Using assessment practice to evaluate the legal skills curriculum

A comprehensive audit of the skills curriculum offered to students in a Bachelor of Laws program yielded important insights about the collective impact of assessment tasks on the hidden and operational skills curriculum. This qualitative case study supports the views (1) that assessment tasks provide significant skills practice and performance opportunities for students; (2) that assessment provides students with important cues about what type of learning is valued; and (3) that review of assessment practices across the curriculum can provide important information for curricular reform

DEPENDABLE NEURAL NETWORKS FOR SAFETY CRITICAL TASKS

Neural Networks (NNs) have demonstrated impressive performance improvement over the last decade in safety critical tasks, e.g., perception for autonomous vehicles, medical image analysis, etc., but, NNs performing safety critical tasks poses a risk for harm, as NN performance often degrades when the operating domain changes. Previous work has proposed new training paradigms to improve NN generalization to new operating domains but fails to predict what the NN performance in the new operating domain will be. In addition, performance metrics in Machine Learning (ML) focus on the average probability of success but do not differentiate failures that cause harm from those that do not. In this thesis, we leverage structure in NN behavior based on the environment context and the NN embedding to predict NN performance for safety critical tasks in unconstrained environments. We denote factors relating to the environment context as context features. First, we define performance metrics that capture both the probability of task success and the probability of causing harm. We then address the task of predicting NN performance in a novel operating domain as Network Generalization Prediction (NGP), and we derive a NGP algorithm from a finite test set using known context features. Second, we extend our NGP algorithm to identify which context features impact NN performance from a set of observed context features, where it is not known a priori what features are important. Third, we map structure in the NN embedding space that is informative about NN performance and derive a NGP algorithm based on how unlabeled novel operating domain images map into the embedding space. Fourth, we investigate safety functions for NNs. Safety functions are standard practice in functional safety where an external function is added to a process, e.g., a chemical reaction, to improve the overall safety. We introduce the concept of safety functions for NNs and show that external logic around NNs can improve the safety for a robot control task and image classification tasks. We demonstrate these methods on pertinent real-world tasks using state-of-the-art NNs, e.g., DenseNet for melanoma classification and FasterRCNN for pedestrian detection

Impact of Seizure Alert Dogs in Epilepsy

Epilepsy, a seizure disorder, is characterized by a disruption of electrical activity in the brain. Most commonly, epilepsy is diagnosed after a person has two or more seizures (Shafer, 2013). Worldwide 65 million people have epilepsy, 3.4 million of which are in the United States; 150,000 people are added to that number every year (Shafer, 2013). “One-third … of people with epilepsy … live with uncontrollable seizures because no available treatment works for them” (Shafer, 2013). Seizure Alert dogs (SADs) are certified service animals under the federal law that detect when a person is going to have a seizure and notify them before the seizure occurs (Epilepsy Foundation, 2007). The seizure alert dogs can also be trained to assist during and after the seizure by staying “close to their companions for the duration of the seizure, as well as fetch medications, a telephone or caretaker” (Epilepsy Foundation, 2007). The purpose of this Evidence-Based Practice review is to determine the effectiveness of seizure alert dogs (SAD) in reducing the frequency of seizures in those diagnosed with epilepsy. Healthcare providers can educate patients about alternatives to medical seizure therapy and can advocate for patients to own a SAD to improve patient outcomes and quality of life for patients with epilepsy

Shadowing and goShadow: Tools to Discover and Co-design Ideal Care Experiences

Adding more funding and/or staff does not always improve patient experience. This audit focuses on the benefits of shadowing and an innovative "goShadow" app that provides accurate, quantitative feedback on the patients' care experiences

Exploring the design space of therapeutic robot companions for children

Robots that lend social and emotional support to their users have the potential to extend the quality of care that humans can provide. However, developing robotic aids to address symptoms of loneliness, anxiety and social isolation can be especially challenging due to factors that are complex and multi-faceted. Using a user-centered approach, a prototype therapeutic robot, TACO, was developed. The design of this robot was closely informed by a comprehensive need finding process which included a detailed literature review, ethical analysis, interviews with pediatric domain experts, and a site visit to a pediatric hospital. The prototype robot was evaluated over the course of several structured play sessions, using short interviews with children as well as a modified version of the SOFIT testing procedure. Results from early-stage testing suggest that TACO was well-liked, children found playing with it engaging and frequently exhibited affective behaviors like cuddling and stroking. These findings motivate follow-on work to further advance its design and to test its effectiveness as a therapeutic tool

Ready or not? Expectations of faculty and medical students for clinical skills preparation for clerkships

Background: Preclerkship clinical-skills training has received increasing attention as a foundational preparation for clerkships. Expectations among medical students and faculty regarding the clinical skills and level of skill mastery needed for starting clerkships are unknown. Medical students, faculty teaching in the preclinical setting, and clinical clerkship faculty may have differing expectations of students entering clerkships. If students' expectations differ from faculty expectations, students may experience anxiety. Alternately, congruent expectations among students and faculty may facilitate integrated and seamless student transitions to clerkships. Aims: To assess the congruence of expectations among preclerkship faculty, clerkship faculty, and medical students for the clinical skills and appropriate level of clinical-skills preparation needed to begin clerkships. Methods: Investigators surveyed preclinical faculty, clerkship faculty, and medical students early in their basic clerkships at a North American medical school that focuses on preclerkship clinical-skills development. Survey questions assessed expectations for the appropriate level of preparation in basic and advanced clinical skills for students entering clerkships. Results: Preclinical faculty and students had higher expectations than clerkship faculty for degree of preparation in most basic skills. Students had higher expectations than both faculty groups for advanced skills preparation. Conclusions: Preclinical faculty, clerkship faculty, and medical students appear to have different expectations of clinical-skills training needed for clerkships. As American medical schools increasingly introduce clinical-skills training prior to clerkships, more attention to alignment, communication, and integration between preclinical and clerkship faculty will be important to establish common curricular agendas and increase integration of student learning. Clarification of skills expectations may also alleviate student anxiety about clerkships and enhance their learning