Iowa Virtual Literacy Protocol: A Pre-Experimental Design Using Kurzweil 3000 Text-to-Speech Software with Incarcerated Adult Learners.
Notice bibliographique
Résumé
The problem: The increasingly competitive global economy demands literate, educated workers.Both men and women experience the effects of education on employment rates and income.Racial and ethnic minorities, English language learners, and especially those with prison records are most deeply affected by the economic consequences of dropping out of school.The purpose of this study is to assess the effect of adaptive technology (text-to-speech software) on incarcerated low-literate adult populations.This study will determine the effectiveness of text-to-speech computer software technology with incarcerated adult learners seeking to improve literacy competencies.paying, dead-end jobs.Only 7% of dropouts 25 and older have ever made more than $40,000 a year (Johnson, 2011).In hard economic times, some will find that not having a diploma puts them at the front of the unemployment line.High school dropouts can expect to earn significantly less than high school graduates due to both income differences and employment rates.Over a lifetime, a high school dropout will earn $200,000 less than a high school graduate (Johnston, 2011).For more than 60 years, millions of adults who did not complete their formal high school studies have used the General Educational Development (GED) Tests to realize both personal satisfaction and educational and occupational opportunities.The GED Testing Program provides high-quality tests and accessible testing services for individuals who may benefit from high school diplomas or certificates, awarded by participating jurisdictions in the United States, Canada, and U.S. insular areas (American Council of Education, 2008). 1 However, obtaining a GED is no quick fix for low earnings: it takes time for substantial GED-related differences to accrue (Tyler, 2007).For example, for Black men obtaining GED certificates in prison, they do not realize immediate economic payoff until after five years (Tyler, 2007).A recent study in Florida linked GED Test information to quarterly earnings records collected by Florida's unemployment insurance system.The study included 81,170 individuals, all of whom were between the ages of 16 and 40 when they attempted the GED.Five years after achieving a GED, the GED holders' income showed a 15% gain (Tyler, Murname & Willett, 2000).But even when high school dropouts use the GED Tests to obtain basic credentials, they often decline to pursue further education, limiting their life chances in a 1 An example of an insular area is American Samoa.The Samoans have adopted their own constitution, are not American citizens, do not pay federal taxes, and control their own borders.Other examples of insular areas include Guam, U.S. Virgin Islands and Puerto Rico.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».