scholarly journals LO81: Bridging the GAP: A deliberate practice method for learning Genital Abnormalities in Prepubescent girls

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S35-S36
Author(s):  
K. Boutis ◽  
A. Davis ◽  
M. Pecarcic ◽  
M. Pusic ◽  
M. Shouldice ◽  
...  
Keyword(s):  
Child Abuse ◽  
Sensitivity And Specificity ◽  
Performance Metrics ◽  
Deliberate Practice ◽  
Pediatric Emergency ◽  
Learning Curves ◽  
Future Research ◽  
Physical Examination Skill ◽  
On Line ◽  
On Line Learning

Introduction: Correctly identifying pathology in pre-pubertal females is a high-stakes physical examination skill. Currently, learning this skill relies heavily on case-by-case exposure, which is variable, limited and often results in suboptimal skill. Thus, there is a need to develop and evaluate learning platforms that simulate the presentation and diagnosis of this important clinical task. We developed an on-line learning and assessment platform that allowed the deliberate practice of 158 pre-pubertal female genital image interpretations . We examined the quantity of skill acquisition by deriving performance metrics and learning curves. Methods: This was a prospective cross-sectional study administered via an on-line learning and assessment platform. Colposcopic images were acquired from a child abuse clinic. Two child abuse experts interpreted images to determine case solutions and 40% of cases had medical or traumatic pathology. Further, to validate image interpretations, a unique set of five child abuse and pediatric gynaecology experts reviewed the cases. Study participants were recruited from the USA and Canada and were required to complete all 158 cases. For each image, learners designated cases as normal or abnormal and if abnormal indicated the abnormal area on the image. The primary outcome was the change in accuracy, sensitivity and specificity. Results: We enrolled 107 participants, 26 medical students, 31 pediatric residents, 24 pediatric emergency fellows, and 26 pediatric emergency attendings. For all participants, the change in accuracy was +9.6% for accuracy (<0.001), +1.4% for sensitivity (p=0.6) and +15.7% (p<0.001) for specificity. The final score for accuracy, sensitivity and specificity was 79.5%, 66.1%, and 87.8%, respectively. There was no difference between learner types with respect to summary performance metrics (accuracy, p=0.15; sensitivity, p=0.44; specificity, p=0.54). Learning curves show maximal learning gains (inflection point) up until 100 cases. Conclusion: Deliberate practice of pre-pubertal female image interpretation was effective for ensuring predictable skill improvement for normal cases but was less effective for abnormal cases. Future research could examine how to refine the education tool to better serve diagnostic skill of abnormal cases.

scholarly journals LO79: Climbing the learning curve teaching the pediatric emergency physician how to interpret point-of-care ultrasound images

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S35-S35
Author(s):  
C. Kwan ◽  
K. Weerdenburg ◽  
M. Pecarcic ◽  
M. Pusic ◽  
M. Tessaro ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Performance Metrics ◽  
Point Of Care ◽  
Image Interpretation ◽  
Deliberate Practice ◽  
Pediatric Emergency ◽  
Learning Curves ◽  
Point Of Care Ultrasound ◽  
On Line ◽  
On Line Learning

Introduction: Point-of-Care Ultrasound (POCUS) is rapidly being integrated into Pediatric Emergency Medicine (PEM), and image interpretation is an important component of this skill. Currently, PEM physicians often rely on case-by-case exposure and feedback by a POCUS expert physician to learn this skill; however, this may not be efficient, reliable or feasible. Thus, there is a pressing need to develop effective POCUS image interpretation learning and assessment tools. We developed an on-line learning platform that allowed for the deliberate practice of images in four POCUS applications [soft tissue, lung, cardiac and Focused Assessment Sonography for Trauma (FAST)], and determined the quantity of participant skill acquisition by deriving performance metrics and learning curves. Methods: This was a prospective cross-sectional study administered via an on-line learning and measurement platform. Images were acquired from a pediatric emergency department and each POCUS application contained 100 still/video images. Final diagnosis of each image was determined via the consensus of three PEM POCUS experts. PEM fellow and attending study participants were recruited from the USA and Canada and were required to complete the cases of at least one application. We aimed to enroll 200 participants who had to complete a minimum of 100 cases which, based on prior work, would provide sufficient raters for item analyses and comparisons between PEM attendings and fellows. To derive reference standard performance metrics and to validate image interpretations, a unique set of five PEM POCUS experts completed each application. Results: We enrolled 225 PEM physicians, 74 fellows and 151 attendings. For all applications, the Cohens d effect size was large at 0.87, and there was no difference between PEM attendings and fellows with respect to summary performance metrics (accuracy, p= 0.29; sensitivity, p=0.13; specificity, p=0.92). Final accuracy soft tissue, lung, cardiac, and FAST for all participants was 86.4%, 89.6%, 81.6%, 88.0%, respectively, and the corresponding accuracy of PEM POCUS experts for each application was 96.0%, 96.0%, 90.0%, and 93.0%. Learning curves show maximal learning gains (inflection point) up until 65 cases for soft tissue, 70 for FAST, 75 for lung, and 85 for cardiac. Conclusion: Deliberate practice of POCUS image interpretation was effective for ensuring broad domain coverage and predictable skill improvement. Specifically, there was a large learning effect after 100 case interpretations, and 65-85 case interpretations were needed to reach an accuracy threshold of approximately 85%.

