Development of the Online and Blended Teaching Readiness Assessment (OBTRA)
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 rapid shift to online teaching and learning in postsecondary education during COVID-19 forced institutions to provide additional support and resources to instructors, especially those who were teaching online for the first time. The Online and Blended Teaching Readiness Assessment (OBTRA) was designed to assess the perceptions and competencies of instructors undertaking the move to online teaching to identify strengths and limitations. The present study identified the underlying factor structure and evidence of construct validity of the OBTRA for a sample of 223 postsecondary instructors (data collected from November 2019 to January 2020). An exploratory factor analysis revealed 5 factors that were interpreted as Technology, Engagement and Communication, Pedagogy, Perceptions of Teaching Online, and Organization. OBTRA scores were also found to be positively correlated with scores obtained from measures of instructional practices and teacher efficacy. The next steps in the development of the OBTRA are to examine how it can be used to enable academic units to provide the most appropriate support and resources aligned with instructor needs and to guide instructors to the initial steps required for successful transition to online teaching.
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