The Design and Implementation of an Educational Augmented Reality Application for Logical Circuit Design
Bibliographic record
Abstract
The purpose of the study is to determine the effect of augmented reality applications on the learning of engineering students in their professional courses. The objective of the study is to ensure that augmented reality technologies, which are among the most important technologies of today, are used in educational settings. The other important objective of the study is to ensure that the augmented reality technologies used in professional training in countries such as the USA, Canada and the Netherlands are also used in our country and to provide a world-class education opportunity. Also, contributing to the economy of our country with the successful studies to be carried out in this regard is among the objectives of the study because of the increasing interest in augmented reality software throughout the world and the formation of an important economy related to the development of these kinds of software.In the study, an augmented reality application developed by the researcher was used in the learning process of a subject included in the faculty of engineering education curriculum. The study was performed using a convergent parallel mixed-methods design in which both qualitative and quantitative data were used simultaneously. The result of the study showed that there were no significant difference between the average attitude towards AR applications of the students participating in the study and the gender, class, and father education level; however, it is seen that there was a significant difference between maternal education status. It was also determined that the difference between the students’ average attitude towards AR applications before and after the study was significant.Similarly, it was observed that the difference between the AR attitude averages before and after the study and the AG attitude average 4 weeks after the study was also observed to be significant. It was also found that the students who participated in the study found the AR applications remarkable, entertaining, understandable and useful for the instructor. Moreover, they stated that using AR applications in lessons would contribute to fast and active learning and increase success.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".