Learning from the experts: Evaluating a participatory autism and universal design training for university educators
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Notice bibliographique
Résumé
Autistic students experience strengths and challenges that can impact their full inclusion in higher education, including stigma. A participatory team of autistic and non-autistic scholars developed an autism and universal design (UD) training. This participatory approach centered the voices of autistic collaborators in training design and evaluation. Ninety-eight educators from 53 institutions across five countries completed assessments before training (pre-tests), 89 completed post-tests (after training), and 82 completed maintenance assessments (a month after post-test). Pre-test autism stigma was heightened among males, educators with less autism knowledge, and those who reported heightened social dominance orientation. Autism knowledge, autism stigma, and attitudes toward UD improved with training. Improvements remained apparent a month after post-test but were somewhat attenuated for knowledge and stigma. To the best of our knowledge, this is the first evidence of maintenance of benefits of an autism training over time. Participants’ main reason for enrolling in the study was to gain a better understanding about neurodiversity. Feedback indicates that this goal was reached by most with the added benefit of gaining understanding about UD. Results suggest that interest in one type of diversity (e.g. autism) can motivate faculty to learn UD-aligned teaching strategies that benefit diverse students more generally. Lay abstract Autistic university students have many strengths. They also go through difficulties that professors may not understand. Professors may not understand what college life is like for autistic students. They might judge autistic students. A team of autistic and non-autistic researchers made a training to help professors understand autistic students better. This training also gave professors ideas to help them teach all of their students. Ninety-eight professors did an online survey before the autism training. They shared how they felt about autism and teaching. Before our training, professors who knew more about autism appreciated autism more. Professors who thought people should be equal and women also appreciated autism more. Then, 89 of the professors did our training and another survey after the training. This helped us see what they learned from the training. They did one more survey a month later. This helped us see what they remembered. Our training helped professors understand and value autism. It also helped them understand how they can teach all students better. The professors remembered a lot of what we taught them. This study shows that a training that autistic people helped make can help professors understand their autistic students better.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle