# bib

id: cord-290394-fc6xnbju
author: Jha, Amrit Kumar
title: The Neuropsychological Impact of E-learning on Children
date: 2020-07-13
extension: .txt
mime: text/plain
words: 1045
sentence: 38
flesch: 43
cache: cache/cord-290394-fc6xnbju.txt
txt: txt/cord-290394-fc6xnbju.txt
summary:
  Brain's plasticity sheds light upon how neural circuitry in young brains respond to digital learning, given the fact that the formation of higher-order J o u r n a l P r e -p r o o f functions take place during childhood years (Zelazo and Muller, 2002) . Cognitive overload, as a product of multi-method based learning and divided attention, impacts the quality of comprehension, prioritization, and deep-level processing of incoming information, which in turn, critically determines consolidation of memory into long-term memory (Carr, 2010) .


id: cord-346843-z82ikuqc
author: Jabbar, Abdul
title: Parasitology education before and after the COVID-19 pandemic
date: 2020-10-23
extension: .txt
mime: text/plain
words: 1466
sentence: 48
flesch: 31
cache: cache/cord-346843-z82ikuqc.txt
txt: txt/cord-346843-z82ikuqc.txt
summary:
  Editorial special issue -learning and teaching of veterinary parasitology Assessing social presence in asynchronous text-based computer conferencing Connectivism: a learning theory for the digital age Learning Theory and Online Technologies Promoting Self-Directed Learning through the Implementation of Cooperative Learning in a Higher Education Blended Learning Environment Theories and frameworks for online education: Seeking an integrated model Can new digital technologies support parasitology teaching and learning? Covid-19 and rapid adoption and improvisation of online teaching: curating resources for extensive versus intensive online learning experiences e-Learning, online learning, and distance learning environments: Are they the same? Online design education: meta-connective pedagogy Asynchronous and synchronous online teaching: perspectives of Canadian high school distance education teachers From bricks and mortar to remote teaching: a teacher education programmer's response to COVID-19 We are grateful to Professor Robin B. Gasser for his advice and suggestions during the rapid adoption and improvisation of online parasitology teaching as well as providing feedback on the manuscript.


id: cord-030613-i4rdhipz
author: Jankowski, Natasha A.
title: Guideposts for Assessment During COVID‐19
date: 2020-08-03
extension: .txt
mime: text/plain
words: 1648
sentence: 77
flesch: 54
cache: cache/cord-030613-i4rdhipz.txt
txt: txt/cord-030613-i4rdhipz.txt
summary:
  With questions of the quality of the educational experience in view (Eaton 2020a) , the role of student learning outcomes assessment is more crucial than ever to counteract future concerns over transfer, quality of degree completion, and alignment with quality standards. Faculty and staff need to widen their lens of what falls into the category of evidence of student learning.


id: cord-265850-v83dwt6k
author: Thomas, Michael S. C.
title: Education, the science of learning, and the COVID-19 crisis
date: 2020-05-25
extension: .txt
mime: text/plain
words: 1500
sentence: 75
flesch: 53
cache: cache/cord-265850-v83dwt6k.txt
txt: txt/cord-265850-v83dwt6k.txt
summary:
  The second part, taking the longer view, considers the potential negative impact of the COVID-19 crisis in increasing inequality in education; but also the potential positive impact of driving innovations in technology use for educating children. Parents also need to be aware of the information passed on to children, both factual and emotional, because children will learn from whatever information is around them.


id: cord-029031-jtdc9a7w
author: Jirapanthong, Waraporn
title: A Tool for Supporting the Evaluation of Active Learning Activities
date: 2020-06-22
extension: .txt
mime: text/plain
words: 2126
sentence: 129
flesch: 55
cache: cache/cord-029031-jtdc9a7w.txt
txt: txt/cord-029031-jtdc9a7w.txt
summary:
  The core elements of active learning are student activity and engagement in the learning process. Two scenarios of active learning classrooms are created in order to evaluate the prototype tool.


id: cord-013381-aagbb1ip
author: van Teijlingen, Alexander
title: Artificial Intelligence and Health in Nepal
date: 2020-09-30
extension: .txt
mime: text/plain
words: 2313
sentence: 95
flesch: 41
cache: cache/cord-013381-aagbb1ip.txt
txt: txt/cord-013381-aagbb1ip.txt
summary:
  In terms of patient care AI can be used to rapidly transfer knowledge between institutions on a global scale. AI algorithms have been successfully applied in various healthcare and medical domains as decision support tools for diagnosis to prognosis (predictive analysis) applications.


id: cord-265665-411rtt89
author: Teele, Sarah A.
title: Online Education In A Hurry: Delivering Pediatric Graduate Medical Education During COVID-19
date: 2020-11-04
extension: .txt
mime: text/plain
words: 2481
sentence: 102
flesch: 36
cache: cache/cord-265665-411rtt89.txt
txt: txt/cord-265665-411rtt89.txt
summary:
  The top three motivating factors were: I feel continuing my education through online learning is important, I feel it is my professional responsibility to do this online learning, and Online learning provides a way to stay professionally connected to my peers and faculty mentors. Respondents reported a high level of motivation for participating in online learning.


