Incorporation of Student-Generated Problems in an Online Textbook
Bibliographic record
Abstract
An open-source online statics textbook was developed to support students in an engineering statics course.Through the course, students were asked to develop and solve their own problems using real-world examples for one of the concepts in that assignment.The motivation for this request was to help students see statics concepts applied in their every-day lives, to express their creativity, to have them review the technical content of that week at a higher level, and to engage with one topic more deeply.Additionally, students were given to option to publish their examples in the online textbook, and 58% of the class submitted 59 real-world examples.A previous study found that 93% of the students thought the activity should be completed in future years, and that students were motivated to publish examples in order to support students in future years and learn the material.Four student assistants were hired to help create the textbook and digitize examples.This paper documents their experience and describes lessons learned for the development of open-source online materials.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".