The Implementation Fidelity, Contributions, and Challenges of Augmented Reality in Some Selected Pre-Primary Schools of Addis Ababa City Administration
Bibliographic record
Abstract
This study aimed to investigate preprimary school teachers' perspectives on the fidelity, contributions, and challenges of Augmented Reality and 3D visualization in the preprimary education program. Quantitative and qualitative approaches with concurrent triangulation designs were employed to address the purpose of the study. The participants of the study were seventeen preprimary education teachers, two preprimary education principals, one Augmented Reality designer, and four staff members from Plan International, selected by employing purposive sampling techniques. A survey questionnaire, interview, focus group discussion, and document analysis were used to collect the data. Both quantitative (mean and standard deviation) and qualitative (thematic analysis) techniques were used to analyze the data. Findings revealed that Augmented Reality application practice in exploration, installation, and implementation stages were well addressed through the project activities. Preprimary education teachers believed that augmented reality had several contributions, including improving children’s motivation, interest, memory, active involvement, fine motor skill, social interaction, and digital literacy skills. There are a variety of difficulties that affect how Augmented Reality is implemented. The application has several hurdles including limitation in the pedagogy, misalignment with the curriculum, inadequate preparation of the Augmented Reality for KG2, and challenges with using Augmented Reality in large classes. Finally, preprimary education opts to consider emergent ideas, outcomes, and methods. Thus, the application of Augmented Reality needs to reconsider how it can foster curiosity, imagination, reflection, and creativity in the learning process.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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 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".