Augmented Reality and Museum Education: Rethinking Interactive Learning Experiences in Museums
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The digital era creates new opportunities for museum educators to enhance visitors' interaction, play, and learning with exhibits and objects. Although museum-based studies suggest that new technologies can assist in communicating science and enhancing science learning (Heath & vom Lehn, 2008), little is yet known about the use of augmented reality (AR) in and for museum education in Canada and internationally. Through presenting an AR project that took place at Science World in Vancouver, BC, this chapter offers insights into ways of harnessing AR in a museum exhibit. The chapter considers how the AR-integrated museum exhibit can enhance visitors' interactive learning experiences with virtual objects: a pedagogical approach combining technology, artifacts, and spaces. In doing so, this chapter contributes to the discourse on interactivity in museum settings and suggests design strategies to re-envision museum visitors' interactivity and learning through AR technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it