The Role of Interactive Technologies in the Development of Interior Architecture of Lecture Halls in Arts and Design Colleges – A Comparative Study
Bibliographic record
Abstract
This research examines the role of interactive technologies in the development of interior architecture in lecture halls and facilities within Arts and Design colleges. It emphasizes the importance of interactive design as a tool to enhance the educational process and foster interaction between students and instructors. The study highlights the link between the interior design of educational spaces and academic outcomes, focusing on technologies such as Virtual Reality (VR), Augmented Reality (AR), and interactive displays in classrooms, studios, and other facilities. The research addresses the limited adoption of these technologies in arts institutions, which negatively impacts the quality of the learning environment and reduces engagement and motivation. The objective is to identify the most commonly used technologies, evaluate their impact on academic performance, and present a comparative study of three models: a local (Applied Science University – Jordan), a regional (Canadian University – Dubai), and a global (Mount Royal University – Canada). Using a descriptive-analytical approach, the study assesses the types of interactive technologies and their effects on educational spaces. The results show that interactive design enhances active learning, increases the flexibility of learning environments, and improves the overall learning experience. The study also demonstrates that the effectiveness of lecture halls is directly linked to the integration of interactive technologies in their interior design. Based on these findings, it is recommended to restructure the interior architecture of Arts and Design colleges to support digital transformations through adopting modern technologies and providing faculty training to improve education and student experience.
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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 | 0.000 | 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 | 0.000 |
| 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".