Development of ethical codes for instructors engaged in distance education: a Delphi study
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
Ethical codes are written documents that delineate a set of rules and principles that guide the duties and responsibilities of professionals within a professional organization from an ethical perspective. The research aims to develop an ethical code framework for instructors engaged in distance education. The Delphi, a qualitative research method, was employed to achieve this aim. The study included 22 distance education experts, selected via purposive sampling. The Delphi technique, conducted in three rounds, commenced with an evaluation of the ethical dimensions of distance education. In the study’s second phase, we invited participants to suggest additional ethical codes for the agreed-upon dimensions. We collected the suggestions and agreed on specific ethical code items in the third round. The researchers thus established the final form of the ethical code list. This process resulted in developing an ethical code framework for instructors engaged in distance education. The framework comprises sixdimensions: Instructional Design (ID), Social Interaction (SI), Content Provision (CP), Technology Usage (TU), Management (M), and Assessment and Evaluation (AE). It includes 62 ethical code items. The study demonstrates that the ethical code dimensions align with the roles of online instructors, as described in the relevant literature. This alignment substantiates the ethical code framework's validity and reliability.
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 | 0.000 |
| 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 | 0.001 |
| 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