Assessment of Professional Development Activities, Instructional Needs, and Methods of Delivery for Part-Time Technical and Occupational Faculty in U.S. Community Colleges
Bibliographic record
Abstract
This study describes the professional development activities and perceived instructional needs \nand best methods of delivering professional development opportunities for part-time occupational and technical program faculty within the community colleges in the U.S. Introduction to the policies and procedures of the college and/or department, introduction to other college faculty/staff, orientation to the course/classroom, and help in meeting administrative requirements were the professional development activities found to occur at least once a quarter or semester. The types of instructional help part-time faculty members were perceived to need most were: (a) identifying the learning characteristics of students, (b) alternating teaching methods to accommodate different learning styles, (c) participation in \nweb-based instruction, and (d) participation in distance learning. It was discovered that professional development activities should be offered to part-time faculty at least once per semester or quarter using seminar discussions, group classroom activities, and computer assisted instruction or multi-media interaction as the preferred methods of delivery. An evening/night format and during the Fall were found to be the most suitable times to offer professional development opportunities and per diem and travel \nexpenses should be provided to part-time faculty for participation in professional development activities.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".