Differentiation of Roles: Instructional Designers and Faculty in the Creation of Online Courses
Bibliographic record
Abstract
Instructional design has continued to change and undergo metamorphosis. A key component of this process in higher education is the collaboration between an instructional designer and one or more faculty members to create a robust, quality online course. In this collaborative process, instructional designers are clearly the design expert, while the faculty member is the content expert. However, problems occur when roles are not clearly delineated. Conflict is often reported by instructional designers who feel they are not respected by faculty. Conflict can also occur when instructional designers cross the line and try to influence content instead of providing guidance on content delivery. In order to decrease conflict, the roles of instructional designers and the faculty they collaborate with must be clearly defined. Both the instructional designer and the faculty member should clearly articulate their expected roles in the collaborative course creation process. In addition, written policies and procedures for the instructional design process are crucial to the success of these collaborative relationships.
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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 | 0.083 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.019 | 0.020 |
| Scholarly communication | 0.029 | 0.024 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".