id: cord-310553-qsk42zf7
author: Alkhowailed, Mohammad S.
title: Digitalization plan in medical education during COVID-19 lockdown
date: 2020-09-17
extension: .txt
mime: text/plain
words: 2655
sentence: 112
flesch: 39
cache: cache/cord-310553-qsk42zf7.txt
txt: txt/cord-310553-qsk42zf7.txt
summary:
  Online learning is considered a feasible and compliant method for training and scientific meetings and the sustainability of learning [3] . The expansion in global virtual learning is dependent on the availability of technology-enhanced active learning tools, and the options of online learning and their role in the field of medical education cannot be disregarded


id: cord-338706-566e3o5j
author: Popa, Simona
title: Reflections on COVID-19 and the future of education and learning
date: 2020-09-29
extension: .txt
mime: text/plain
words: 2651
sentence: 106
flesch: 51
cache: cache/cord-338706-566e3o5j.txt
txt: txt/cord-338706-566e3o5j.txt
summary:
  For education communities, this is a chance to take a close look at aspects of education systems that we have taken for granted for far too long. The economic and social effects of lockdowns, loss of production and business confidence, and global recession will cast a long shadow over education systems (Keith Lewin, in this special issue).


id: cord-258996-e2xagi27
author: Rhim, Hye Chang
title: Teaching online: foundational concepts of online learning and practical guidelines
date: 2020-09-01
extension: .txt
mime: text/plain
words: 2725
sentence: 120
flesch: 34
cache: cache/cord-258996-e2xagi27.txt
txt: txt/cord-258996-e2xagi27.txt
summary:
  Hye Chang Rhim: https://orcid.org/0000-0002-7986-6493 Heeyoung Han: https://orcid.org/0000-0002-7286-2473 Innovation in response to the COVID-19 pandemic crisis Medical student education in the time of COVID-19 Flipped classroom improves student learning in health professions education: a meta-analysis The inevitable reimagining of medical education Mediation and remediation in online learning Liquid modernity Learning at the back door: reflections on non-traditional learning in the lifespan e-Learning, online learning, and distance learning environments: are they the same? key: cord-258996-e2xagi27 authors: Rhim, Hye Chang; Han, Heeyoung title: Teaching online: foundational concepts of online learning and practical guidelines date: 2020-09-01 journal: Korean J Med Educ DOI: 10.3946/kjme.2020.171 sha: doc_id: 258996 cord_uid: e2xagi27 Medical schools have been slowly adopting online learning into pedagogical methods for more than a decade.


id: cord-260167-3kjjjbp0
author: Kusunose, Kenya
title: Steps to use artificial intelligence in echocardiography
date: 2020-10-12
extension: .txt
mime: text/plain
words: 3065
sentence: 155
flesch: 38
cache: cache/cord-260167-3kjjjbp0.txt
txt: txt/cord-260167-3kjjjbp0.txt
summary:
  Echocardiographic images require many types of recordings because of the complexity of the cardiac structure. Beginnings of artificial intelligence in medicine (AIM): computational artifice assisting scientific inquiry and clinical art-with reflections on present aim challenges Deep learning in neural networks: an overview Deep Learning Nat Utilization of artificial intelligence in echocardiography Artificial intelligence in cardiology Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions Deep learning analysis of left ventricular myocardium in CT angiographic intermediate-degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis Deep learning for diagnosis of chronic myocardial infarction on nonenhanced cardiac cine MRI Coronavirus disease 2019 (COVID-19) information for cardiologists-systematic literature review and additional analysis ASE Statement on protection of patients and echocardiography service providers during the 2019 novel coronavirus outbreak: endorsed by the American college of cardiology Review of the efforts of the Japanese Society of Echocardiography for coronavirus disease 2019 (COVID-19) during the initial outbreak in Japan Identifying the extent of oral fluid droplets on echocardiographic machine consoles in COVID-19 era Unsupervised learning of generative and discriminative weights encoding elementary image components in a predictive coding model of cortical function The evolution of computing: AlphaGo On modelling label uncertainty in deep neural networks: automatic estimation of intra-observer variability in 2d echocardiography quality assessment Fast and accurate view classification of echocardiograms using deep learning Fully automated echocardiogram interpretation in clinical practice Deep learning for segmentation using an open large-scale dataset in 2D echocardiography Automated echocardiographic quantification of left ventricular ejection fraction without volume measurements using a machine learning algorithm mimicking a human expert Deep Learning for Assessment of Left Ventricular Ejection Fraction from Echocardiographic Images Deep learning interpretation of echocardiograms A deep learning approach for assessment of regional wall motion abnormality from echocardiographic images Automated technique for coronary artery disease characterization and classification using DD-DTDWT in ultrasound images Quantification of cardiac bull's-eye map based on principal strain analysis for myocardial wall motion assessment in stress echocardiography Cardiac ultrasound uses artificial intelligence to produce images Clinically feasible and accurate view classification of echocardiographic images using deep learning Automatic quality assessment of echocardiograms using convolutional neural networks: feasibility on the apical four-chamber view guideline on diagnosis and treatment of acute coronary syndrome ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) developed with the special contribution of the heart failure association (HFA) of the ESC Xception:


