Textbook Affordability and Student Acceptance of eTextbooks: An Institutional Case-study
Bibliographic record
Abstract
There is significant interest among institutions of higher education in the potential of digital textbooks to enhance student learning and to address issues arising from textbook affordability. Innovations in digital textbook design and delivery infrastructure and the emergence of exemplary practices from early adopters signal that digital reading may be a practical alternative to print. Less well understood, however, is students’ experience of textbook affordability, their experience of print and digital textbook utilization, and factors that might influence their acceptance of digital textbooks. This paper explores the results of a semester-long eTextbook research project at a Canadian college and shares six suggestions grounded in student feedback. Les établissements d’enseignement supérieur s’intéressent considérablement au potentiel des manuels numériques pour améliorer l’apprentissage des étudiants et pour répondre au problème du coût élevé des manuels. Les innovations dans le domaine de la conception des manuels numériques et de l’infrastructure de leur distribution, ainsi que l’émergence de pratiques exemplaires de la part des premières personnes qui ont adopté ces manuels, signalent que la lecture numérique peut être considérée comme une alternative pratique à la page imprimée. Toutefois, ce que l’on connaît moins, ce sont l’expérience des étudiants face au coût des manuels, leur expérience à utiliser des manuels imprimés ou des manuels numériques, ainsi que les facteurs qui pourraient influencer leur acceptation des manuels numériques. Cet article explore les résultats d’un projet de recherche portant sur l’utilisation d’un manuel numérique pendant tout un semestre dans un collège canadien et présente six suggestions basées sur les rétroactions des étudiants.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".