Faculty Feedback Research Articles

The Impact of Faculty Feedback on Student Perceptions of Faculty-Student Relationships

The Impact of Faculty Feedback on Student Perceptions of Faculty-Student Relationships

A Polarization-Modulated Laser Frequency-Shifted Feedback System Reducing the Parasitic Noise Intensity by About Three Orders of Magnitude

We propose a parasitic noise suppression laser frequency-shifted feedback system based on polarization modulation, which can reduce the parasitic noise intensity by about 30 dB without affecting the signal of interest by applying different polarization modulations to the parasitic noise and the signal to make them converted to system-insensitive and sensitive states, respectively. Therefore, the proposed system can still get correct information which is originally drowned in parasitic noise. Based on the proposed principle, the displacement of the aluminum block 2 m away from the system is successfully recovered. Furthermore, the vibration of an ordinary carton which is 80 m away from the system is demodulated, and the voice signal near the carton is restored according to the vibration information with much better performance than there is no parasitic noise suppression. During the vibration recovery process, the effective response energy as low as 5.5 photons is achieved in each feedback modulation cycle. The successful implementation of the proposed parasitic noise suppression laser frequency-shifted feedback system based on polarization modulation provides a practical anti-interference and sensitive coherent detection method in weak light signals detection.

Using simulation as a platform to prepare for ear, nose and throat emergencies in the coronavirus disease 2019 era and beyond.

Following limited clinical exposure during the coronavirus disease 2019 pandemic, a simulation-based platform aimed at providing a unique and safe learning tool was established. The aim was to improve the skills, knowledge and confidence of new ENT doctors. The course was developed through 5 iterations over 28 months, moving from a half-day session to 2 full-day courses with more scenarios. Participant, faculty and local simulation team feedback drove course development. High-fidelity scenarios were provided, ranging from epistaxis to stridor, using technology including SimMan3 G mannequin, mask-Ed™ and nasendoscopy simulators. Participant feedback consistently demonstrated that the knowledge and skills acquired enhanced preparedness for working in ENT, with impact being sustained in clinical practice. Preparing healthcare professionals adequately is essential to enhancing patient safety. This simulation course has been effective in supporting new doctors in ENT and has subsequently been rolled out at a national level.

Optimal Reconstruction of Single-Pixel Images through Feature Feedback Mechanism and Attention

The single-pixel imaging technique can reconstruct high-quality images using only a bucket detector with no spatial resolution, and the image quality is degraded in order to meet the demands of real-time applications. According to some studies of algorithm performance, the network model performs differently in simulated and real-world experiments. We propose an end-to-end neural network capable of reconstructing 2D images from experimentally obtained 1D signals optimally. In order to improve the image quality of real-time single-pixel imaging, we built a feedback module in the hidden layer of the recurrent neural network to implement feature feedback. The feedback module fuses high-level features of undersampled images with low-level features through dense jump connections and multi-scale balanced attention modules to gradually optimize the feature extraction process and reconstruct high-quality images. In addition, we introduce a learning strategy that combines mean loss with frequency domain loss to improve the network’s ability to reconstruct complex undersampled images. In this paper, the factors that lead to the degradation of single-pixel imaging are analyzed, and a network degradation model suitable for physical imaging systems is designed. The experiment results indicate that the reconstructed images utilizing the proposed method have better quality metrics and visual effects than the excellent methods in the field of single-pixel imaging.

Examining the use of geriatric standardized patients with baccalaureate nursing students

ABSTRACT The need for clinical placements for undergraduate nursing programs heightened during the COVID-19 pandemic as nursing schools across the country faced restrictions with the high-risk geriatric client population. Nursing students experienced increased anxiety levels, decreased learning opportunities, and uncertainties about the decision to enter the workforce as healthcare professionals. In turn, this amplified the need for faculty support and feedback imperative for student success. One method for mitigating the gap between didactic content and clinical placement is using simulation-based learning experiences. The purpose of this observational study was to examine the impact of a newly developed home health geriatric simulation on student satisfaction and self-confidence in learning among 133 senior-level Baccalaureate nursing students from a large public university. Study measures included the National League of Nursing’s Self-Confidence in Learning Scale (SCLS) and Simulation Design Scale (SDS). The primary outcome was satisfaction and self-confidence in learning. Higher SDS component scores were significantly correlated with higher SCLS scores (all p = <.0001), indicating that high satisfaction among Baccalaureate nursing students in simulation design relates to increased satisfaction and self-confidence in learning. Study findings support using standardized geriatric simulation scenarios to prepare students to communicate and care for older adults.