id: cord-292123-ko1pnree
author: Pikhart, Marcel
date: 2020-12-31
extension: .txt
mime: text/plain
words: 3375
sentence: 134
flesch: 44
cache: cache/cord-292123-ko1pnree.txt
txt: txt/cord-292123-ko1pnree.txt
title:
  The use of technology in the learning environment for business communication: applied linguistics of business communication from the positive psychology perspective

summary:
  The use of technology in the educational process should not be intuitive based on our experience but it should rather be a very intentional process that needs our undivided attention if we want to create eLearning courses that will be successful and useful Naturally, the reason could be not a well-prepared online course, however, the tutor claims that the course follows a well-established methodology and basically copies other online courses used at the university.


id: cord-329108-meqjy3p8
author: Al-Balas, Mahmoud
date: 2020-10-02
extension: .txt
mime: text/plain
words: 3425
sentence: 144
flesch: 34
cache: cache/cord-329108-meqjy3p8.txt
txt: txt/cord-329108-meqjy3p8.txt
title:
  Distance learning in clinical medical education amid COVID-19 pandemic in Jordan: current situation, challenges, and perspectives

summary:
  The overall satisfaction rate in medical distance learning was 26.8%, and it was significantly higher in students with previous experience in distance learning in their medical schools as well as when instructors were actively participating in learning sessions, using multimedia and devoting adequate time for their sessions. Overall, only 144 students (26.77%) were satisfied with their experience in medical distance learning (Fig. 1) .


id: cord-024503-f4ibgn9i
author: Jawed, Shayan
title: Self-supervised Learning for Semi-supervised Time Series Classification
date: 2020-04-17
extension: .txt
mime: text/plain
words: 4339
sentence: 199
flesch: 53
cache: cache/cord-024503-f4ibgn9i.txt
txt: txt/cord-024503-f4ibgn9i.txt
summary:
  Multitask learning DTW-D: time series semi-supervised learning from a single example The UCR time series classification archive Unsupervised visual representation learning by context prediction Multi-task self-supervised visual learning Deep learning for time series classification: a review Unsupervised representation learning by predicting image rotations Learning time-series shapelets Lars: Invariant time-series factorization Multi-task learning using uncertainty to weigh losses for scene geometry and semantics Temporal ensembling for semi-supervised learning SUCCESS: a new approach for semi-supervised classification of time-series Shuffle and learn: unsupervised learning using temporal order verification Positive unlabeled learning for time series classification Unsupervised learning of visual representations by solving jigsaw puzzles An overview of multi-task learning in deep neural networks Time series feature learning with labeled and unlabeled data Bag-of-words representation for biomedical time series classification Time series classification from scratch with deep neural networks: a strong baseline Learning and using the arrow of time Semi-supervised time series classification Time series analysis with graph-based semi-supervised learning Colorful image colorization Semi-supervised learning using gaussian fields and harmonic functions Semi-supervised learning literature survey Acknowledgements. The idea behind semi-supervised learning is to exploit unlabeled data for training purpose in the presence of only few labeled instances.


id: cord-305226-9iedjcr6
author: Dua, Anisha B
date: 2020-10-16
extension: .txt
mime: text/plain
words: 4584
sentence: 169
flesch: 28
cache: cache/cord-305226-9iedjcr6.txt
txt: txt/cord-305226-9iedjcr6.txt
title:
  Challenges, collaboration, and innovation in rheumatology education during the COVID-19 pandemic: leveraging new ways to teach

summary:
  Social media has become a powerful instrument for international collaboration and knowledge and information sharing that supplements traditional learning, and rheumatology medical education has been no exception. This new and exciting format for medical education may have a lasting impact on the field beyond the limits of this pandemic.


id: cord-011971-h78639ld
author: Wood, D. Brian
date: 2020-07-03
extension: .txt
mime: text/plain
words: 4442
sentence: 203
flesch: 36
cache: cache/cord-011971-h78639ld.txt
txt: txt/cord-011971-h78639ld.txt
title:
  Conference Didactic Planning and Structure: An Evidence-based Guide to Best Practices from the Council of Emergency Medicine Residency Directors

