Browse
Submit Data
Databases
API
Help

Dataset Information

9 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Online conferences for better learning.

ABSTRACT: Conferences provide an invaluable set of opportunities for professional development. Online, virtual, and distributed conferences do not necessarily mean less opportunity for growth and innovation in science but varied and novel options for communicating the scientific process. Open science and many existing tools are in place in the practice of contemporary ecology and evolution to provide latitude for a much broader scope of sharing and thus learning from conferences. A brief overview of the science supporting online conferences and a highlight of some of the open science concepts in ecology and evolution are provided here to enable better learning through better planning for online conferences.

SUBMITTER: Lortie CJ

PROVIDER: S-EPMC7679531 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Online conferences for better learning.

Lortie Christopher J CJ

Ecology and evolution 20201022 22

Conferences provide an invaluable set of opportunities for professional development. Online, virtual, and distributed conferences do not necessarily mean less opportunity for growth and innovation in science but varied and novel options for communicating the scientific process. Open science and many existing tools are in place in the practice of contemporary ecology and evolution to provide latitude for a much broader scope of sharing and thus learning from conferences. A brief overview of the s ...[more]

PMID: 33250984

Similar Datasets

Moving conferences online: lessons learned from an international virtual meeting.

Project description:We consider the opportunities and challenges associated with organizing a conference online, using a case study of a medium-sized (approx. 400 participants) international conference held virtually in August 2020. In addition, we present quantifiable evidence of the participants' experience using the results from an online post-conference questionnaire. Although the virtual meeting was not able to replicate the in-person experience in some aspects (e.g. less engagement between participants) the overwhelming majority of respondents found the meeting an enjoyable experience and would join similar events again. Notably, there was a strong desire for future in-person meetings to have at least some online component. Online attendance by lower-income researchers was higher compared with a past, similar-themed in-person meeting held in a high-income nation, but comparable to one held in an upper-middle-income nation. This indicates that online conferences are not a panacea for diversity and inclusivity, and that holding in-person meetings in developing economies can be at least as effective. Given that it is now relatively easy to stream contents of meetings online using low-cost methods, there are clear benefits in making all presented content accessible online, as well as organizing online networking events for those unable to attend in person.

| S-EPMC8527193 | biostudies-literature

Self-regulated spacing in a massive open online course is related to better learning.

Project description:In this study, we examined students' natural studying behaviors in massive, open, online course (MOOC) on introductory psychology. We found that, overall, distributing study across multiple sessions-increasing spacing-was related to increased performance on end-of-unit quizzes, even when comparing the same student across different time-points in the course. Moreover, we found important variation on who is more likely to engage in spaced study and benefit from it. Students with higher ability and students who were more likely to complete course activities were more likely to space their study. Spacing benefits, however, were largest for the lower-ability students and for those students who were less likely to complete activities. These results suggest that spaced study might work as a buffer, improving performance for low ability students and those who do not engage in active practices. This study highlights the positive impact of spacing in real-world learning situations, but more importantly, the role of self-regulated learning decisions in shaping the impact of spaced practice.

| S-EPMC7076029 | biostudies-literature

Redesign your in-person course for online: Creating connections and promoting engagement for better learning.

Project description:This spring, instructors moved their courses online in an emergency fashion as campuses were closed due to the pandemic. As colleges prepare for the next academic year, there is a need to provide flexible instruction that is more intentional for quality online learning. We taught two undergraduate courses online for the first time this spring and surveyed our students' reactions to the course experiences. From our experiences and student feedback, we identified design elements and activities that were beneficial in promoting student engagement, sense of connectivity, and learning. We describe four qualities for a successful transition to online learning: (a) big questions and core concepts; (b) peer groups including reflective writing; (c) outreach to broader scientific community; and (d) instructor's social presence in the class. Our experience gives us confidence that courses can be redesigned for online without compromising rigor or essential learning goals.

| S-EPMC7679538 | biostudies-literature

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective.

Project description:As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

| S-EPMC8377301 | biostudies-literature

Students online: learning medical genetics.

