After-School Computer Clubhouses and At-Risk Teens.
Notice bibliographique
Résumé
ABSTRACT KLICK! (Kids Learning In Computer Clubhouses!), a federally funded, afterschool, computer clubhouse operating in Michigan, is investigated as a means for supporting positive, engaging, and innovative after school activities for teens. A quasi-experimental, pre-test/post-test survey suggests that participating in KLICK! is differentially effective for teens with initially low value for school and low GPA on outcomes of school value and technology expertise. Implications for this finding on similar after school programs are discussed. Our nation's teens have garnered much recent attention (Head, 1997; Hellmich, 2002; NBC, 2002). Because of violence, drug and alcohol abuse, dropout rates, suicide, and gang activity our most prized commodity is in jeopardy. Research suggests that our teens are struggling in a culture designed to inspire risk-taking (Ponton, 1997), violence (Canada, 1995, 1998), self-abuse (Pipher, 1994); and even cold-heartedness (Kindlon & Thompson, 2000). Our teens are distant (Hersch, 1998) yet looking for a positive outlet for an unbelievable amount of energy and enthusiasm (Schneider & Stevenson, 1999). Recognizing this, the U.S. Department of Education has supported a strong initiative to open after school programs for teens across the country. After school programs continue to be funded by the U.S. Department of Education (U.S.D.E.) at an incredible rate. In the last several years the U.S.D.E. has provided almost 250 million dollars to establish after school programs in rural and inner city schools. Research continues to demonstrate that students in high quality after school programs are more successful academically and socially than non-participating peers, are more likely to develop healthy self-perceptions and attitudes, and are better able to resist unsafe behaviors such as drug and alcohol use, gang affiliation, and other criminal activities, (U.S. Department of Education, 1998). The block of unsupervised time, between the release of school and the return of parents from work, has led many adolescents to destructive and often criminal behavior. Statistics from the Federal Bureau of Investigation (FBI) show between the ages of 12 and 17 are most at risk of committing violent acts and victimization between 3 p.m. and 6 p.m. - a time when they are not in school at the end of the regular school day (U.S. Department of Education, 1998). In addition to providing needed supervision and guidance, after school programs designed to further engage and enrich students' educational experiences seem to be most successful. Because student participation is voluntary, successful programs usually afford a great deal of choice to their participants. Students are often allowed to decide what activities to choose, when to choose a different activity, and to engage in whatever form and to whatever degree they choose. Most successful programs offer activities and resources that adolescents are not likely to find in other places such as a library, a youth sports center, or their own home. After school programs that provide access to high technology resources seem to be particularly valuable and compelling to teens (Blumenfeld, Soloway, Marx, Krajcik, Guzdial, & Palincsar, 9 1999 1; Kafai, 1996; Papert, 1991). For example, in the 5th Dimensions program originally developed in the Eaboratory of Comparative Human Cognition (LCHC) at the University of California at San Diego, participating teens chose what path to follow through a 'maze' of different activities and challenges. Teens chose which route to take, which activities to attempt, and how to begin completing those activities. Children in the 5th Dimensions program also use a full complement of computer technologies in the form of games, puzzles, and other challenging activities unfamiliar to them (Cole, 1996). At another successful after school program developed at the Media Lab at the Massachusetts Institute of Technology in Boston, teens were free to become creative and productive users of technology for the purposes of designing and expressing themselves artistically. …
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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 | 0,000 | 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) | 0,002 | 0,001 |
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.
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».