Outcomes from Professional Experience Provision for Students Through Media Development and Special Hybrid Event During Covid-19 Pandemic
Bibliographic record
Abstract
This research was aimed to provide professional experience to students, to develop and examine the quality of media development and special hybrid event during Covid-19 pandemic, to evaluate the perception, and the satisfaction of the sampling group towards media and special hybrid event during Covid-19 pandemic. The tools in this research consisted of 1) an interview schedule for students regarding professional experience provision, 2) media and special hybrid event during Covid-19 pandemic, 3) evaluation forms for quality of contents and media presentation and activities, 4) a perception evaluation form, and 5) a satisfaction questionnaire for the sampling group regarding media and special hybrid event during Covid-19 pandemic. The data were collected from 30 fourth-year undergraduate students from the Department of Educational Communications and Technology who enrolled in the ETM 361 Presentation Skill II course and participated in the project to raise funds for students with financial hardship in the Faculty of Industrial Education and Technology. They were chosen using purposive sampling method. The statistical methods were percentage, mean score, and standard deviation. The findings were as follows: after the professional experience provision for students,and interview them, such experience helped students gain skills in planning, problem solving, and teamwork. Therefore, the training in this course could really provide quality professional experience to students. With regards to media development and special hybrid event during Covid-19 pandemic, this research followed the ADDIE Model which consists of 5 steps as in Analysis, Design, Development, Implementation and Evaluation. The expert panels then evaluated the quality. It was found that the quality of contents was at a very good level (x = 4.77, S.D. = 0.42) and that the quality of media presentation and activities was at a very good level (x = 4.76, S.D. = 0.45). The perception and the satisfaction of the sampling group regarding the media development and special hybrid event during Covid-19 pandemic was at the highest level (x = 4.79, S.D. = 0.45), (x = 4.76, S.D. = 0.45). Therefore, the professional experience provision for students through media development and special hybrid event during Covid-19 pandemic was of good quality.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".