The Digital Lives of U.S. Teachers: A Research Synthesis and Trends to Watch
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
The United States Department of Education's 2010 National Educational Technology Plan called for educators to transform learning and teaching with digital resources and tools. However, classroom teachers are especially challenged by information seeking, use, and management as well as by increased pressure to provide accountability data and serve diverse learners. In response to these challenges, the digital library community, spurred to improve science, technology, education, and mathematics (STEM) education, is developing solutions that include metadata and paradata schema; highly curated, centralized collections; and integrated planning, management, and assessment tools. Still, local and external factors can hinder change and must be considered in design and implementation. In this paper, we integrate an extensive collection of research relating to educators' digital "lives," or processes; provide an overview of very recent developments in digital library technology that pose possible solutions; and illustrate essential facilitating conditions, including the vital role of the teacher librarian.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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