Internationalization at Home: A Reflection on a Semester-Long Online Collaborative Project Between Canadian and Indian Students

In today’s global community, internationalization offers students a crucial advantage by developing their intercultural competence and global citizenship skills. Recent research on Internationalization at Home (IaH) has shown that students can benefit from this approach even without travelling. There has been minimal research conducted on how internationalization affects students’ attitudes towards environmental sustainability, which is another critical theme in our interconnected world. This study evaluates an IaH initiative’s impact on students’ environmental beliefs and values from Alberta, Canada, and Kerala, India. As an IaH initiative, this project engaged students in online collaboration with students from a different world region. Participants worked collaboratively on four tasks and completed an individual reflection assignment. Student and faculty feedback shows that participants improved their knowledge of environmental issues and their commitment to environmental sustainability. Additionally, students also demonstrated stronger intercultural communication and global citizenship skills.

Neurosurgical Education in Tanzania: The Dar es Salaam Global Neurosurgery Course

Postgraduate neurosurgical training is essential to develop a neurosurgical workforce with the skills and knowledge to address patient needs for neurosurgical care. In Tanzania, the number of neurosurgeons and neurosurgical services offered have expanded in the past 40 years. Training opportunities within the country, however, are not sufficient to meet the needs of residents, specialists, and nurses in neurosurgery, forcing many to train outside the country incurring associated costs and burdens. We report on the Dar es Salaam Global Neurosurgery Course, which aims to provide local training to neurosurgical health care providers in Tanzania and surrounding countries. We report the experience of the Global Neurosurgery Course held in March 2023 in Dar es Salaam, Tanzania. We describe the funding, planning, organization, and teaching methods along with participant and faculty feedback. The course trained 121 participants with 63 faculty-42 from Tanzania and 21 international faculty. Training methods included lectures, hands-on surgical teaching, webinars, case discussions, surgical simulation, virtual reality, and bedside teaching. Although there were challenges with equipment and Internet connectivity, participant feedback was positive, with overall improvement in knowledge reported in all topics taught during the course. International collaboration can be successful in delivering topic-specific training that aims to address the everyday needs of surgeons in their local setting. Suggestions for future courses include increasing training on allied topics to neurosurgery and neurosurgical subspecialty topics, reflecting the growth in neurosurgical capacity and services offered in Tanzania.

Simulation-based training in central venous catheterization for first-year postgraduate students: A prospective study

ABSTRACT Background: The current model of procedure training involves lectures, seminars, observations and personalised education in small groups or by watching videos on digital platforms. Central venous catheterisation (CVC) is an important skill; however, its training largely remains unstructured. There is a need of protocol-based uniform training policy. Aims: The aims and objectives of the study are to prepare and implement simulation-based CVC training module for the 1st year post-graduate students. Materials and Methods: After approval from the institutional ethical committee, 1st year post-graduate students of anaesthesia, medicine and surgery were enroled. Training modules and questionnaires were prepared with discussions amongst faculty. Students’ baseline knowledge regarding the CVC was noted on mannequins along with self-reported confidence. After that, they were subjected to training module. Students repeat knowledge and confidence regarding CVC were noted. In the next few months, procedures performed by post-graduate students were directly observed and rated. Students as well as faculty feedback regarding this teaching module was also collected. Results: Training module was associated with a statistically significant increase in knowledge and self-reported confidence regarding the knowledge and skill of CVC (P &lt; 0.05). Most of the students and faculty agreed regarding the training module utility. Conclusions: A structured simulation module for CVC helped to improve students’ knowledge and confidence about the CVC skill. The module was well accepted by both faculty and students.

