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Using School-Wide Data to Advocate for Student Success

2002· article· en· W172645906 sur OpenAlex

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aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
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Notice bibliographique

RevueProfessional School Counseling · 2002
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSchool Choice and Performance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGraduation (instrument)Report cardQuarter (Canadian coin)PsychologyMedical educationMathematics educationPedagogyMedicineGeographyEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The past three decades have seen a growing interest in improving the quality of U.S. public education, especially related to increasing the high school graduation rate. Despite the attention, the most recent national data show limited gains over the past quarter of a century. Although more than 85% of 19- to 24-year-olds nationally have earned a high school diploma or its equivalent (U.S. Department of Commerce [USDOC], 2000), approximately 5 of every 100 students over the age of 16 who were enrolled in high school in any of the past 10 years dropped out prior to completing a high school program (U.S. Department of Education [USDOE], 1999). Moreover, more than two thirds (67.3 percent) of all dropouts were 16 to 18 years old. Critically, reform efforts have done little to improve the rate at which students graduate from a regular high school program by the typical age of 18 years. And, as we discuss, wide disparities in data collection methods have made it impossible to accurately describe the academic trajectories of students and develop responsive policies based meaningful data. As a guiding metaphor for the present study, therefore, we imagined a busload of students bound for graduation. What we wanted to know was how many of the students who were expected to get the bus (i.e., those eighth graders who were presently enrolled in the school district and assigned to enroll in the high school in the fall) actually got the bus (i.e., enrolled) and then how many of these students actually got off at graduation 4 years later. Along the way, we hoped to capture an accurate picture of how many of this cohort got off prior to graduation, when and why they got off, and where they went once they got off the bus (i.e., withdrew, transferred, or were retained in grade). In addition, we were interested in identifying when and how many students got the bus along the way, either as transfers from other schools or as members of the cohort returning to the school. THE HIGH COST OF DROPPING OUT Recognizing that a 12-year curriculum is the norm for virtually every U.S. public school today, the failure to receive a high school diploma on time places millions of young Americans at risk each year. Unable to meet the minimum requirement for advanced education or entry into the workforce, dropouts experience higher unemployment rates and lower earnings than other workers (Coley, 1995; Sherraden, 1986; USDOE, 1999). Among males age 25-34, for example, the 1998 employment rate was 87% for those who received a high school diploma or were granted a General Education Diploma (GED) versus 78.5% among those who dropped out (USDOE, 2000a). Although in 1998, females were slightly more likely than males to have completed high school by age 24 (87.1% versus 84.6%; USDOE, 1999), females with a high school diploma or GED were employed far more often than those who had dropped out of school (69.5% versus 47.3%, respectively; USDOE, 1999). Significantly, failing to complete high school presents several major social consequences that include (a) forgone national income, (b) forgone tax revenues for the support of government services, (c) increased demand for social services, (d) increased crime and antisocial behavior, (e) reduced political participation, (f) reduced intergenerational mobility, and (g) poorer levels of health (Coley; Jaffe, 1998; Rumberger, 1987; Tidwell, 1988; USDOE, 1999). As the demographic face of America changes, it is instructive to view the dropout statistics by race and socioeconomic status. National statistics by race show that Hispanic students (7.8%) were more likely than Black (6.5%), White (4.0%), and Asian (5.0%) students to leave school prior to graduation (USDOE, 2000a). In addition, more young adults living in low-income families (11.0%) dropped out versus middle (5.0%) and high-income (2.1%) families (USDOE, 1999). These disparities highlight the fact that the dropout problem is most concentrated in large urban areas where poor and minority students tend to live (Coley, 1995). …

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,458
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,000
Communication savante0,0000,001
Science ouverte0,0020,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,206
Tête enseignante GPT0,455
Écart entre enseignants0,249 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle