Research on the Use of Social Media Networks by Teacher Candidates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social media networks are the most important product of the development of computer and communicationtechnologies that affect social life. Social media networks have become a driving force in social and culturaldevelopment, while providing social contact for people. This force has improved its sphere of influence oversocieties in many fields such as health, defense, banking, commerce, marketing and entertainment, especially ineducation, which sometimes have no relationship with each other. This study is a qualitative educational researchbased on content analysis of teacher candidates' research on using social media networks. The study's population iscomposed of 552 teacher candidates who are reached with the help of social media networks. A data collection tooldeveloped by the researcher in order to collect data was used in the research. A personal information sectioncontaining information on the participants and their use of social media networks was used in the first part of the datacollection tool while a form consisting of 7 semi-structured questions was used in the second part. Data wereanalyzed by using descriptive analysis and content analysis for the data obtained from data collection tool. Given thefindings of the study, it is concluded that more than half of teacher candidates participating in the research use socialmedia networks more than once every day; more than half of these candidates use social media networks for 2 to 4hours a day; they mostly use mobile instant messaging tools; the most popular social media networks teachercandidates are Instagram and Facebook; they mostly use social media networks in order to communicate with theirfriends; they attribute different meanings to social media networks and they regard social media tools as apedagogical value.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| 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 it