Review of the Studies on Multimedia Annotation in China Over the Past Two Decades
Bibliographic record
Abstract
This paper reviews the studies on multimedia annotation from the following perspectives: theoretical construct on multimedia annotation, the empirical research on different effectiveness of types of multimedia annotation on the reading/listening comprehension and vocabulary acquisition, which aims to help the overseas scholars to know the present situation and the direction for the future research on multimedia annotation in China. The source data is mainly from the articles on multimedia annotation published in CNKI from Jan. 2000 to Jan. 2020 (www.cnki.net), and the situation is as follow: (1) most domestic scholars introduce and verify the multimedia annotation theories through empirical researches; (2) the researchers focus more on the effects of the types of multimedia annotation on the reading comprehension and the vocabulary acquisition compared to the effects on listening comprehension, and it could be classified into three effects: positive, negative and no effect, but the factors causing the above effects have not been systematically studied or summarized; (3) most scholars mainly take intermediate and advanced language level learners as the research subjects, the lower level learners should be also considered; (4) in the research of the types of the multimedia annotation, the theme of the research materials in reading/listening comprehension would be a new prospective which has been rarely studied compared to other types. To sum up, more researches should be done to investigate the effects of different types of multimedia annotation to the reading/listening comprehension and vocabulary acquisition, which should cover wider range of subjects and consider different types of experiment materials. And the author believes that it will enhance the EFL learning and teaching in the future.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".