Comments on Motivation in Real-Life, Dynamic, and Interactive Learning Environments
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
Articles published in this special section report state-of-the-art research on motivation and related constructs by studying learners in authentic and dynamic situations. Each research team demonstrates the value of using multiple methodologies. I draw out four themes that illuminate critical issues in this area of research: First, learners hold multiple goals simultaneously. Second, holding multiple goals affords opportunities for self-regulation. Third, goals and motivation evolve over time, although we know little about the trajectory of this process. Fourth, investigations that adopt multiple methodologies create opportunities to accelerate progress in the field. I also offer an alternative interpretive stance, a cognitive one, for theorizing about these constructs. I attempt to stimulate alternative but not antithetical views for future research about motivational constructs and their relations to learners' participation in classroom activities and achievements.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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