summary:
  The impact of audience response systems on medical student learning: a randomised controlled trial Effect of an audience response system on resident learning and retention of lecture material Spaced learning using emails to integrate psychiatry into general medical curriculum: Keep psychiatry in mind Teaching the science of learning The reverse classroom: lectures on your own and homework with faculty Academic outcomes of flipped classroom learning: a meta-analysis Improved learning outcomes after flipping a therapeutics module: results of a controlled trial The flipped classroom: a course redesign to foster learning and engagement in a health professions school Flipping the classroom to improve student performance and satisfaction Does the flipped classroom improve learning in graduate medical education? pdf? Journal club in residency education: an evidence-based guide to best practices from the Council of Emergency Medicine Residency Directors Individualized interactive instruction: a guide to best practices from the Council of Emergency Medicine Residency Directors Wellness in resident education: an evidence-based guide to best practices from the Council of Emergency Medicine Residency Directors Clinical Teaching: An Evidencebased Guide to Best Practices from the Council of Emergency Medicine Residency Directors Oxford Centre for Evidence-based Medicine -Levels of Evidence Family medicine didactics revisited The academic half-day in Canadian neurology residency programs Megaconference: a radical approach to radiology resident education with full-day weekly conferences Implementation of an academic half day in a vascular surgery residency program improves trainee and faculty satisfaction with surgical indications conference Positive impact of transition from noon conference to academic half day in a pediatric residency program Expanding resident conferences while tailoring them to level of training: a longitudinal study Characteristics of emergency medicine residency curricula that affect board performance Increasing faculty attendance at emergency medicine resident conferences: Does CME credit make a difference?


id: cord-020176-yc20rbml
author: Mutambara, David
title: Understanding Rural Parents’ Behavioral Intention to Allow Their Children to Use Mobile Learning
date: 2020-03-06
extension: .txt
mime: text/plain
words: 4752
sentence: 244
flesch: 52
cache: cache/cord-020176-yc20rbml.txt
txt: txt/cord-020176-yc20rbml.txt
summary:
  This might mean that even though rural parents have limited knowledge about the benefits that m-learning bring into STEM learning, that little knowledge they possess positively affects their attitudes towards the use of m-learning for STEM learning. The results suggest that rural parents value what people important to them say about the use of mlearning for STEM learning.


id: cord-354763-odzrco6q
author: Drake, John M.
date: 2006-12-20
extension: .txt
mime: text/plain
words: 5746
sentence: 230
flesch: 41
cache: cache/cord-354763-odzrco6q.txt
txt: txt/cord-354763-odzrco6q.txt
title:
  Societal Learning in Epidemics: Intervention Effectiveness during the 2003 SARS Outbreak in Singapore

summary:
  Societal learning models were fit to the reciprocal of the mean of observed lags between onset of symptoms and removal c An alternative is to compare the observed outbreak size with the theoretical distribution of outbreak sizes for outbreaks initialized at I 0


id: cord-309201-c1awh48y
author: Elzainy, Ahmed
date: 2020-10-22
extension: .txt
mime: text/plain
words: 5210
sentence: 316
flesch: 57
cache: cache/cord-309201-c1awh48y.txt
txt: txt/cord-309201-c1awh48y.txt
title:
  Experience of e-learning and online assessment during the COVID-19 pandemic at the College of Medicine, Qassim University

summary:
  Training sessions for various procedures of virtual classrooms and online assessments were organised for teachers and students. Out of the basic year students and staff, 58.82% reflected their high satisfaction towards virtual classrooms, online assessment, and online workshops.


id: cord-275622-v5o4uayk
author: Bjursell, Cecilia
title: The COVID-19 pandemic as disjuncture: Lifelong learning in a context of fear
date: 2020-10-30
extension: .txt
mime: text/plain
words: 6896
sentence: 262
flesch: 46
cache: cache/cord-275622-v5o4uayk.txt
txt: txt/cord-275622-v5o4uayk.txt
summary:
  It is therefore impossible to create a fully institutionalised system of lifelong learning; irrespective of where learning takes place, such learning must be recognised as part of the person's total learning. According to lifelong learning 3 theory, disjuncture triggers learning, but what is it that we learn during a pandemic?


