Instructional Design Collaboration: A Professional Learning and Growth Experience
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
High-quality online courses can result from collaborative instructional design and development approaches that draw upon the diverse and relevant expertise of faculty design teams. In this reflective analysis of design and pedagogical practice, the authors explore a collaborative instructional design partnership among education faculty, including the course instructors, which developed while co-designing an online graduate-level course at a Canadian University. A reflective analysis of the collaborative design process is presented using an adapted, four-fold curriculum design framework. Course instructors discuss their approaches to backward instructional design and describe the digital tools used to support collaboration. Benefits from collaborative course design, including ongoing professional dialogue and peer support, academic development of faculty, and improved course design and delivery, are described. Challenges included increased time investment for instructors and a perception of increased workload during design and implementation of the course. Overall, the collaborative design team determined that the course co-design experience resulted in an enhanced course design with meaningful assessment rubrics, and offered a valuable professional learning and online teaching experience for the design team.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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