Transforming faculty development programs from face-to-face to blended/hybrid environments
Bibliographic record
Abstract
Faculty development programs are critical to the success of the learning and teaching process in higher education. With the rapid development of blended courses there is a need to transform the face-to-face faculty development programs to blended programs. The transformation requires instructors to examine new teaching methods and techniques, and obtain new skill set to ensure the success of the learning process and students’ engagement in the new environment. Blended teaching is not just about transferring part of the training course online, but involves creating online activities that engage learners and complement the face-to-face activities. The role of the instructors changes from lecturer to facilitator of learning, coach and collaborator. Through participation in blended learning environments, instructors could experiment the new teaching strategies in a collaborative and safe environment. This paper presents the process, benefits and challenges of transforming the Instructional Skills Workshop (ISW) for instructors from a three-day twenty four hours intensive format to four-week blended format. The Instructional Skills Workshop is peer-based training in which participants interact and present lessons in small groups to develop effective instructional skills through the use of constructive feedback strategies. Strategies associated with the re-design process which is based on the instructional design theories and principles will be presented. The paper presents data from formative and summative evaluations on communication, instructional skills and course design. The recommendations will address best practices that could be used to transform many faculty development programs from face-to-face to blended formats. Keywords: Hybrid, Online, Blended Teaching, Blended Learning, Faculty Development Programs, Instructional Skills.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".