MétaCan
Menu
Retour à la cohorte
Enregistrement W348634200

Coaching a High School Science Olympiad Team.

2003· article· en· W348634200 sur OpenAlexaboutno aff
Scott E. Robinson

Notice bibliographique

RevueAcademic exchange quarterly · 2003
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueDiverse Educational Innovations Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOlympiadMathematics educationTournamentCoachingCompetition (biology)PsychologyScience educationMedical educationPedagogyMathematicsMedicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Abstract Each year thousands of high school serve as Science Olympiad coaches. These teacher-coaches mentor and assist students who compete in biology, chemistry, earth science, physics, and technology events at this extra curricular academic competition. Why do serve as coaches? What are their rewards and challenges? What levels of competition and cooperation exist among students engaging in this endeavor? What is the relationship of coaching a Science Olympiad team and teaching high school science? Nine who served as coaches at a regional high school Science Olympiad in 2002 were interviewed to answer these questions. Their insights are reported here. ********** The Science Olympiad [SCIO] is international nonprofit organization devoted to improving the quality of education by generating student interest in and providing recognition for outstanding achievement in education by both students and teachers (Putz, 2002, p. CC1). According to Gerald Putz, SCIO National Director, roughly 13,500 elementary and secondary teams involving 200,000 individuals from all 50 states and Canada take part in this extra curricular academic competition each year. In New York alone, 275 high school teams with 550 high school teacher-coaches and 4000 students (grades 9-12) participated in 2002. Of this total, 25 teams involving 50 teacher-coaches and 375 high school students, with nearly equal numbers of girls and boys, took part in the regional tournament in Rochester, New York, on a Saturday in February of that year. On the day of the tournament, students in groups of two or three per school competed against their peers from other schools in 18 and engineering events. The events required students to apply their scientific content knowledge and laboratory skills during 50-minute sessions addressing such topics as bird identification, chemistry laboratory investigation, topographical map reading, and physics experimentation. They also used their engineering and technical know-how in constructing remote controlled robots, balsa wood boomilevers, catapults, energy transfer devices, and musical instruments based on precise design specifications and performance criteria. Students who finished in the first three places for each event received gold, silver, and bronze medals to recognize their accomplishments. All participants in each event earned points for their teams based on their results. The top finishing teams received trophies as well as invitations to the state level high school SCIO to compete against other regional qualifiers in March. The top two teams from the state tournament participated in the national SCIO in May. The SCIO evolved out of a concern over dwindling enrollments both in high school and college and waning student interest in fairs (Macbeth, 1977, p. 22). A SCIO and a fair are similar in that they are extracurricular competitions. They differ in that the SCIO involves collaborative group competitions on a variety of and technology events whereas a fair tends to be an individual scientific research project on a particular problem (Jones, 1991). There has been a belief among many secondary and post secondary and teacher educators that the SCIO generates student interest in (Cairns, 1984; Fletcher, 1981; McGee-Brown, Martin, Monsaas, & Stombler, 2002; Wilson, 1981). The authors of the National Science Education Standards (NRC, 1996) wrote that the SCIO enhanced scientific literacy as students display their understanding and ability in science (p. 39). In light of this published support, what can be learned about who served as coaches at a regional tournament? Goals and Methods The goal of this study was to investigate the nature of coaching a high school SCIO team. What were the beliefs and needs of high school who served as coaches? …

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 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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,482
Score d'incertitude au seuil0,846

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,271
Écart entre enseignants0,240 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2003
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueAcademic exchange quarterlyMême sujetDiverse Educational Innovations StudiesTravaux en français237 207