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Enregistrement W272138261 · doi:10.5935/reeduc.v8i17.172

Argumentação e design: Cognição, afetividade e moralidade em comunidades universitárias de aprendizagem

2011· article· pt· W272138261 sur OpenAlexaff
Milton Campos, Cristina Grabovschi

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2011
Typearticle
Languept
DomaineSocial Sciences
ThématiqueEducation and Digital Technologies
Établissements canadiensUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésHumanitiesPhilosophy

Résumé

récupéré en direct d'OpenAlex

<p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><span style="mso-ansi-language: PT-BR;"><span style="font-size: small;"><span style="font-family: Times New Roman;">Esse estudo tem dois objetivos principais: ilustrar práticas pedagógicas de utilização de fóruns de discussão no ensino universitário e um método de análise da argumentação em rede. Estudamos, paralelamente, elementos cognitivos (as razões que fundamentam os argumentos), afetivos (o “clima” no qual se desenrolaram as conversas em rede) e morais (as evidências de respeito). Essas dimensões foram costuradas juntas à luz do processo de co-construção de conhecimentos. Categorizamos então, metodologicamente, as diversas comunidades universitárias de aprendizagem estudadas de modo a determinar os níveis prevalentes das trocas. Essa perspectiva está fundamentada na hipótese segundo a qual a co-construção de conhecimentos que se estabelece nas trocas argumentativas em rede não pode ser compreendida sem que consideremos a afetividade dos participantes, como as emoções, assim como sentimentos morais. Nesse sentido, estudamos transcrições de conversações em rede de seis comunidades universitárias de aprendizagem, provindo de disciplinas diferentes. Muito embora nossa metodologia seja fundamentada na análise argumentativa, integramos instrumentos quantitativos e qualitativos com o objetivo de ampliá-la. Os resultados relacionados à dimensão argumentativa (procedimentos lógicos), confirmaram estudos prévios sobre a co-construção de conhecimentos em rede. No entanto, os resultados provindos das dimensões afetivas e morais exploradas se mostraram menos claros. O que é certo, no entanto, é que os processos argumentativos dos cursos estudados nos permitem dizer que conversações em rede significativas não emergem por si mesmas. O contexto da aprendizagem, o planejamento e as ações do professor são fundamentais para o sucesso da estratégia pedagógica.</span></span></span> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><span style="font-size: small;"><span style="font-family: Times New Roman;"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: PT-BR;">Palavras-chave: </span></strong><span style="mso-ansi-language: PT-BR;">Argumentação em rede. Comunidades de aprendizagem. Fóruns de discussão. Educação universitária. Co-construção dos conhecimentos.</span></span></span> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: PT-BR;"><span style="font-size: small; font-family: Times New Roman;"> </span></span></strong> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: center;" align="center"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: EN-US;" lang="EN-US"><span style="font-size: small; font-family: Times New Roman;"> </span></span></strong> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: center;" align="center"><strong style="mso-bidi-font-weight: normal;"><span style="font-size: 14pt; mso-ansi-language: EN-US;" lang="EN-US"><span style="font-family: Times New Roman;">Argumentation and design: cognition, affectivity and morality in learning<span style="mso-spacerun: yes;"> </span>community in<span style="mso-spacerun: yes;"> </span>higher education</span></span></strong> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: PT-BR;"><span style="font-size: small; font-family: Times New Roman;"> </span></span></strong> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: EN-CA;" lang="EN-CA"><span style="font-size: small;"><span style="font-family: Times New Roman;">Abstract</span></span></span></strong> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><span style="mso-ansi-language: EN-US;" lang="EN-US"><span style="font-size: small;"><span style="font-family: Times New Roman;">This study has two main goals: to highlight pedagogical practices in the use of electronic forums in higher education, and a method to analyze networked argumentation. On the one hand, we studied the cognitive (the reasons that found arguments), affective (the “climate” in which networked conversations were developed) and moral dimensions (evidences of the occurrence of respect). They were weaved in knowledge co-construction processes. On the other, we categorized methodologically a number of higher education learning communities so as to determine what was prevalent in networked exchanges. This approach is based on the hypothesis that knowledge co-construction that happens in networked argumentation exchanges cannot be understood without taking into account the affectivity of participants, such as their emotions and moral feelings. For that, we studied transcripts of networked conversations coming from six higher education learning communities that emerged in courses in which different disciplines were taught. Although our method is based on argumentation analysis, we integrated qualitative and quantitative tools with the goal to enhance it. Results related to the argumentative dimension (logical procedures), confirmed previous studies on networked knowledge co-construction. However, results related to the affective and moral dimensions were far less clear. It can be stated, though, that the argumentation processes identified in the studied courses show that meaningful networked conversations do not emerge by themselves. The learning context, the design and the instructors’ actions are equally fundamental for successful pedagogical strategies.</span></span></span> <p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-align: justify;"><span style="font-size: small;"><span style="font-family: Times New Roman;"><strong style="mso-bidi-font-weight: normal;"><span style="mso-ansi-language: EN-CA;" lang="EN-CA">Key words: </span></strong><span style="mso-ansi-language: EN-US;" lang="EN-US">Networked argumentation. Learning communities. Electronic forums. Higher education. Knowledge co-construction.</span></span></span>

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)0,003
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante, Science ouverte, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,294
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,001
Communication savante0,0040,006
Science ouverte0,0070,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0280,000

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 Opus0,599
Tête enseignante GPT0,583
Écart entre enseignants0,017 · 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.

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

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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