Work In Progress: Beyond Textbook: An Open Educational Resource Platform that Generates Course-Specific E-Textbooks
Bibliographic record
Abstract
Beyond Textbook (BT) is an Open Educational Resources (OER) platform that combines an etextbook generation algorithm with a website interface.The frontend allows users to upload lecture notes.Then, given a list of topics, the backend matches each topic with the most relevant lecture notes, merges these lecture notes into one file, and finally generates a customized etextbook for users to view and download.BT is developed to provide instructors and students with an e-textbook that is customized to specific requirements in a course.BT offers a zero-cost avenue to deliver and access curriculum content in a standardized, but collaborative and dynamic manner.The goal is to reduce the financial barrier to education, allow students to have access to up-to-date educational content, and leverage modern technology to improve pedagogy and learning.We proceeded with a trial run of BT involving both instructors and students in a firstyear course and collected their feedback.Survey results identified that all participants found BT to be a useful educational tool and would use it upon its release.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".