Flexible Learning Models Utilizing Different Neural Plasticities

The existing models for vestibulo-ocular reflex (VOR) and optokinetic response (OKR) learning utilize neural circuit structure and capture a few characteristics of these two learning systems. However, it remains unclear how the error signals guide these learning processes. Here, we propose novel dynamic learning models using error feedback in a flexible fashion to account for both VOR and OKR learning. We first used a feedback modulation model and found the error signals play an essential guiding role in gain compensation of wild-type mice. However, this feedback modulation model cannot accurately reproduce gain changes during the recovery period. Therefore, we propose a non-uniform feedback modulation model using flexible plasticity learning rules of different memory sites to take into account the effect of classical linearity models in both training and recovery periods. To further study learning characteristics of gain reduction, we introduce a reversal-phase feedback modulation model and explore the contribution of synaptic plasticity to adaptive learning, in which characteristics and bidirectional synaptic plasticity in the VOR-decrease learning mode can be fully recovered. Taken together, our results suggest that, to explain VOR and OKR learning systems, one needs dynamical models with flexible and multiple components at different or same sites of neuronal circuits.

The SOAP Feedback Training Program.

Accessible and efficient opportunities for health professional faculty to hone feedback skills are limited. In addition, feedback models to apply to the objective structured clinical examination (OSCE) setting are lacking. Annually, paediatric interns from Children's National Hospital and Walter Reed National Military Medical Center participate in an OSCE, which includes faculty observation and immediate feedback to trainees. In 2018, we incorporated the subjective, objective, assessment, plan (SOAP) Feedback Training Program during 20 min of the pre-OSCE faculty orientation. The SOAP Feedback Training Program introduced the SOAP feedback model (subjective, objective, assessment, plan), facilitated practice in pairs and distributed a cognitive aid referencing the model. We evaluated the quality of faculty feedback exchanges during the 2018 OSCE via retrospective video review using the Direct Observation of Clinical Skills Feedback Scale (DOCS-FBS). We compared the results to the 2015 initial evaluation and used focus groups to understand how and why faculty feedback changed. Comparison of the initial evaluation to the post-SOAP Feedback Training Program intervention data using a Wilcoxon signed rank test showed statistically significant improvement in six of eight feedback items on the DOCS-FBS. Causal coding of focus group transcripts revealed that the SOAP Feedback Training Program evoked affective responses, reinforced prior practice in feedback delivery, improved feedback organisation and increased feedback delivery preparation. The SOAP Feedback Training Program is an effective intervention to teach the SOAP feedback model and improve faculty feedback quality in an OSCE setting. It is efficient and low resource, facilitating its potential use in settings beyond the OSCE.

Vision Transformer Customized for Environment Detection and Collision Prediction to Assist the Visually Impaired.

This paper presents a system that utilizes vision transformers and multimodal feedback modules to facilitate navigation and collision avoidance for the visually impaired. By implementing vision transformers, the system achieves accurate object detection, enabling the real-time identification of objects in front of the user. Semantic segmentation and the algorithms developed in this work provide a means to generate a trajectory vector of all identified objects from the vision transformer and to detect objects that are likely to intersect with the user's walking path. Audio and vibrotactile feedback modules are integrated to convey collision warning through multimodal feedback. The dataset used to create the model was captured from both indoor and outdoor settings under different weather conditions at different times across multiple days, resulting in 27,867 photos consisting of 24 different classes. Classification results showed good performance (95% accuracy), supporting the efficacy and reliability of the proposed model. The design and control methods of the multimodal feedback modules for collision warning are also presented, while the experimental validation concerning their usability and efficiency stands as an upcoming endeavor. The demonstrated performance of the vision transformer and the presented algorithms in conjunction with the multimodal feedback modules show promising prospects of its feasibility and applicability for the navigation assistance of individuals with vision impairment.

A neural model of modified excitation/inhibition and feedback levels in schizophrenia.

