Use of Social Software to Address Literacy and Identity Issues in Second Language Learning
Bibliographic record
Abstract
The emerging trend of social software technology can address many different second language (L2) learner needs through authentic social interaction and a variety of scaffolding processes. Social software connects education with real-life learning and interests, and engages and motivates students. It can facilitate learning environments that are more learner-centred, informal and collaborative. Increasingly culturally and linguistically diverse classrooms and uneven access to technology are revealing educational inequalities for English Language Learners (ELLs) (Pruitt-Mentle, 2007). In a review of the literature, the author explores how social software tools, through the lens of socio-constructivist theory, can support literacy development and improve linguistic power relationships, building self-esteem and encouraging positive educational and identity experiences for L2 learners. Recommendations for future research on social software use focusing on issues of appropriateness and responsible use for L2 learners, acceptance of social tools and technology accessibility, are presented. Résumé : La nouvelle tendance de la technologie des logiciels sociaux répond à plusieurs besoins différents d’apprenants de langue seconde (L2) grâce à une interaction sociale authentique et une variété de processus d’échafaudage. Les logiciels sociaux font le pont entre l’éducation et l’apprentissage et les intérêts dans la vie réelle; ils stimulent également l’engagement et la motivation des élèves en plus de fournir des environnements d’apprentissage qui sont davantage centrés sur l’apprenant, plus informels et plus collaboratifs. Les salles de classe de plus en plus culturellement et linguistiquement diversifiées ainsi qu’un accès disproportionné à la technologie révèlent des inégalités en matière d’éducation pour les apprenants de l’anglais (Pruitt-Mentle, 2007). Dans ce document, l’auteur explore, à travers le prisme de la théorie socio-constructiviste, comment les outils logiciels sociaux peuvent favoriser le développement de la littératie et améliorer les rapports de pouvoir linguistiques, contribuer à la construction d’une estime de soi positive et encourager les expériences éducatives et identitaires positives pour les apprenants de L2. L’article émet des recommandations pour la conduite de recherches futures sur l’utilisation des logiciels sociaux en se concentrant sur les questions de leur pertinence et de leur utilisation responsable par les apprenants de L2, de l’acceptation des outils sociaux et de l’accessibilité de la technologie.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".