scholarly journals Online Learning Cognition as Perceived by Undergraduate Students in China Eastern Province

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Zezhao LIU ◽  
Haifeng Tian
Keyword(s):  
Undergraduate Students ◽  
Survey Design ◽  
Eastern China ◽  
Perceived Usefulness ◽  
Future Research ◽  
Teaching Resources ◽  
Learning Practices ◽  
On Line ◽  
Instructor Characteristics ◽  
On Line Learning

Company with global educational reform brought by digital governance and the challenge of COVID-19 pandemic in the year 2020, it is quite necessary to explore learners’ recognition behaviors for on-line learning in the context of locked environment. By investigating on-line learning practices in China eastern provincial regions, the study attempts to disclose the undergraduate students’ perceptions on the issues pertaining to on-line learning and the innate critical factors for individual intention through the selected region of relatively-developed eastern China. A survey design was used for the study, and a close- ended questionnaire with the six point Likert scale was developed regarding the issues over on-line learning practices. The findings indicate that instructor characteristics and teaching resources are the predictors of the perceived usefulness of on-line learning, and perceived usefulness coupled with the joyfulness are the predictors of on-line learning recognition. While statistically significant, perceived adaptability was shown to own the weakest effect for on-line learning recognition among the predictors. All these results are consistent with previous studies in other China regions, proving the universal trait of learners’ perception and individual behavior towards on-line learning. Implications and future research are discussed eventually.

scholarly journals LO088: Development of a simulation-based curriculum for ultrasound-guided internal jugular central venous catheterization

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S60-S60
Author(s):  
M. Woodcroft ◽  
M. Holden ◽  
T. Chaplin ◽  
L. Rang ◽  
M. Jaeger ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Deliberate Practice ◽  
Venous Catheter ◽  
High Volume ◽  
Careful Consideration ◽  
Learning Curves ◽  
Central Venous ◽  
Real Patient ◽  
Hand Motion ◽  
Simulation Based

Introduction / Innovation Concept: Insertion of an internal jugular (IJ) central venous catheter (CVC) under ultrasound guidance (USG) is a complex skill that requires considerable practice in order to achieve technical proficiency. Simulation allows novices to engage in structured and high volume repetitive practice of USG IJ CVC insertion and to work through a predictable pattern of errors prior to real patient encounters. Based on earlier work on learning curves for CVC insertion, this curriculum uses a model of simulation-based high volume deliberate practice of the fundamental skills of USG CVC insertion, and was designed with careful consideration of the conditions associated with optimal learning and improvement of performance. Methods: Eight residents (post graduate year 2) from the Departments of Emergency Medicine and Anesthesiology engaged in deliberate practice of USG CVC insertion during three two-hour sessions, at 2-week intervals. Progress of the residents was monitored with direct observation and regular hand motion analysis (HMA), which was compared to performance metrics set by a local expert. Curriculum, Tool, or Material: Students reviewed online introductory ultrasound video and articles outlining internal jugular (IJ) and femoral CVC insertion prior to the first session. Session 1 focused on ultrasound skills including knobology, transducer movement, and needle tracking. This was followed by 60 minutes of deliberate practice of the skills of USG CVC insertion on both femoral and IJ models. During sessions 2/3, students practiced complete gowning and draping using sterile technique. This was followed again by deliberate practice of the skills of USG CVC insertion on both femoral and IJ models. Students received coaching and feedback throughout all sessions, with HMA assessment of USG IJ CVC insertion at the beginning and end of each session. After three training sessions, consisting of 85 total attempts, 5/8 residents surpassed the expert benchmark for probe hand motion, 6/8 for needle hand motion, and 1/8 for total procedure time, with the remaining residents approaching the expert benchmark for each metric. Conclusion: We have successfully developed a simulation-based curriculum for USG IJ CVC placement. Residents demonstrated continuous improvement in each session, approaching or exceeding the expert benchmarks by the end of the third session.