id: cord-035388-n9hza6vm
author: Xu, Jie
title: Federated Learning for Healthcare Informatics
date: 2020-11-12
extension: .txt
mime: text/plain
words: 6144
sentence: 269
flesch: 38
cache: cache/cord-035388-n9hza6vm.txt
txt: txt/cord-035388-n9hza6vm.txt
summary:
  The next generation of precision medicine: observational studies, electronic health records, biobanks and continuous monitoring National health information privacy: regulations under the health insurance portability and accountability act Robust aggregation for adaptive privacy preserving federated learning in healthcare KETOS: Clinical decision support and machine learning as a service-A training and deployment platform based on Docker One-shot federated learning Distributed learning of deep neural network over multiple agents Deep compression: compressing deep neural networks with pruning, trained quantization and huffman coding Robust federated training via collaborative machine teaching using trusted instances Federated learning for mobile keyboard prediction Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption Central server free federated learning over single-sided trust social networks The Rationale for Learning Communities and Learning Community Models Distilling the knowledge in a neural network Observational health data sciences and informatics (ohdsi): opportunities for observational researchers Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records Privacy preserving qoe modeling using collaborative learning Mining electronic health records: towards better research applications and clinical care Improving federated learning personalization via model agnostic meta learning A survey towards federated semi-supervised learning Mimic-iii, a freely accessible critical care database Advances and open problems in federated learning Efficient decentralized deep learning by dynamic model averaging Incentive design for efficient federated learning in mobile networks: A contract theory approach Credit risk assessment from combined bank records using federated learning Federated tensor factorization for computational phenotyping Federated optimization: distributed optimization beyond the datacenter Federated optimization: distributed machine learning for on-device intelligence Federated learning: strategies for improving communication efficiency Survey of personalization techniques for federated learning Peer-to-peer federated learning on graphs Deep learning Privacy-preserving patient similarity learning in a federated environment: development and analysis Federated optimization for heterogeneous networks Fair resource allocation in federated learning Distributed learning from multiple ehr databases: Contextual embedding models for medical events Two-stage federated phenotyping and patient representation learning Threats to federated learning: a survey Communication-efficient learning of deep networks from decentralized data Learning differentially private recurrent language models Predictive modeling of the hospital readmission risk from patients' claims data using machine learning: A case study on copd Deep learning for healthcare: review, opportunities and challenges Agnostic federated learning System and method for dynamic context-sensitive federated search of multiple information repositories Client selection for federated learning with heterogeneous resources in mobile edge Dissecting racial bias in an algorithm used to manage the health of populations Multiparty differential privacy via aggregation of locally trained classifiers Large-scale assessment of a smartwatch to identify atrial fibrillation Federated and differentially private learning for electronic health records The eicu collaborative research database, a freely available multi-center database for critical care research Modern framework for distributed healthcare data analytics based on hadoop A model and infrastructure for federated learning content repositories Accelerating dnn training in wireless federated edge learning system Braintorrent: a peer-to-peer environment for decentralized federated learning Learning in a large function space: privacypreserving mechanisms for svm learning A generic framework for privacy preserving deep learning Federated learning for ultra-reliable lowlatency v2v communications Robust and communication-efficient federated learning from non-iid data Preserving patient privacy while training a predictive model of in-hospital mortality Biscotti: a ledger for private and secure peer-topeer machine learning Privacy-preserving deep learning Federated learning in distributed medical databases: meta-analysis of large-scale subcortical brain data An investigation into on-device personalization of end-to-end automatic speech recognition models Using the adap learning algorithm to forecast the onset of diabetes mellitus Federated multi-task learning Multiparty privacy in social media unfriendly: multi-party privacy risks in social networks Federated learning: rewards & challenges of distributed private ml A hybrid approach to privacy-preserving federated learning Federated learning of electronic health records improves mortality prediction in patients hospitalized with covid-19 medRxiv Deep reinforcement learning with double q-learning Split learning for health: distributed deep learning without sharing raw patient data Ai in health: state of the art, challenges, and future directions -edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning Federated learning for healthcare informatics Federated patient hashing Federated machine learning: concept and applications A federated learning framework for healthcare iot devices Federated learning with non-iid data Mobile edge computing, blockchain and reputationbased crowdsourcing iot federated learning: a secure, decentralized and privacy-preserving system Multi-objective evolutionary federated learning Federated reinforcement learning Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Conflict of Interest The authors declare that they have no conflict of interest. In particular, we summarize the general solutions to the statistical challenges, system challenges, and privacy issues in federated learning, and point out the implications and potentials in healthcare.


id: cord-159103-dbgs2ado
author: Rieke, Nicola
title: The Future of Digital Health with Federated Learning
date: 2020-03-18
extension: .txt
mime: text/plain
words: 6704
sentence: 264
flesch: 41
cache: cache/cord-159103-dbgs2ado.txt
txt: txt/cord-159103-dbgs2ado.txt
summary:
  Medical data is particularly diverse -not only in terms of type, dimensionality and characteristics of medical data in general but also within a defined medical task, due to factors like acquisition protocol, brand of the medical device or local demographics. key: cord-159103-dbgs2ado authors: Rieke, Nicola; Hancox, Jonny; Li, Wenqi; Milletari, Fausto; Roth, Holger; Albarqouni, Shadi; Bakas, Spyridon; Galtier, Mathieu N.; Landman, Bennett; Maier-Hein, Klaus; Ourselin, Sebastien; Sheller, Micah; Summers, Ronald M.; Trask, Andrew; Xu, Daguang; Baust, Maximilian; Cardoso, M. Jorge title: The Future of Digital Health with Federated Learning date: 2020-03-18 journal: nan DOI: nan sha: doc_id: 159103 cord_uid: dbgs2ado Data-driven Machine Learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems.