Project description:It is possible to focus medical genetics education by using a model that integrates the skills of end-user searching of the medical literature into the traditional course content. Since 1988, 313 first-year medical students were studied as they accessed MEDLINE to retrieve information about biochemical genetic disorders. Their search behavior was studied by analyzing data from the National Library of Medicine's traffic files. The skills that they initially learned were reinforced as they searched clinical genetics problem cases in the second-year pathology course, and these skills were consolidated in the third year when the students addressed specific patient-care questions in pediatrics. The students' perception of the value of this model was studied by analyzing questionnaires completed during the exercise. It was demonstrated that when students were taught the skills of accessing MEDLINE by computer, they could formulate a question, retrieve current information, critically review relevant articles, communicate effectively, and use these skills to contribute to patient care.

| S-EPMC1682177 | biostudies-other

A pilot study of team-based learning in one-hour pediatrics residency conferences.

Project description:BACKGROUND:Active learning has been shown to improve knowledge retention, facilitate feedback, and motivate learners. Despite this evidence, lecture, a passive mode of instruction, is the most widely utilized instructional method for residency educational conferences. Team-based learning fosters active learning but is infrequently used during residency training. METHODS:Three team-based learning sessions (one introductory and two content-based) were held during noon conferences in a pediatrics residency program. A pre-post static-group design was used to evaluate learner satisfaction and knowledge gains. Additional data was collected about facilitator preparation, session attendance, and readiness assurance test scores. Descriptive statistics and qualitative content analyses were conducted. RESULTS:Forty-seven residents and students participated (81%, 47 of 58). Prior to the introductory session, the majority of participants (55%) were not familiar with team-based learning. After the three sessions, 65% of residents and students reported high levels of satisfaction with team-based learning. When compared to traditional, lecture-based noon conferences, 76% of participants reported more engagement and 48% perceived more learning in team-based learning sessions. Challenges included low completion rates of the assigned reading prior to the session and abridged discussions due to time limitations during sessions. Each session required 10 hours of preparation for curriculum development. CONCLUSIONS:Team-based learning resulted in greater satisfaction and engagement among learners when compared to lecture-based formats. However, it did not prove to be a feasible instructional method during one-hour residency conferences. Adaptations that promote learner preparation for sessions and overcome time limitations during sessions may improve the feasibility and impact of team-based learning during one-hour conferences. TRIAL REGISTRATION:Not applicable.

| S-EPMC6637552 | biostudies-literature

Self-supervised Chinese ontology learning from online encyclopedias.

Project description:Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO.

| S-EPMC3970055 | biostudies-other

Differentially Private Distributed Online Learning.

Project description:In the big data era, the generation of data presents some new characteristics, including wide distribution, high velocity, high dimensionality, and privacy concern. To address these challenges for big data analytics, we develop a privacy-preserving distributed online learning framework on the data collected from distributed data sources. Specifically, each node (i.e., data source) has the capacity of learning a model from its local dataset, and exchanges intermediate parameters with a random part of their own neighboring (logically connected) nodes. Hence, the topology of the communications in our distributed computing framework is unfixed in practice. As online learning always performs on the sensitive data, we introduce the notion of differential privacy (DP) into our distributed online learning algorithm (DOLA) to protect the data privacy during the learning, which prevents an adversary from inferring any significant sensitive information. Our model is of general value for big data analytics in the distributed setting, because it can provide rigorous and scalable privacy proof and have much less computational complexity when compared to classic schemes, e.g., secure multiparty computation (SMC). To tackle high-dimensional incoming data entries, we study a sparse version of the DOLA with novel DP techniques to save the computing resources and improve the utility. Furthermore, we present two modified private DOLAs to meet the need of practical applications. One is to convert the DOLA to distributed stochastic optimization in an offline setting, the other is to use the mini-batches approach to reduce the amount of the perturbation noise and improve the utility. We conduct experiments on real datasets in a configured distributed platform. Numerical experiment results validate the feasibility of our private DOLAs.

| S-EPMC6764830 | biostudies-literature

WHO simulations for youth engagement in global governance in a post-COVID world: Opportunities and challenges of moving conferences online.

Project description: Not available

| S-EPMC8219344 | biostudies-literature

Online cross-validation-based ensemble learning.

Project description:Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd.

| S-EPMC5671383 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data