The strength of certain visual illusions, including contrast-contrast and apparent motion, is weakened in individuals with schizophrenia. Such phenomena have been interpreted as the impaired integration of inhibitory and excitatory neural responses, and impaired top-down feedback mechanisms. To investigate whether and how these factors influence the perceived contrast-contrast and apparent motion illusions in individuals with schizophrenia, we propose a two-layer network, with top-down feedback from layer 2 to layer 1 that can model visual receptive fields (RFs) and their inhibitory and excitatory subfields. Our neural model suggests that illusion perception changes in individuals with schizophrenia can be influenced by altered top-down mechanisms and the organization of the on-center off-surround receptive fields. Alteration of the RF inhibitory surround and/or the excitatory center can replicate the difference of illusion precepts between individuals with schizophrenia within certain clinical states and normal controls. The results show that the simulated top-down feedback modulation enlarges the difference of the model illusion representations, replicating the difference between the two groups. We propose that the heterogeneity of visual and in general sensory processing in certain clinical states of schizophrenia can be largely explained by the degree of top-down feedback reduction, emphasizing the critical role of top-down feedback in illusion perception, and to a lesser extent on the imbalance of excitation/inhibition. Our neural model provides a mechanistic explanation for the modulated visual percepts of contrast-contrast and apparent motion in schizophrenia with findings that can explain a broad range of visual perceptual observations in previous studies. The two-layer motif of the current model provides a general framework that can be tailored to investigate subcortico-cortical (such as thalamocortical) and cortico-cortical networks, bridging neurobiological changes in schizophrenia and perceptual processing.

Differential effect of heteronymous feedback from femoral nerve and quadriceps muscle stimulation onto soleus H-reflex.

Excitatory feedback from muscle spindles, and inhibitory feedback from Golgi tendon organs and recurrent inhibitory circuits are widely distributed within the spinal cord to modulate activity between human lower limb muscles. Heteronymous feedback is most commonly studied in humans by stimulating peripheral nerves, but the unique effect of non-spindle heteronymous feedback is difficult to determine due to the lower threshold of excitatory spindle axons. A few studies suggest stimulation of the muscle belly preferentially elicits non-spindle heteronymous feedback. However, there remains a lack of consensus on the differential effect of nerve and muscle stimulation onto the H-reflex, and the relation of the heteronymous effects onto H-reflex compared to that onto ongoing EMG has not been determined. In this cross-sectional study, we compared excitatory and inhibitory effects from femoral nerve and quadriceps muscle belly stimulation onto soleus H-reflex size in 15 able-bodied participants and in a subset also compared heteronymous effects onto ongoing soleus EMG at 10% and 20% max. Femoral nerve stimulation elicited greater excitation of the H-reflex compared to quadriceps stimulation. The differential effect was also observed onto ongoing soleus EMG at 20% max but not 10%. Femoral nerve and quadriceps stimulation elicited similar inhibition of the soleus H-reflexes, and these results were better associated with soleus EMG at 20%. The results support surface quadriceps muscles stimulation as a method to preferentially study heteronymous inhibition at least in healthy adults. The primary benefit of using muscle stimulation is expected to be in persons with abnormal, prolonged heteronymous excitation. These data further suggest heteronymous feedback should be evaluated with H-reflex or onto ongoing EMG of at least 20% max to identify group differences or modulation of heteronymous feedback in response to treatment or task.

Autonomy Maps: Building a Shared Mental Model for Progressive Resident Operative Autonomy on the Road to Entrustable Professional Activities (EPAs)

Our residents expressed dissatisfaction with operative autonomy and faculty feedback regarding technical skills. They reported variability among faculty regarding allowed operative autonomy. Our goals were to establish a shared mental model among residents and faculty regarding intraoperative performance expectations. We asked faculty to assign a level of expected autonomy (Zwisch scale) for various steps of common procedures according to the resident post-graduate year. Through an iterative process, the maps were standardized across service lines. The resulting "Autonomy Maps" were distributed to the faculty and residents. We held educational sessions and set expectations for use. Selected benchmarks were incorporated into resident end-of-rotation assessment forms. Initial operative case mapping identified variability in faculty expectations for a given post-graduate year and procedure. Residents reported improved satisfaction with understanding expectations regarding operative performance. Establishing autonomy benchmarks facilitated more specific feedback regarding residents' technical skills. Faculty expectations for resident operative autonomy are variable. Autonomy Maps provide structure for a shared mental model between faculty and residents for progressive operative autonomy and serve as a framework for expectations that improve resident satisfaction. Case-specific technical benchmarks are useful tools for assessing residents' technical milestones.

