Development Path Exploration of Online Teaching for Primary and Secondary Schools in Underprivileged Areas Post-Pandemic—A Survey and Analysis of 471 Teachers in Rongcheng District, Jieyang City
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
During the pandemic, online teaching has become the most important instructional method for "classes suspended but learning continues". However, for educationally disadvantaged areas like Jieyang City, conducting online teaching is faced with difficulties such as outdated hardware and software equipment, lack of teaching resources, and insufficient practical experience for teachers and students. In light of this, based on literature review, policy analysis, teacher exchange, and expert guidance, our research team has preliminarily identified sixteen typical problems in online teaching. We have conducted data research, analysis, and attribution, and discussed these issues from three dimensions: the construction and support of the online teaching environment, the participation and interaction of key stakeholders, and the design and implementation of online teaching processes. Finally, we explore the future development direction of online teaching post-pandemic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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