Online Homework and Student Success in Preparatory Chemistry
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
Adoption of the cyber learning system Assessment and Learning in Knowledge Spaces (ALEKS) and subsequent inter-departmental coordination of assignments and deadlines led to increased student success in a preparatory, lecture-only chemistry course with large enrollment, CHEM 101. This article describes the process of our adoption and optimization of ALEKS in this course. As a result of our efforts, we were able to increase the pass rate for this course from 60.8% in the fall quarter 2009 to 73.9% in the fall quarter of 2012. The average GPA in CHEM 101 increased from 1.96 to 2.42. At the same time, students scores on the ACS 2009 Toledo Examination improved from an average of 27 (±6.0) in the pre-test to 34 (±6.8) in the post-test. This represents an improvement from the 25 to the 59 percentile compared to national data.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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