Better Together: Development and Implementation of Fellow Group Evaluationsof Faculty.

High-quality trainee evaluations of faculty are essential for meaningful faculty development and for improving the clinical learning environment. However, concerns about anonymity can limit usefulness of trainee evaluations, particularly in smaller programs, such as subspecialty fellowships. To develop and implement a fellow-driven group evaluation process to enhance trainee confidentiality and generate high-quality feedback for pulmonary and critical care medicine faculty. A novel process was developed for faculty evaluation and feedback consisting of quarterly, structured, fellow-led group evaluation sessions focused on collecting confidential, behaviorally oriented, actionable feedback for faculty. Upper-year fellow moderators utilized a standard format to structure discussion, generating strengths and areas for growth for each faculty member while explicitly asking for input from fellows with divergent perspectives. Moderators compiled anonymized session notes for the program director, who delivered feedback to individual faculty. After the first six sessions, an electronic survey was distributed to assess fellow perceptions of the group evaluation model. Thirty-seven faculty members were evaluated in 11 group sessions over 42 months. Fellows rated group-generated feedback as more confidential, more specific, more accurate, more efficient, more actionable, and less biased when compared with individual written evaluations (P < 0.01 for all categories). The authors successfully developed and implemented a process for fellow-led group evaluation of faculty, designed to facilitate fellow confidentiality and enrich the quality of feedback. Fellows preferred the group evaluation process and perceived group-generated feedback more favorably compared with individual written evaluations.

The NYU Data Catalog: a modular, flexible infrastructure for data discovery.

Researchers at New York University (NYU) Grossman School of Medicine contacted the Health Sciences Library for help with locating large datasets for reuse. In response, the library developed and maintained the NYU Data Catalog, a public-facing data catalog that has supported not only faculty acquisition of data but also the dissemination of the products of their research in various ways. The current NYU Data Catalog is built upon the Symfony framework with a tailored metadata schema reflecting the scope of faculty research areas. The project team curates new resources, including datasets and supporting software code, and conducts quarterly and annual evaluations to assess user interactions with the NYU Data Catalog and opportunities for growth. Since its launch in 2015, the NYU Data Catalog underwent a number of changes prompted by an increase in the disciplines represented by faculty contributors. The catalog has also utilized faculty feedback to enhance support of data reuse and researcher collaboration through alterations to its schema, layout, and visibility of records. These findings demonstrate the flexibility of data catalogs as a platform for enabling the discovery of disparate sources of data. While not a repository, the NYU Data Catalog is well-positioned to support mandates for data sharing from study sponsors and publishers. The NYU Data Catalog makes the most of the data that researchers share and can be harnessed as a modular and adaptable platform to promote data sharing as a cultural practice.

Addressing the semi-open set dialect recognition problem under resource-efficient considerations

This work presents a resource-efficient solution for the spoken dialect recognition task under semi-open set evaluation scenarios, where a closed set model is exposed to unknown class inputs. We have primarily explored the task 2 of the OLR 2020 challenge for our experiments. In this task, three Chinese dialects Hokkien, Sichuanese, and Shanghainese, are to be recognized. For evaluation, along with the three target dialects, utterances from other unknown classes are also included. We find that the top-performing submissions and the baseline system did not propose solutions that explicitly address the semi-open set scenario. This work pays special attention to the semi-open set nature of the problem and analyzes how the unknown utterances can potentially degrade the overall performance if not treated separately. We train our main dialect classifier with the ECAPA-TDNN architecture and 40-dimensional MFCC from the training data of three dialects. We propose a confidence-assessment algorithm and combine the TDNN performance from both end-to-end and embedding extractor approaches. We then frame the semi-open set scenario as a constrained optimization problem. By solving it, we prove that the performance degradation by the unknown utterances is minimized if the corresponding softmax prediction is equally confused among the target outputs. Based on this criterion, we develop different feedback modules in our system. These modules work on the novelty detection principles and flag unknown class utterances as anomaly. The prediction score of the corresponding utterance is then penalized by flattening. The proposed system achieves Cavg(×100) score of 8.50 and EER (%) of 9.77. Averaging both metrics, the score for our system outperforms the winning submission. Due to the proposed semi-open set adaptations, our system achieves this performance using much less training data and computation resources than the top-performing submissions. Additionally, to verify the broader applicability of the proposed semi-open set solution, we experiment with two other dialect recognition tasks covering English and Arabic languages and larger database sizes.

