What Every Writing Teacher Should Know and Be Able to Do: Reading Outcomes for Faculty Members
Bibliographic record
Abstract
The need for much better preparation of faculty on reading arises from evidence in three areas: students’ problems with critical reading and thinking, lack of extant faculty preparation in reading pedagogy, and an absence of focused faculty development to improve student reading. Many recent studies show clearly that students do not read as well as they might, online and off. Both quantitative studies like the ACT’s data on over a million students in the U.S. and Canada and qualitative studies like the Citation Project show that half or more of current college students lack the skills to analyze, synthesize, evaluate and use material they have read for their own purposes, in school and beyond. Critical and analytical skills are particularly lacking as shown in untimed tests by Stanford University researchers of students’ ability to evaluate online material. To address students’ needs, clear goals for faculty development can help. Pre-service faculty should be trained in the psycholinguistics of reading as well as in teaching techniques. In-service faculty should have access to professional development to understand students’ reading needs and address them more effectively. Collaborations across campus with library faculty can also provide useful approaches to building students’ online critical reading skills.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.061 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".