Learning Choices: A Map for the Future
Notice bibliographique
Résumé
<p>Dusseldorp Skills Forum has commissioned this report to provide a comprehensive picture of the Learning Choices sector, to pull together the existing research and evidence, summarise the data and findings that are available, and identify the gaps in knowledge.</p><p>A wide variety of alternative (Learning Choices) educational programs have been developed in Australia aimed at (re-)engaging young people with education. Some of these grew out of interest in progressive and democratic approaches to education while others responded to policy pressures to enable more young people to complete school. However, alternative education in Australia is fragmented both as a sector of educational practice and as a field of research. This means we have only limited knowledge about the range of programs that exist.</p><p>What we do know is that Learning Choices programs offer vital pathways to enable young people to remain in school or to return to complete their education. There is clear evidence for the need such Learning Choices programs address. Retention to Year 12 has stabilised at around 75% since the mid-1990s (ABS, 2010). The retention rate for Indigenous young people continues to lag well behind at only 45% (Purdie and Buckley, 2010). The OECD provides comparative data for what it calls upper secondary attainment. The secondary school drop out rate is given as 14.7% for Australia compared to 12.9% for the OECD and 11% for the European Union (OECD, 2009). More than 16% of 15-19 year olds in Australia are not fully engaged and nearly a quarter of 20 to 24 year-olds: that is not in full time education or full time work (FYA, 2010, p.5; p.22). The concern grows when considering those 15-24 year olds who completed Year 10 or below: almost 57% are not fully engaged in the year after leaving school (FYA, 2010, p.21). Early school leaving has been linked to increased likelihood of unemployment, underemployment, crime and ill-health (AIG and DSF, 2007; BCA, 2003; FYA, 2010).</p><p>The policy response has been to negotiate a national agreement on youth attainment and transitions: the National Partnership on Youth Attainment and Transitions. As part of this, the Australian Federal, State and Territory governments agreed to a target to raise the Year 12 (or equivalent) attainment rate to 90% by 2015 (CoAG, 2009, p.7). Achieving this target will require many young people who traditionally have left formal education early, for whatever reason, to remain in or return to education. Learning Choices programs play an important role in enabling these young people to attain Year 12 or equivalent qualifications and thereby assist governments to meet their target. Knowledge about the contribution Learning Choices programs make to engaging young people with education and helping them attain credentials is imperative.</p><p>For the past decade Dusseldorp Skills Forum has built connections among Learning Choices programs through its Learning Choices expos in 2004 and 2006 and its Learning Choices website: www.learningchoices.org.au. In 2011, Dusseldorp Skills Forum further developed this by conducting a national survey of Learning Choices programs and initiatives. The Learning Choices National Scan used the definition of those programs/schools that cater for young people at risk of not completing their education. More than 400 individual entries were made by the end of the survey period. Although inevitably not all relevant programs are included, this is the most comprehensive database of Learning Choices programs currently available.</p><p>This report draws on data from the National Scan, supplemented with reports from individual programs (see Appendix 1) and existing research publications (see Appendix 2 for a selected annotated bibliography) to provide an overview of alternative education provision in Australia.</p>
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 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».