id: cord-339440-qu913a8q
author: Fonseca, David
title: New methods and technologies for enhancing usability and accessibility of educational data
date: 2020-10-26
extension: .txt
mime: text/plain
words: 3188
sentence: 130
flesch: 26
cache: cache/cord-339440-qu913a8q.txt
txt: txt/cord-339440-qu913a8q.txt
summary:
  Educational data are also the basis for learning analytics [17] [18] [19] , with an increasing focus on the way educational data are presented [20] [21]


id: cord-303385-2jjg8qw6
author: Kiendrébéogo, Joël Arthur
title: Policy learning and Universal Health Coverage in low- and middle-income countries
date: 2020-07-21
extension: .txt
mime: text/plain
words: 6637
sentence: 263
flesch: 43
cache: cache/cord-303385-2jjg8qw6.txt
txt: txt/cord-303385-2jjg8qw6.txt
summary:
  key: cord-303385-2jjg8qw6 authors: Kiendrébéogo, Joël Arthur; De Allegri, Manuela; Meessen, Bruno title: Policy learning and Universal Health Coverage in low- and middle-income countries date: 2020-07-21 journal: Health Res Policy Syst DOI: 10.1186/s12961-020-00591-z sha: doc_id: 303385 cord_uid: 2jjg8qw6 Learning is increasingly seen as an essential component to spur progress towards universal health coverage (UHC) in low- and middle-income countries (LMICs). The political science literature provides us with the concept of 'policy learning', which is learning applied to policy-making processes.


id: cord-143033-88o1bazi
author: Peppler, Kylie
date: 2020-08-15
extension: .txt
mime: text/plain
words: 7163
sentence: 256
flesch: 36
cache: cache/cord-143033-88o1bazi.txt
txt: txt/cord-143033-88o1bazi.txt
title:
  Key principles for workforce upskilling via online learning: a learning analytics study of a professional course in additive manufacturing

summary:
  The study also emphasizes broader strategies for course designers and instructors to align course assignments, learning objectives, and assessment measures with learner needs and interests, and argues for a synchronized data infrastructure to facilitate effective just in time learning and continuous improvement of online courses. Additionally, online courses and brief topical certificates reduce costs regarding physical materials, spaces, and allow for economics of scale, one certificate can teach critical competencies to thousands of learners.


id: cord-286531-3syf6upw
author: Dong, Chuanmei
title: Young Children’s Online Learning during COVID-19 Pandemic: Chinese Parents’ Beliefs and Attitudes
date: 2020-09-08
extension: .txt
mime: text/plain
words: 7252
sentence: 272
flesch: 44
cache: cache/cord-286531-3syf6upw.txt
txt: txt/cord-286531-3syf6upw.txt
summary:
  As the first exploration of Chinese parents' beliefs and attitudes around online learning during the COVID-19 pandemic, this study has found that many young children had online learning experiences that were delivered by their kindergarten teachers or online learning apps at no or low cost. The parents generally had negative beliefs about the values and benefits of online learning and preferred traditional learning in early childhood settings.


id: cord-026732-2t4pu36i
author: Garip, Gulcan
title: Learners’ perceptions and experiences of studying psychology online
date: 2020-06-13
extension: .txt
mime: text/plain
words: 7588
sentence: 269
flesch: 39
cache: cache/cord-026732-2t4pu36i.txt
txt: txt/cord-026732-2t4pu36i.txt
summary:
  While the popularity of online learning can be attributed to the flexibility inherent to its medium, research has identified concerns related to student engagement (Prior et al. 2016) , retention rates (Mubarak et al. 2020; Current trends indicate that a greater proportion of students engage in online learning than in the past (Li et al. 2019 ).


id: cord-018038-gqdylj6n
author: Snyder, William M.
title: Our World as a Learning System: A Communities-of-Practice Approach
date: 2010
extension: .txt
mime: text/plain
words: 7657
sentence: 330
flesch: 43
cache: cache/cord-018038-gqdylj6n.txt
txt: txt/cord-018038-gqdylj6n.txt
summary:
  One way to assess the level of civic stewardship in any city or region is to map the prevalence, inclusiveness, and effectiveness of civic communities of practice (also known as coalitions, associations, partnerships, and alliances, among other terms) who take responsibility for clusters of issues related to particular civic domains, such as education, economic development, health, housing, public safety, infrastructure, culture, recreation, and the environment. Civic communities of practice also need help to build a technology infrastructure for communicating across geographies and time zones, and for building accessible knowledge repositories.


id: cord-273005-kab6f157
author: Longhurst, Georga J.
date: 2020-05-09
extension: .txt
mime: text/plain
words: 7775
sentence: 324
flesch: 37
cache: cache/cord-273005-kab6f157.txt
txt: txt/cord-273005-kab6f157.txt
title:
  Strength, Weakness, Opportunity, Threat (SWOT) Analysis of the Adaptations to Anatomical Education in the United Kingdom and Republic of Ireland in Response to the Covid‐19 Pandemic

summary:
  A novel coronavirus from patients with pneumonia in China Daily medical education for confined students during COVID-19 pandemic: A simple videoconference solution Advice from Medical Schools Council to UK Medical Schools on Actions Surrounding Covid-19 Nursing student's evaluation of a virtual classroom experience in support of their learning bioscience SARS and its effect on medical education in Hong Kong Using videoclips to improve theoretical anatomy teaching Effectiveness of using blended learning strategies for teaching and learning human anatomy Guidance: Staying at home and away from others (social distancing) Sense of connection, identity and academic success in distance education: Sociologically exploring online learning environments Student perceptions of the use of instructor-made videos in online and face-to-face classes Medical student education in the time of COVID-19 RTÉ. THOMAS Acland's Video Atlas of Human Anatomy ® COVID-19 and medical education Lancet Inf Dis The perception of anatomy teaching among UK medical students Second-year medical students' motivational beliefs, emotions, and achievement Improving online interactions.


