E-learning on the road: online learning and social media for continuing professional competency.
Bibliographic record
Abstract
<p>Background</p><p>The impact of social media and online learning in health professions education has previously shown generally positive results in medical, nursing and pharmacy students. To date there has not been any extensive research into social media and online learning use by prehospital health care professionals such as paramedics.</p><p>Aim &amp; Methods</p><p>We sought to identify the extent to which Irish pre-hospital practitioners make use of online learning and social media for continuous professional competency (CPC), and the means by which they do so. A cross-sectional online survey of practitioners was conducted to obtain both quantitative and qualitative data. The release of the survey was in a controlled manner to PHECC registrants via various channels. Participation was voluntary and anonymous.</p><p>Results</p><p>A total of 248 respondents completed the survey in full by closing date of 31 March 2015, representing 5.4% of all registrants (n=4,555). 77% of respondents were male, and the majority were registered as Emergency Medical Technicians (49%), followed by Advanced Paramedics (26%). Over 78% of respondents used a mobile device in the course of their clinical duties; the majority used an iOS device. Social media and online learning were considered learning tools by over 75% of respondents, and over 74% agreed they should be further incorporated into prehospital education. The most popular platforms for CPC activities were YouTube and Facebook. The majority of respondents (88%) viewed self-directed activities to constitute continuous professional development activity, but 64% felt that an activity that resulted in the awarding of a certificate was better value. Over 90% of respondents had previous experience with online learning, but only 42% indicated they had previously purchased or paid for online learning.</p><p>Conclusion</p><p>Prehospital practitioners in Ireland in the population studied consider online learning and social media acceptable for CPC purposes. The main social media outlets used by PHECC registrants are YouTube and Facebook. Practitioners consider online learning that awards a certificate to be better value than self-directed activities. The majority have previous experience of online learning. The results of this study can be used to ensure educational interventions are targeted at practitioners through the correct channels.</p><p> </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".