Electronic vs. Traditional Textbook Use: Dental Students’ Perceptions and Study Habits
Bibliographic record
Abstract
This descriptive study assessed dental students' attitudes about computer use as it relates to study habits and use of e-textbook technology. Academic deans and student leaders at all accredited dental education programs in the United States, Puerto Rico, and Canada were asked to forward an e-mail to students explaining the purpose of the study and asking them to participate. The e-mail included an embedded URL link to the survey. A total of 703 complete responses from twenty-four dental schools were received and used in the final analysis. Because the number of students contacted could not be determined, the overall response rate cannot be calculated. Over 65 percent of the respondents reported spending >11 hours per week studying although over 75 percent said they spent little time studying from their textbooks. Over 55 percent were from schools that use e-textbooks exclusively, with 25 percent from schools that exclusively use print textbooks. One-fourth indicated they purchased a traditional printed textbook even when an e-textbook was provided; more than one-third printed information from the e-textbooks rather than reading on the computer. A majority (59 percent) preferred traditional textbook resources over e-textbooks, with over 50 percent reporting not using the required e-textbooks at all. E-textbooks were used by students in this study less frequently than materials/notes provided by dental school faculty. The majority preferred to use traditional resources as references and for augmenting lecture material.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".