Personalized Learning and Online Instruction
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
This development of digital inclusion with personalized learning has had an impact on how courses are designed and delivered. To that end, a behavioral approach that combines digital with personalized learning is CAPSI (computer-aided personalized system of instruction). In CAPSI, students decide when and where to study course material and where and when to take a test on their learning. The changes occurring in higher education also need to incorporate the development of critical thinking skills. CAPSI is highly adaptable to developing critical or higher-level thinking based on Bloom's taxonomy; CAPSI's emphasis on written answers, providing feedback, and writing appeals leads to higher order thinking. To assess student satisfaction, questionnaires given at the end of a course show that many students find CAPSI to be beneficial to their learning. Also, due to its flexible design, CAPSI is highly modifiable and can be used in all courses in a variety of locations and with students at different educational levels.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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