id: cord-258269-ig8i9278
author: Philippe, Stéphanie
title: Multimodal teaching, learning and training in virtual reality: a review and case study
date: 2020-10-31
extension: .txt
mime: text/plain
words: 7774
sentence: 321
flesch: 36
cache: cache/cord-258269-ig8i9278.txt
txt: txt/cord-258269-ig8i9278.txt
summary:
  In this paper, we highlight the connection between VR learning and multimodality and the instruction concepts related to it. (report) Investigating learners′ attitudes toward virtual reality learning environments: based on a constructivist approach Improving teaching and learning of computer programming through the use of the Second Life virtual world Teaching training in a mixed-reality integrated learning environment Fostering learning through interprofessional virtual reality simulation development A constructivist approach to virtual reality for experiential learning.


id: cord-154587-qbmm5st9
author: Nguyen, Thanh Thi
date: 2020-07-30
extension: .txt
mime: text/plain
words: 8188
sentence: 365
flesch: 38
cache: cache/cord-154587-qbmm5st9.txt
txt: txt/cord-154587-qbmm5st9.txt
title:
  Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions

summary:
  -Imbalanced datasets due to insufficient COVID-19 medical image data. A summary of COVID-19 related data sources that are available for research purposes is also presented.


id: cord-032733-5v6kxgv4
author: Bozward, D.
title: Value creation programmes: lessons from an early-stage implementation
date: 2020-09-26
extension: .txt
mime: text/plain
words: 9048
sentence: 298
flesch: 36
cache: cache/cord-032733-5v6kxgv4.txt
txt: txt/cord-032733-5v6kxgv4.txt
summary:
  Education + Training Action learning in new creative ventures A model of work-based learning The evolution of entrepreneurial competencies: A longitudinal study of university spin-off venture emergence The impact of assessment on student learning: how can the research literature practically help to inform the development of departmental assessment strategies and learner-centred assessment practices? Human Resource Development International Powerful learning communities: A guide to developing student, faculty, and professional learning communities to improve student success and organizational effectiveness Handbook of curriculum evaluation Understanding entrepreneurial learning: A competency approach Mentoring in action: A practical guide Fostering critical reflection: A guide to transformative and emancipatory learning Models of pedagogical implementation of ICT in Israeli schools Impact of entrepreneurship education in Denmark-2012.


id: cord-281745-jkscwdjh
author: Adarkwah, Michael Agyemang
title: “I’m not against online teaching, but what about us?”: ICT in Ghana post Covid-19
date: 2020-09-16
extension: .txt
mime: text/plain
words: 8574
sentence: 315
flesch: 41
cache: cache/cord-281745-jkscwdjh.txt
txt: txt/cord-281745-jkscwdjh.txt
summary:
  The International Review of Research in Open and Distance Learning An assessment of the ICT situation in senior high schools in the upper west region of Ghana Challenges in development of eLearning systems in higher education of the developing countries Novel coronavirus, novel faculty development programs: Rapid transition to eLearning during the pandemic Innovating an integrated approach to collaborative eLearning practices in higher education: The case study of a corporate communication e-platform Using disruptive technologies to make digital connections: Stories of media use and digital literacy in secondary classrooms Barriers and solutions to online learning in medical education -An integrative review Cross-cultural differences in undergraduate students' perceptions of online barriers JiFUNzeni: A blended learning approach for sustainable teachers' professional development E-learning functional model: A technology-based teaching method for providing access to sustainable quality education Blending with Purpose: The Multimodal Model Leading and managing e-learning: What the e-learning leader needs to know Online learning in a south African higher education institution: Determining the right connections for the student. In the wake of the COVID-19 which has forced many countries and educational sectors to adopt online learning, there is a need to discuss the effectiveness of online learning and barriers to online learning in the developing contexts, and how to successfully integrate ICT in schools for online learning, especially rural schools where students’ educational careers are in jeopardy because they benefit less from online learning.


id: cord-303137-g2pe3ad8
author: Moss, Emanuel
title: High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response
date: 2020-10-09
extension: .txt
mime: text/plain
words: 5945
sentence: 185
flesch: 36
cache: cache/cord-303137-g2pe3ad8.txt
txt: txt/cord-303137-g2pe3ad8.txt
summary:
  Machine learning applications may construct risk such that individuals can act upon it to their own advantage without addressing the social conditions that make such risks unevenly distributed, thereby presenting a false sense of risk reduction. These risks are often framed as threatening privacy, and there are various technical methods for limiting such risks for individuals, including differential privacy, encrypted computation, and decentralized computation (particularly for contact tracing and other diagnostic applications).


