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Wondering + Online Inquiry = Learning: Online Information Sources Can Form the Basis of Effective Inquiry-Based Learning If Teachers Construct Assignments to Promote Collaboration, Communication, and More Inquiry

2014· article· en· W878835034 sur OpenAlexaboutno aff
Diane Carver Sekeres, Julie Coiro, Jill Castek, Lizabeth A. Guzniczak

Notice bibliographique

RevuePhi Delta Kappan · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEducation and Critical Thinking Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMeaning (existential)Construct (python library)Mathematics educationContext (archaeology)NegotiationReading (process)PedagogyInquiry-based learningPsychologyComputer scienceSociology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Learning what happens as elementary school children read and make meaning of the text and images they see fascinating, especially when the reading done in the context of children's interactions with each other and with online information. But such online inquiry tends to happen with students sitting closely together at a computer or a tablet, when all you can see the backs of their heads. So how do we know the time they're spending in inquiry productive? What influence does a project's design have on children's work? Is the chatter that we hear helpful for their thinking and learning? We have found carefully structured tasks that scaffold the ability to question, navigate, and negotiate the meaning of online text, and we have discovered that images can foster collaborations that are engaging, deeply comprehensive, and fruitful (Coiro et al., 2014). Inquiry-based learning engages students in collecting information, analyzing data, and crafting presentations that create solutions or make arguments. Students be come more positive and independent in their learning while gaining new knowledge and meaningful understandings of their world. Yet designing assignments that scaffold inquiry often necessary to support students' efforts. Structured inquiry experiences can help learners develop skills for coping with problems that have no clear solutions, dealing with challenges, and adapting procedures to the demands of different situations (Alberta Learning, 2004). Our research findings reinforce what others have suggested--that while students follow general patterns in thinking and collaboration, the inquiry is not linear or lock step. It highly individual, nonlinear, flexible, and more recursive than might be suggested in traditional models of the research process (Alberta Learning, 2004, p. 9). Thus, depending on the purposes of inquiry and the abilities of students, there are different ways to frame inquiries to support student success. Alberta's model of inquiry-based learning delineates four gradually less restrictive frameworks designed to encourage students' wondering with authentic inquiry tasks (see Figure 1). We found that the design of a structured online inquiry supports children's success in grades 3-5. We also uncovered certain patterns in how children read and talk about their work that enable them to be productive during various phases of the inquiry process. Designing online inquiry An authentic inquiry task connects students to relevant, real-world concepts and events. Thus, we based the inquiry task for our study of students in grades 3-5 on some of the curriculum topics their teachers covered. Our study took place in an International Baccalaureate school that used the environment and economics, among other themes, to shape its curricula. We presented the following scenario to the students: A new Green Toys Shop will open in our town. You have been asked to recommend several toys for the shop that would be eco-friendly and would appeal to children. Use the Internet to learn more about eco-friendly materials and to search for eco-friendly toys. Then, send an email to the Green Toys Shop owner that includes three recommended toys and the reasons that you chose them. We structured the inquiry by asking students to find particular answers to our teacher-directed scenario and to move through the given materials by working in pairs. We asked students to read an informational overview web page we created with embedded hyperlinks to increase their knowledge of environmentally friendly materials so that they could think about why a toy was eco-friendly. Some students chose to read deeply, visiting and discussing every link and generating additional questions to explore. Others read the words aloud to their partner, choosing not to follow any of the hyperlinks, and went on to search for toys without discussion or additional exploration. …

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut 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: aucune
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil0,087

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0050,007
Science ouverte0,0010,005
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0260,010

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 Opus0,029
Tête enseignante GPT0,337
Écart entre enseignants0,308 · 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 source (Gemma direct ou Codex distillé), 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

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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