Leadership in the transition to online instruction: implications for teachers’ need satisfaction and motivation
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 transition to remote teaching during the COVID-19 pandemic introduced many threats to teachers’ psychological needs and intrinsic motivation. Given the possibility of similar disruptions in the future, we examined the potential influence of three resources provided by school leaders to smoothen teachers’ transition to online instruction: pedagogical support, availability of instructional technologies, and professional freedom. Survey data from 103 PreK-12 teachers in the United States and Canada were analyzed using Bayesian mediation models to explore how these administrative resources influenced teachers’ need satisfaction and intrinsic motivation. Results indicated that teachers who received more pedagogical support were more intrinsically motivated, and this relationship was partially mediated by their perceived competence and relatedness with students. Those with greater access to instructional technologies reported higher perceived competence and relatedness with students but were no more intrinsically motivated than their peers. Teachers who were granted professional freedom reported greater intrinsic motivation, and the relationship was partially mediated by all three psychological needs. Results highlight the importance of maintaining teacher-student relationships and suggest that, during unplanned transitions to online instruction, teachers are most self-determined when provided high quality instructional support and allowed freedom in how they navigate new challenges.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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