Patterns of Implicit Learning Below the Level of Conscious Knowledge

2010 ◽  
Vol 24 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Juliana Yordanova ◽  
Rolf Verleger ◽  
Ullrich Wagner ◽  
Vasil Kolev
Keyword(s):  
Implicit Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Knowledge Generation ◽  
Sleep Stages ◽  
Implicit Processing ◽  
Implicit Processes ◽  
Late Night ◽  
On Line ◽  
On Line Learning

The objective of the present study was to evaluate patterns of implicit processing in a task where the acquisition of explicit and implicit knowledge occurs simultaneously. The number reduction task (NRT) was used as having two levels of organization, overt and covert, where the covert level of processing is associated with implicit associative and implicit procedural learning. One aim was to compare these two types of implicit processes in the NRT when sleep was or was not introduced between initial formation of task representations and subsequent NRT processing. To assess the effects of different sleep stages, two sleep groups (early- and late-night groups) were used where initial training of the task was separated from subsequent retest by 3 h full of predominantly slow wave sleep (SWS) or rapid eye movement (REM) sleep. In two no-sleep groups, no interval was introduced between initial and subsequent NRT performance. A second aim was to evaluate the interaction between procedural and associative implicit learning in the NRT. Implicit associative learning was measured by the difference between the speed of responses that could or could not be predicted by the covert abstract regularity of the task. Implicit procedural on-line learning was measured by the practice-based increased speed of performance with time on task. Major results indicated that late-night sleep produced a substantial facilitation of implicit associations without modifying individual ability for explicit knowledge generation or for procedural on-line learning. This was evidenced by the higher rate of subjects who gained implicit knowledge of abstract task structure in the late-night group relative to the early-night and no-sleep groups. Independently of sleep, gain of implicit associative knowledge was accompanied by a relative slowing of responses to unpredictable items suggesting reciprocal interactions between associative and motor procedural processes within the implicit system. These observations provide evidence for the separability and interactions of different patterns of processing within implicit memory.

SCROLLA — On-Line Learning and Assessment

2001 ◽  
Vol 1 (2) ◽  
pp. 27-27
Author(s):  
Cliff Beevers
Keyword(s):  
On Line ◽  
On Line Learning

scholarly journals Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 664
Author(s):  
Nikos Kanakaris ◽  
Nikolaos Giarelis ◽  
Ilias Siachos ◽  
Nikos Karacapilidis
Keyword(s):  
Language Processing ◽  
Scientific Knowledge ◽  
Link Prediction ◽  
Performance Metrics ◽  
Future Research ◽  
Knowledge Graph ◽  
Prediction Problem ◽  
Textual Information ◽  
Research Collaborations ◽  
Processing Techniques

We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that combines structural and textual information of a scientific knowledge graph through a purposeful integration of graph algorithms and natural language processing techniques. Our work: (i) investigates whether the integration of unstructured textual data into a single knowledge graph affects the performance of a link prediction model, (ii) studies the effect of previously proposed graph kernels based approaches on the performance of an ML model, as far as the link prediction problem is concerned, and (iii) proposes a three-phase pipeline that enables the exploitation of structural and textual information, as well as of pre-trained word embeddings. We benchmark the proposed approach against classical link prediction algorithms using accuracy, recall, and precision as our performance metrics. Finally, we empirically test our approach through various feature combinations with respect to the link prediction problem. Our experimentations with the new COVID-19 Open Research Dataset demonstrate a significant improvement of the abovementioned performance metrics in the prediction of future research collaborations.

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