Bridging the Gap: Social Networks and Professional Development in the Eyes of Prospective Science Teachers
Bibliographic record
Abstract
Virtual social network platforms have rapidly become settings for cultivating various types of bonding, bridging, and building social capital. This promotes professional and personal relationships and has implications for our psychological wellness. Our qualitative study, which has taken place in the United Arab Emirates (UAE) and Oman, explored the perspectives of science teachers in training regarding the utilization of social networks for professional development (PD). We conducted 26 semi-structured interviews across both countries. Our results unveiled nuanced insights into the influence of social networks on the professional development of prospective science teachers, the challenges they face while using these means for networking, and how cultural norms and institutional factors impact learning, collaboration, and adoption of such virtual social systems. The findings suggest that social networks can serve as valuable tools for the professional development of prospective science teachers. Notably, there was a subtle divergence between the two groups. The UAE participants have emphasized global perspectives and valued insights into worldwide educational trends, whereas the Omani participants have appreciated the global perspective and prioritized local connections. Additionally, remarkable differences in technology access and infrastructure challenges between UAE and Oman teachers in training highlight the need for more equitable professional development opportunities. Emirati and Omani participants differ in their access to international educational trends and technology because of economic disparities. This could be translated into more resources for education and technological infrastructure, as the geographical location of the UAE as a global hub makes it easier to access global networks and trends. The implications of these findings point to the critical need for the effective use of social networks in the professional development of science teachers. Doi: 10.28991/ESJ-2024-08-01-014 Full Text: PDF
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".