<scp>VILLAGE</scp> — <scp>V</scp> irtual <scp>I</scp> mmersive <scp>L</scp> anguage <scp>L</scp> earning and <scp>G</scp> aming <scp>E</scp> nvironment: Immersion and presence
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Metaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
- Consensus categories
- Meta-epidemiology (narrow), Science and technology studies, Research integrity
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: Not applicable
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.156
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.243 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Abstract 3 D virtual worlds are promising for immersive learning in E nglish as a Foreign Language ( EFL ). Unlike E nglish as a Second Language ( ESL ), EFL typically takes place in the learners’ home countries, and the potential of the language is limited by geography. Although learning contexts where E nglish is spoken is important, in most EFL courses at the college level, EFL is taught by acquiring vocabularies, grammar and pragmatic features without contextual immersion. In this study, an immersive E nglish learning environment in a 3 D virtual world, O pen S imulator, was developed with two key learning artifacts, chatbot and time machine. A single‐factor, independent measures design was used to examines learners’ presence under four learning conditions: virtual learning environment without digital learning artifacts ( VE ), virtual learning environment with chatbot ( VEC ), virtual learning environment with time machine ( VETM ) and virtual learning environment with chatbot and time machine ( VECTM ). Three research questions emerging from the four learning conditions form the backbone of this study: (1) Does chatbot increase language learners’ presence in the immersive virtual E nglish learning environment? (2) Does time machine increase language learners’ presence in the immersive virtual E nglish learning environment? (3) Does the combined use of chatbot and time machine increase presence more than either learning artifact alone? The experimental results indicate that the chatbot and time machine increase the learners’ sense of immersion and presence. Best design practices should address how immersion and presence can be integrated into affordances of virtual worlds.
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.
The record
- Venue
- British Journal of Educational Technology
- Topic
- Virtual Reality Applications and Impacts
- Field
- Computer Science
- Canadian institutions
- University of British Columbia
- Funders
- not available
- Keywords
- ChatbotAffordanceImmersion (mathematics)Computer scienceVirtual machineLearning environmentMultimediaMetaverseVirtual learning environmentLanguage acquisitionSense of presenceHuman–computer interactionWorld Wide WebVirtual realityPsychologyMathematics educationOperating system
- Has abstract in OpenAlex
- yes