Brains–Computers–Machines: Neural Engineering in Science Classrooms

Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This Feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering into the classroom.     

A Campus-Wide Investigation of Clicker Implementation: The Status of Peer Discussion in STEM Classes

At the University of Maine, middle and high school teachers observed more than 250 university science, technology, engineering, and mathematics classes and collected information on the nature of instruction, including how clickers were being used. Comparisons of classes taught with (n = 80) and without (n = 184) clickers show that, while instructional behaviors differ, the use of clickers alone does not significantly impact the time instructors spend lecturing. One possible explanation stems from the observation of three distinct modes of clicker use: peer discussion, in which students had the opportunity to talk with one another during clicker questions; individual thinking, in which no peer discussion was observed; and alternative collaboration, in which students had time for discussion, but it was not paired with clicker questions. Investigation of these modes revealed differences in the range of behaviors, the amount of time instructors lecture, and how challenging the clicker questions were to answer. Because instructors can vary their instructional style from one clicker question to the next, we also explored differences in how individual instructors incorporated peer discussion during clicker questions. These findings provide new insights into the range of clicker implementation at a campus-wide level and how such findings can be used to inform targeted professional development for faculty.     

Assessing the special education professional development needs of northern Malawian schoolteachers

This research examines special needs education professional development needs among both general and special education schoolteachers in northern Malawi. A semi‐structured questionnaire with open and close‐ended questions was used for the research. Quantitative and thematic analyses were conducted to determine the extent to which teachers believe that students with disabilities should be educated together with students without disabilities, the importance of professional development for teaching students with disabilities, prioritised professional development needs regarding special education knowledge, and self‐identified needs for successful special education classrooms. Results indicate that teachers are generally in favour of inclusive practices and identify a high need for special education professional development. Participants identified training and resources to teach students with visual impairments or auditory impairments as a high priority. Participants noted a need for improved infrastructure, more educational materials, and recognition by the government for work in special education.     

Guiding Low Spatial Ability Individuals through Visual Cueing: The Dual Importance of Where and When to Look

Research suggests that spatial ability may predict success in complex disciplines including anatomy, where mastery requires a firm understanding of the intricate relationships occurring along the course of veins, arteries, and nerves, as they traverse through and around bones, muscles, and organs. Debate exists on the malleability of spatial ability, and some suggest that spatial ability can be enhanced through training. It is hypothesized that spatial ability can be trained in low-performing individuals through visual guidance. To address this, training was completed through a visual guidance protocol. This protocol was based on eye-movement patterns of high-performing individuals, collected via eye-tracking as they completed an Electronic Mental Rotations Test (EMRT). The effects of guidance were evaluated using 33 individuals with low mental rotation ability, in a counterbalanced crossover design. Individuals were placed in one of two treatment groups (late or early guidance) and completed both a guided, and an unguided EMRT. A third group (no guidance/control) completed two unguided EMRTs. All groups demonstrated an increase in EMRT scores on their second test (P < 0.001); however, an interaction was observed between treatment and test iteration (P = 0.024). The effect of guidance on scores was contingent on when the guidance was applied. When guidance was applied early, scores were significantly greater than expected (P = 0.028). These findings suggest that by guiding individuals with low mental rotation ability “where” to look early in training, better search approaches may be adopted, yielding improvements in spatial reasoning scores. It is proposed that visual guidance may be applied in spatial fields, such as STEMM (science, technology, engineering, mathematics and medicine), surgery, and anatomy to improve student's interpretation of visual content. Anat Sci Educ. © 2018 American Association of Anatomists.     

Automatic path planning for an unmanned drone with constrained flight dynamics

In the article we solve path planning task for an agent being multirotor unmanned aerial vehicle (multicopter). We propose an approach of estimating path geometry constraints based on UAV flight dynamics model and control constraints. Than we introduce a new path finding method which takes into consideration those geometry constraints and study this method both theoretically and empirically.     

Assessing library topics using sentiment analysis in R: a discussion and code sample

Abstract

This article discusses the use of R programing language for executing a sentiment analysis of tweets pertaining to library topics. This discussion is situated within the literature of marketing and management sciences, which is employing methods of machine learning and business intelligence to make informed decision-making, and library administration, which has expressed great interest in social media engagement within its literature but has yet to adopt these types of analysis. Presented in this article is a sample code with instructions on how users may execute it within R to retrieve and analyze tweets relevant to library services. Two examples created using the code (analysis of top librarians’ tweets and analysis of posts about major book publishers) are used to demonstrate the functionality of the code. The code presented in this article may be used by libraries to analyze tweets about their library and library-related topics, which, in turn, may inform management and marketing design.