Milieu in Dental School and Practice Electronic Curriculum Implementation at North American Dental Schools
Bibliographic record
Abstract
Abstract: Electronic curriculum, or E-curriculum, refers to computer-based learning including educational materials available on CD or DVD, online courses, electronic mechanisms to search the literature, email, and various applications of instructional technology including providing laptops to students, multimedia projection systems, and Internet-compatible classrooms. In spite of enthusiasm about the potential for E-curriculum to enhance dental education, there is minimal guidance in the literature to assist schools with implementation. The study objectives were: 1) identify U.S. and Canadian dental schools that have initiated mandatory laptop programs and assess cost, faculty development issues, extent of curricular use, problems, and qualitative perceptions; 2) determine the extent to which twenty-two other E-curriculum resources were available and used at North American dental schools; and 3) identify factors that influenced E-curriculum implementation. A twenty-six item questionnaire, known as the Electronic Curriculum Implementation Survey (ECIS), was mailed to all sixty-six North American dental schools (ten Canadian and fifty-six U.S. schools) during 2002-03 with a response rate of 100 percent. Twenty-five of the twenty-six ECIS questions employed a menu-driven, forced choice format, but respondents could provide amplifying comments. Fifty-three questionnaires were completed by associate deans for academic affairs, three by deans, and ten by instructional technology (IT) managers, IT committee chairs, or directors of dental informatics departments. The survey found that E-curriculum implementa-tion among North American dental schools is following the classic innovation pattern in which a few early adopting institutions proceed rapidly while the majority of potential adopters make modifications slowly. Fourteen U.S. dental schools have estab-
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".