The Development of Digital Content on the Metaverse Combined with Interactive Communication Activities with Professional on TikTok Marketing for Students
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
This research aimed to 1) examine the needs for developing digital content on the metaverse 2) develop and evaluate the quality of digital content on the metaverse combined with interactive communication activities 3) compare the perception of the sample group before and after viewing the digital content, and 4) assess the satisfaction of the sample group with the digital content and activities. The tools used in the study include a needs survey, content and presentation quality evaluation forms, perception assessment, satisfaction assessment, and the digital content with interactive activities, which the researcher developed, consisted of 26 posters and 8 video clips. The sample group included 48 third-year students from the Department of Educational Communications and Technology, who registered for ETM 358 Marketing Communication in the second semester of 2023. Simple random sampling was used, selecting students who had previously viewed the content and were willing to respond to the survey. Statistical analysis involved mean, standard deviation, and t-test. The results showed that the sample group's demand for developing digital content with communication activities was at the highest level. Based on this, the digital content on the metaverse, combined with interactive communication activities with professional, was developed and evaluated by experts. The content quality was rated at a very good level, while the presentation quality was rated at a good level. Perception assessment after viewing the content and activities showed a significant improvement (p < .05), and satisfaction was rated at the highest level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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