From First Life to Second Life: Evaluating task-based language learning in a new environment / De la vie réelle à la vie virtuelle: évaluation de l'apprentissage des langues basé sur les tâches dans un nouvel environnement
Bibliographic record
Abstract
Second Life is an avatar-based 3D virtual world that has recently received attention from educators and researchers in various fields to explore its pedagogical benefits. Considering the increasing implementation of technologies broadly in much instruction, this study investigated how different task types affect ESL students’ use of Second Life environment, and factors that determine success or failure of a task completion. Enrolled in a university ESL program, 34 high- and low-intermediate students participated, and they were asked to use the voice-chat function and communication features of avatars as they participated in three task types: Jigsaw, Decision-making, and Discussion tasks, representing the continuum of communicative tasks by Pica, Kanagy, and Falodun (1993). Emerging phenomena from the data described how the different levels’ of ESL students used Second Life environment in different task types, focusing on avatar use, telepresence, and affordances, and critical factors that led success or failure of task completion. « Second Life » est un univers virtuel en 3D basé sur des avatars qui a récemment retenu l'attention des éducateurs et des chercheurs de divers domaines, désireux d’explorer les avantages pédagogiques de ce jeu. Étant donné l’application croissante des technologies en éducation, cette étude a examiné la manière dont différents types de tâches affectent l’utilisation de l’environnement « Second Life » chez les étudiants d’anglais langue seconde (ALS), et les facteurs déterminant le succès ou l'échec dans l’exécution d’une tâche. 34 étudiants universitaires inscrits dans des programmes intermédiaires d’ALS de niveaux différents ont été invités à utiliser les fonctions de conversation orale (chat vocal) et de communication des avatars alors qu’ils participaient à trois types de tâches: casse-tête, prise de décision, et tâches de discussion, correspondant à l’éventail des tâches communicatives de Pica, Kanagy et Falodun (1993). Les données montrent de façon provisoire comment les d’étudiants d'ALS de différents niveaux ont utilisé l’environnement « Second Life » dans des types variés de tâches, en mettant l'accent sur l'utilisation des avatars, la téléprésence et les affordances, et révèlent les facteurs cruciaux qui ont conduit au succès ou à l'échec dans l'exécution des tâches.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".