Does tailoring instructional style to a medical student\u27s self-perceived learning style improve performance when teaching intravenous catheter placement? A randomized controlled study.

BACKGROUND: Students may have different learning styles. It is unclear, however, whether tailoring instructional methods for a student\u27s preferred learning style improves educational outcomes when teaching procedures. The authors sought to examine whether teaching to a student\u27s self-perceived learning style improved the acquisition of intravenous (IV) catheter placement skills. The authors hypothesized that matching a medical student\u27s preferred learning style with the instructor\u27s teaching style would increase the success of placing an IV catheter. METHODS: Using the VARK model (i.e., visual [V], auditory [A], read/write [R] and kinesthetic [K]), third-year medical students reported their self-perceived learning style and were subsequently randomized to instructors who were trained to teach according to a specific learning format (i.e., visual, auditory). Success was gauged by: 1) the placement of an IV on the first attempt and 2) the number of attempts made until an IV line was successfully placed. RESULTS: The average number of attempts in the matched learning style group was 1.53, compared to 1.64 in the unmatched learning style group; however, results were not statistically significant. Both matched and unmatched groups achieved a similar success rate (57 and 58 %, respectively). Additionally, a comparison of success between the unmatched and matched students within each learning style modality yielded no statistical significance. CONCLUSIONS: Results suggest that providing procedural instruction that is congruent with a student\u27s self-perceived learning style does not appear to improve outcomes when instructing students on IV catheter placement

Supporting Memorization and Problem Solving with Spatial Information Presentations in Virtual Environments

While it has been suggested that immersive virtual environments could provide benefits for educational applications, few studies have formally evaluated how the enhanced perceptual displays of such systems might improve learning. Using simplified memorization and problem-solving tasks as representative approximations of more advanced types of learning, we are investigating the effects of providing supplemental spatial information on the performance of learning-based activities within virtual environments. We performed two experiments to investigate whether users can take advantage of a spatial information presentation to improve performance on cognitive processing activities. In both experiments, information was presented either directly in front of the participant or wrapped around the participant along the walls of a surround display. In our first experiment, we found that the spatial presentation caused better performance on a memorization and recall task. To investigate whether the advantages of spatial information presentation extend beyond memorization to higher level cognitive activities, our second experiment employed a puzzle-like task that required critical thinking using the presented information. The results indicate that no performance improvements or mental workload reductions were gained from the spatial presentation method compared to a non-spatial layout for our problem-solving task. The results of these two experiments suggest that supplemental spatial information can support performance improvements for cognitive processing and learning-based activities, but its effectiveness is dependent on the nature of the task and a meaningful use of space

Early Childhood ABA: Issues of Early ASD Detection and Access to Intervention

This paper provides an overview of ABA, summarizes findings from studies of early childhood ABA with a focus on intervention dosage, and addresses the influence of demographics and culture on early ASD detection and access to early childhood ABA intervention. Although, this paper is not inclusive of all the ABA studies conducted between 1987-2007 and beyond, it summarizes the findings of some of the historical studies in early childhood ABA. These historical studies were located through two systematic reviews including studies between the years 1987- 2007 and selected if they met the following criteria: (1) intervention was based on behavioral principals (2) participants were five years of age or younger at the onset of intervention (3) intervention was in-home or clinic-based (4) utilized a group research design. A total of seven studies met the inclusion criteria. All seven studies reported increasing intellectual, educational, and behavioral gains for children with ASD. However, three of the studies did not report significant differences across all outcome measures favoring the treatment group. The seven studies reported mixed findings regarding treatment dosage with weekly treatment dosage ranging from 40 to 19.45 hours. Additional findings indicated that demographics and culture should be considered as they influence the early detection of ASD and access to intervention. Based on these findings, future research should further investigate how these variables along with others moderate or mediate early childhood ABA outcomes associated with early ASD detection and access to intervention

Effectiveness of Two Keyboarding Instructional Approaches on the Keyboarding Speed, Accuracy, and Technique of Elementary Students

Background: Keyboarding skill development is important for elementary students. Limited research exists to inform practice on effective keyboarding instruction methods. Method: Using a quasi-experimental design, we examined the effectiveness of Keyboarding Without Tears® (n = 786) in the experimental schools compared to the control schools who used the district standard instructional approach of free web-based activities (n = 953) on improving keyboarding skills (speed, accuracy, and technique) in elementary students. Results: The results showed significant improvements in keyboarding speed and accuracy in all schools for all grades favoring the experimental schools compared to the control schools. Significant differences in improvements in keyboarding technique were found with large effect sizes favoring the experimental schools for kindergarten to the second grade and small effect sizes favoring the control schools for the third to fifth grade. Conclusion: Professionals involved in assisting with keyboarding skill development in children are recommended to begin training in these skills in early elementary grades, especially to assist in proper keyboarding technique development. While using free web-based activities are beneficial to improving keyboarding speed and accuracy, as well as keyboarding technique, using a developmentally-based curriculum, such as Keyboarding Without Tears®, may further enhance improvements in the keyboarding skills of elementary students

On the Importance of Visual Context for Data Augmentation in Scene Understanding

Performing data augmentation for learning deep neural networks is known to be important for training visual recognition systems. By artificially increasing the number of training examples, it helps reducing overfitting and improves generalization. While simple image transformations can already improve predictive performance in most vision tasks, larger gains can be obtained by leveraging task-specific prior knowledge. In this work, we consider object detection, semantic and instance segmentation and augment the training images by blending objects in existing scenes, using instance segmentation annotations. We observe that randomly pasting objects on images hurts the performance, unless the object is placed in the right context. To resolve this issue, we propose an explicit context model by using a convolutional neural network, which predicts whether an image region is suitable for placing a given object or not. In our experiments, we show that our approach is able to improve object detection, semantic and instance segmentation on the PASCAL VOC12 and COCO datasets, with significant gains in a limited annotation scenario, i.e. when only one category is annotated. We also show that the method is not limited to datasets that come with expensive pixel-wise instance annotations and can be used when only bounding boxes are available, by employing weakly-supervised learning for instance masks approximation.Comment: Updated the experimental section. arXiv admin note: substantial text overlap with arXiv:1807.0742