Applying Semiotic Theories to Graphic Design Education: An Empirical Study on Poster Design Teaching
Bibliographic record
Abstract
<p class="apa">The rationales behind design are dissimilar to those behind art. Establishing an adequate theoretical foundation for conducting design education can facilitate scientising design methods. Thus, from the perspectives of the semiotic theories proposed by Saussure and Peirce, we investigated graphic design curricula by performing teaching experiments, verifying the adequacy of applying these theories to poster design. During the teaching experiment, a matched groups design method was used for assigning 30 students to either an experimental group or a control group. The results of the experiment revealed that compared with the control group students, the experimental group students, who applied the semiotic theories to their poster designs, performed more favourably in image creativity, picture aesthetic, typography, and total poster design score. The posters created by the students were submitted to International Triennial of Ecological Posters ‘the 4th Block’, and a total of 4 creations from the experimental group were accepted. The results of the teaching experiment verify that applying semiotic theories to graphic design curricula facilitates improving student ability to observe objects and cultivating their capability to design posters and reinforce the visual tension in the posters.</p>
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".