Seeing Beyond Words: An Investigation of Students' Opinions on Interactive Murals for Vocabulary Teaching
Bibliographic record
Abstract
This study investigates the ways in which students view interactive murals as part of the vocabulary teaching and learning process in the classroom. A qualitative methodology and survey were administered to 22 elementary school students. The three components of the questionnaire were as follows: the pedagogical content of the feature of interactive mural, and motivation in using the murals. The questionnaire was administered to a research sample of 22 students who were specifically selected for the study. With a coefficient of scalability (CS) of at least 0.60 and a coefficient of reproducibility (CR) of at least 0.90, the data were deemed to meet the unidimental and cumulative features after being analyzed using the Guttman scale. The results revealed that the mean CS score was 0.91, indicating that the coefficients of scalability were deemed good, and the mean CR score from the three indicators was 0.90, indicating that the CR results were valid. Considering the mean recapitulation rate among the students was 16,33%, the students’ perception was positive. The results, which showed that students’ perceptions of the interactive smural’s use as a technology in the classroom were positively correlated with their use of learning resources. It was possible for the students to acquire new teaching tools, such as interactive murals. Murals werehave been suggested as a potentially engaging substitute for traditional classroom media, particularly when teaching vocabulary. In summary, by documenting the diverse perspectives, this research not only sheds light on the perceived advantages of interactive murals but also emphasizes how these visual aids can be utilizedused to create captivating and productive vocabulary learning opportunities. The findings have implications for teachers, curriculum developers, and legislators who want to improve vocabulary instruction in the classrooms by incorporating interactive and visually appealing elements of murals.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".