We tested the hypothesis that underrepresented students in active-learning classrooms experience narrower achievement gaps than underrepresented students in traditional lecturing classrooms, averaged across all science, technology, engineering, and mathematics (STEM) fields and courses. We conducted a comprehensive search for both published and unpublished studies that compared the performance of underrepresented students to their overrepresented classmates in active-learning and traditional-lecturing treatments. This search resulted in data on student examination scores from 15 studies (9,238 total students) and data on student failure rates from 26 studies (44,606 total students). Bayesian regression analyses showed that on average, active learning reduced achievement gaps in examination scores by 33% and narrowed gaps in passing rates by 45%. The reported proportion of time that students spend on in-class activities was important, as only classes that implemented high-intensity active learning narrowed achievement gaps. Sensitivity analyses showed that the conclusions are robust to sampling bias and other issues. To explain the extensive variation in efficacy observed among studies, we propose the heads-and-hearts hypothesis, which holds that meaningful reductions in achievement gaps only occur when course designs combine deliberate practice with inclusive teaching. Our results support calls to replace traditional lecturing with evidence-based, active-learning course designs across the STEM disciplines and suggest that innovations in instructional strategies can increase equity in higher education.

Harassment by cyberbullies is a significant phenomenon on the social media. Existing works for cyberbullying detection have at least one of the following three bottlenecks. First, they target only one particular social media platform (SMP). Second, they address just one topic of cyberbullying. Third, they rely on carefully handcrafted features of the data. We show that deep learning based models can overcome all three bottlenecks. Knowledge learned by these models on one dataset can be transferred to other datasets. We performed extensive experiments using three real-world datasets: Formspring (˜12k posts), Twitter (˜16k posts), and Wikipedia(˜100k posts). Our experiments provide several useful insights about cyberbullying detection. To the best of our knowledge, this is the first work that systematically analyzes cyberbullying detection on various topics across multiple SMPs using deep learning based models and transfer learning.

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Like the vertebrate spinal cord, the insect ventral nerve cord (VNC) mediates limb sensation and motor control. Here, we applied automated tools for electron microscopy (EM) volume alignment, neuron reconstruction, and synapse prediction to create a draft connectome of theDrosophilaVNC. To interpret the VNC connectome, it is crucial to know its relationship with the rest of the body. We therefore mapped the muscle targets of leg and wing motor neurons in the connectome by comparing their morphology to genetic driver lines, dye fills, and x-ray holographic nano-tomography volumes of the fly leg and wing. Knowing the outputs of the connectome allowed us to identify neural circuits that coordinate the wings with the middle and front legs during escape takeoff. We provide the draft VNC connectome and motor neuron atlas, along with tools for programmatic and interactive access, as community resources.

Animals rely on sensory cues to classify objects in their environment and respond appropriately. However, the spatial structure of those sensory cues can greatly impact when, where and how they are perceived. In this study, we examined the relative roles of visual and chemosensory cues in the mate recognition behavior of fruit flies (Drosophila melanogaster) using a robotic fly dummy that was programmed to interact with individual males. By pairing male flies with dummies of various shapes, sizes and speeds, or coated with different pheromones, we determined that visual and chemical cues play specific roles at different points in the courtship sequence. Vision is essential for determining whether to approach a moving object and initiate courtship, and males were more likely to begin chasing objects with the same approximate dimensions as another fly. However, whereas males were less likely to begin chasing larger dummies, once started, they would continue chasing for a similar length of time regardless of the dummy's shape. The presence of female pheromones on the moving dummy did not affect the probability that males would initiate a chase, but did influence how long they would continue chasing. Male pheromone both inhibits chase initiation and shortens chase duration. Collectively, these results suggest that male D. melanogaster use different sensory cues to progress through the courtship sequence: visual cues are dominant when deciding whether to approach an object whereas chemosensory cues determine how long the male pursues its target.