Writing as a Minecrafter: Exploring how Children Blur Worlds of Play in the Elementary English Language Arts Classroom
Notice bibliographique
Résumé
Background/Context Educators have considered how Minecraft supports language and literacy practices in the game and in the spaces and circumstances immediately surrounding gameplay. However, it is still necessary to develop additional conceptualizations of how children and youth's online and offline worlds and experiences are blurred by and through the games. In this study, I take up this call and examine how the boundaries of the digital were blurred by one child as he wrote in response to a standardized writing prompt within his urban fourth-grade classroom. Purpose/Objective/Research Question/Focus of Study Through snapshots of Jairo's writing, I illuminate how he muddled the lines between his physical play experiences and those he had in the virtual world of Minecraft. In doing so, I argue that he carried over his personal interest as a fan of Minecraft into the writing curriculum through creative language play. As Jairo “borrowed” his physical play experiences in the virtual world of Minecraft to complete an assigned writing task, he exemplified how children blur playworlds of physical and digital play in the elementary ELA classroom. Research Design Drawing on data generated in an 18-week case study, I examine how one child, Jairo, playfully incorporated his lived experiences in the virtual world of Minecraft into mandated writing tasks. Conclusions/Recommendations My examination of his writing is meant to challenge writing scholars, scholars of play, and those engaged in rethinking media's relation to literacy. I encourage a rethinking of what it means for adults to maintain clear lines of what is digital play and what is not. I suggest adults might have too heavy a hand in bringing play into classrooms. Children already have experiences with play—both physical and digital. We must cultivate a space for children to build on what was previously familiar to them by offering scaffolds to bridge these experiences between what we, as adults, understand as binaries. Children do not necessarily see distinctions between “reality” and play worlds, or between digital and physical play. For children, play worlds and digital worlds are perhaps simply worlds; it is we as adults who harbor a desire for clear boundaries.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,013 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,009 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».