Flexible Learning Strategies in First through Fourth-Year Courses
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
Flexible Learning (FL) is a pedagogical approach allowing for flexibility of time, place, and audience, including but not solely focused on the use of technologies. We describe Flexible Learning as a pedagogical approach in four courses framed by three key themes: 1) objectives and aspects of course design, 2) evaluation and assessment, and 3) challenges and improvements. Examples of strategies include: digital media-based assignments; iClicker and on-line quizzes; a librarian-created tutorial and links to copyright-cleared readings; use of Calibrated Peer Review as formative feedback; TurnItIn for self-review; wiki sites, group blogs and community work through Community-based Action Research (CBAR) conducted through the pedagogy of Community-Based Experiential-Learning (CBEL). We believe that the transferability of our experiences and findings is most relevant to educators seeking to create learning experiences that increase student engagement with complexity and uncertainty. FL approaches can help educators create learning environments that more closely resemble the contexts that students find upon graduation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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