well as activity-dependent neuroprotection. To comprehensively determine the molecular alterations, we carried out genome-wide microarray analysis in cultured rat cortical neurons treated with specific(More)
UNLABELLED Etiologic diagnoses of lower respiratory tract infections (LRTI) have been relying primarily on bacterial cultures that often fail to return useful results in time. Although DNA-based assays are more sensitive than bacterial cultures in detecting pathogens, the molecular results are often inconsistent and challenged by doubts on false positives,(More)
Microelectrode arrays (MEAs) provide a means to investigate the electrophysiological behavior of neuronal systems through the measurements from neuronal culture preparations. Changes in activity patterns of neuronal networks are usually detected by applying neural chemicals. Because of the difficulties of fabricating the arrays, and the delicate and less(More)
In this paper we propose an automated strategy to assess participation in a multi-mode math discourse environment called Virtual Math Teams with Geogrebra (VMTwG). A holistic participation clustering algorithm is applied through the lens of activity theory. Our activity theory-informed algorithm is a step toward accelerating heuristic approaches to(More)
Designing kiosk touch screen interfaces challenges our basic knowledge of human-computer interaction. Touch screens are used by people of all ages and educational levels for a wide variety of applications. An empirical study on a kiosk touch screen design was conducted to test the cues and factors influencing user performance by examining design elements(More)
The goal of the present study was to uncover new insights about the learning analytics community by analyzing Twitter archives from the past four Learning Analytics and Knowledge (LAK) conferences. Through descriptive analysis, interaction network analysis, hashtag analysis, and topic modeling, we found: extended coverage of the community over the years;(More)
Developing new methods and technologies in order to pattern neurons into regular networks is of utmost scientific interest in the field of neurological research. An efficient method here is developed for trapping neurons and constructing ordered neuronal networks on bioelectronic chips by using arrayed negative dielectrophoretic (DEP) forces. A special(More)
This study proposes a process-oriented, automatic, formative assessment model for small group learning based on complex systems theory using a small dataset from a technology-mediated, synchronous mathematics learning environment. We first conceptualize small group learning as a complex system and explain how group dynamics and interaction can be modeled(More)