Strategies for developing faculty confidence and competencies to mentor quality improvement DNP projects.

DNP faculty who mentor students in quality improvement (QI) DNP projects often lack essential knowledge of QI principles. The purpose of this article is to guide DNP programs in developing confident and competent faculty mentors for QI DNP projects, facilitating DNP student success. At a multi-campus practice- and research-intensive university, strategies employed to teach College of Nursing faculty essential knowledge of QI principles comprise structural and process components. Structural supports standardize faculty workload, promote potential for collaborative scholarship, and provide instructional and resource support for faculty mentors. Organizational processes facilitate identification of practice sites and meaningful projects. A College of Nursing and university Institutional Review Board collaboration established policy to guide human subjects protection regarding DNP project activity, streamlining and standardizing the process. Library support mechanisms, access to ongoing faculty QI training and resources, and faculty feedback processes to improve QI faculty development are ongoing and sustained. Peer coaching provides continued support for faculty development. Initial process outcomes indicate that implemented strategies are well-received by faculty. The transition to competency-based education provides opportunities to create tools to measure multiple student quality and safety competencies highlighted in Domain 5 of The Essentials: Core Competencies for Professional Nursing Education and inform future directions for faculty development essential to support student success.

Progressive Feedback Residual Attention Network for Cardiac Magnetic Resonance Imaging Super-Resolution.

Atrial fibrillation (AF) is an increasing medical burden worldwide, and its pathological manifestations are atrial tissue remodeling and low-pressure atrial tissue fibrosis. Due to the inherent defects of medical image data acquisition systems, the acquisition of high-resolution cardiac magnetic resonance imaging (CMRI) faces many problems. In response to these problems, we propose the Progressive Feedback Residual Attention Network (PFRN) for CMRI super-resolution. Specifically, we directly perform feature extraction on low-resolution images, retain feature information to a large extent, and then build multiple independent progressive feedback modules to extract high-frequency details. To accelerate network convergence and improve image reconstruction quality, we implement the MS-SSIM-L1 loss function. Furthermore, we utilize the residual attention stack module to explore the image's internal relevance and extract the low-resolution image's detailed features. Extensive benchmark evaluation shows that PFRN can improve the detailed information of the image SR reconstruction results, and the reconstructed CMRI has a better visual effect.

HaptGlove-Untethered Pneumatic Glove for Multimode Haptic Feedback in Reality-Virtuality Continuum.

Novel haptics technologies are urgently needed to bridge the gap between entirely physical world and fully digital environment to render a more realistic and immersive human-computer interaction. Current virtual reality (VR) haptic gloves either deliver limited haptic feedback or are bulky and heavy. The authors develop a haptic glove or HaptGlove, an untethered and lightweight pneumatic glove, that allows users to "physically" interact in a VR environment and enables both kinesthetic and cutaneous sensations naturally and realistically. Integrated with five pairs of haptic feedback modules and fiber sensors, HaptGlove provides variable stiffness force feedback and fingertip force and vibration feedback, allowing users to touch, press, grasp, squeeze, and pull various virtual objects and feel the dynamic haptic changes. Significant improvements in VR realism and immersion areobserved in a user study with participants achieving 78.9% accuracy in sorting six virtual balls of different stiffnesses. Importantly, HaptGlove facilitates VR training, education, entertainment, and socialization in a reality-virtuality continuum.