id: cord-277650-llsgpyrm
author: Damiati, Safa A.
title: Digital Pharmaceutical Sciences
date: 2020-07-26
extension: .txt
mime: text/plain
words: 6138
sentence: 224
flesch: 26
cache: cache/cord-277650-llsgpyrm.txt
txt: txt/cord-277650-llsgpyrm.txt
summary:
  Moreover, machine learning models can be classified into two categories: parametric and nonparametric models (Table I) . Moreover, machine learning models may be used individually or in combination.


id: cord-301035-dz8642qx
author: Rasheed, Jawad
date: 2020-10-10
extension: .txt
mime: text/plain
words: 6139
sentence: 183
flesch: 30
cache: cache/cord-301035-dz8642qx.txt
txt: txt/cord-301035-dz8642qx.txt
title:
  A Survey on Artificial Intelligence Approaches in Supporting Frontline Workers and Decision Makers for COVID-19 Pandemic

summary:
  Table V lists the other identified COVID-19 AI-based applications that utilize respiratory or coughing data. A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19 A web-based Diagnostic Tool for COVID-19 Using Machine Learning on Chest Radiographs (CXR) Detection of Coronavirus (COVID-19) Associated Pneumonia based on Generative Adversarial Networks and a Fine-Tuned Deep Transfer Learning Model using Chest X-ray Dataset COVID-MobileXpert: On-Device COVID-19


id: cord-350256-tpu2oidi
author: Sajnani, Nisha
date: 2020-05-23
extension: .txt
mime: text/plain
words: 8821
sentence: 288
flesch: 35
cache: cache/cord-350256-tpu2oidi.txt
txt: txt/cord-350256-tpu2oidi.txt
title:
  Aesthetic presence: The role of the arts in the education of creative arts therapists in the classroom and online

summary:
  The role of instructor humor and students' educational orientations in student learning, extra effort, participation, and out-of-class communication Music therapy education and training: From theory to practice Competences for online teaching: A special report Arts as education Cambridge John Dewey, Robert Pirsig, and the art of living: Revisioning aesthetic education Variations on a blue guitar: The Lincoln Center Institute lectures on aesthetic education Social presence as a predictor of satisfaction within a computer-mediated conferencing environment Critical thinking, self-direction and online learning: A practical inquiry perspective in higher education. Online students did have a statistically significant higher perception of learning score than their residential peers, which the researchers attribute to the online students having more experience in the field and thus more investment in the learning process.


id: cord-356353-e6jb0sex
author: Fourcade, Marion
title: Loops, ladders and links: the recursivity of social and machine learning
date: 2020-08-26
extension: .txt
mime: text/plain
words: 14366
sentence: 493
flesch: 35
cache: cache/cord-356353-e6jb0sex.txt
txt: txt/cord-356353-e6jb0sex.txt
summary:
  Information Corrupting the cyber-commons: Social media as a tool of autocratic stability Policy paradigms, social learning, and the state: The case of economic policymaking in Britain Perceiving persons and groups The architecture of community: Some new proposals on the social consequences of architectural and planning decisions Exposed: Desire and disobedience in the digital age Simmel, the police form and the limits of democratic policing Posthuman learning: Theories of social learning and socialization have explained how people come to assume behaviors and attitudes in ways not well captured by a focus on internal motivation or conscious deliberation (Miller and Dollard 1941; Bandura 1962; Mauss 1979; Elias 2000) .


id: cord-021206-4zyqqgs0
title: Scientific and Educational Exhibits
date: 2007
extension: .txt
mime: text/plain
words: 138880
sentence: 6780
flesch: 44
cache: cache/cord-021206-4zyqqgs0.txt
txt: txt/cord-021206-4zyqqgs0.txt
summary:
  Conclusion: In the appropriate clinical setting, CT fi ndings in immunologic lung diseases other than asthma and collagen-vascular disorders are suggestive of the underlying disorders and allow in making the correct diagnosis with a reasonable level of confi dence. CT fi ndings combined with certain histopathologic features can suggest specifi c diagnosis.


id: cord-021087-n4epxwn9
title: ECR – Final Programme: Scientific and Educational Exhibits
date: 2004
extension: .txt
mime: text/plain
words: 154405
sentence: 7465
flesch: 43
cache: cache/cord-021087-n4epxwn9.txt
txt: txt/cord-021087-n4epxwn9.txt
summary:
  With more thorough information derived from HRCT and biopsy on the types of tumors patients have, physicians can offer patients more accurate prognosis. Imaging Findings: In normal patients, the fractional anisotropy (FA) maps clearly visualized white matter tracts as areas of high FA compared to gray matter.


