180: Preparing to Interact with the Legal System: It's Child's Play!
Notice bibliographique
Résumé
Child maltreatment (CM) is a widespread problem in children and youth. Pediatricians and health professionals involved may be required to interact with child welfare authorities and the court system; arenas in which they may be unfamiliar. Professionals often have little experience in reporting suspected CM and frequently don't feel prepared to provide court testimony. Even for those specializing in CM, stress surrounding court appearances is reported. Exposure to and familiarity with this element of practice could increase comfort and competence. Games are an established and effective teaching method. However, evidence for game-based learning among health professionals is limited. To assess the satisfaction with and perceived learning from a game-based tool designed to assist with preparation for court. A board game with content developed by an expert CM group was created. Game content, in the form of questions and tasks, reflected knowledge and skills required by the court system. Attendees at a session on ‘preparing for court’ at a national Child Maltreatment Symposium played the game for one hour. An anonymous post-session survey was completed to assess participants' satisfaction and perceived learning. Responses to questions on a 5-point Likert scale were coded and analyzed using descriptive statistics. Qualitative comments were analyzed and grouped by emerging themes. Forty-three of the 58 players completed a survey yielding a response rate of 74%. Thirty-four respondents (79%) self-identified as a pediatrician or Child Abuse pediatrician, 9% (n=4) were trainees and 12% (n=5) were allied health practitioners. Over half of the respondents were between the ages of 25–45 (n=22). The mean number of years in practice was 19 (range 2–46). Respondents most often “agreed” that the game was: useful for learning (88%), helped link knowledge to practice (56%) and met their educational needs (68%). The vast majority of respondents “agreed” or “strongly agreed” (70%) they would participate in a similar session in the future. When asked to compare the game experience to prior educational sessions about court, respondents most often “agreed” or “strongly agreed” (81%) that the game held their attention better. Qualitative feedback, in the form of exemplar quotes also supported respondents' satisfaction with the game as a learning tool. These results suggest that game-based learning is an effective and positively accepted method of learning about court. Similar game based interactive sessions may be useful for education in other areas with limited preparation options and opportunities for practical experience.
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 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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,009 |
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 ».