Argumentação e design: Cognição, afetividade e moralidade em comunidades universitárias de aprendizagem
Bibliographic record
Abstract
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. Palavras-chave: Argumentação em rede. Comunidades de aprendizagem. Fóruns de discussão. Educação universitária. Co-construção dos conhecimentos. Argumentation and design: cognition, affectivity and morality in learning community in higher education Abstract 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. Key words: Networked argumentation. Learning communities. Electronic forums. Higher education. Knowledge co-construction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.028 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".