Desktop Virtual Reality Applications for Training Personnel of Small Businesses
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
Small and medium-sized businesses (SMBs) in most world economies suffer from a series of intense economic pressures from local, regional and international markets. Although these problems are microeconomic to the small and medium-sized business, they are directly related to macro economic factors, particularly in the case of labor. One of the main pressures small and medium-sized businesses suffer from is the lack of worker technical skills. Past research has consistently shown that virtual reality (VR) can be effective for supporting competency-based training skills. The objective of this chapter is to provide an overview on how virtual reality can be used to support technical training in SMBs, including the use of Second Life and DIVE VR platforms. This chapter describes a desktop VR Application for training car mechanics from a small business and highlights advantages and challenges of desktop virtual reality for technical training. Finally, future trends related to the use of VR in training are discussed.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it