Examining physiological and self‐report indicators of empathy during learners’ interaction with a queer history app
Notice bibliographique
Résumé
Abstract Mobile apps take advantage of the ubiquity of mobile phones and can be used to share unique pedagogical experiences with multimedia content not yet available in curriculums. This preliminary study used a quasi‐experimental pretest‐posttest design to examine changes in self‐reported empathy toward sexual orientation and gender identity (SOGI) minority people. We also report on the associations between gender and a physiological measure of emotional activation, skin conductance level (SCL), on self‐reported empathy. The main results of this study that examined 57 undergraduate students at a Canadian University whom interacted with a queer history app individually were the following: Preliminary evidence that (1) students’ empathy toward SO and GI minorities can be measured using a modified version of the Scale of Ethnocultural Empathy (SEE). (2) Statistically significant increases in empathy toward SO and GI minorities pre to post app interaction. (3) Students’ pre‐ and post‐empathy levels were statistically significantly higher toward SO than GI minorities. (4) Female students had statistically significantly higher self‐reported empathy toward SO and GI minorities than males. (5) Male students had statistically significantly higher SCL than females. (6) Statistically significant interaction between SCL grouping and questionnaire administration on GI minority empathy. Findings and implications are discussed in lieu of the contributions that mobile apps can play to support social change, in particular, by fostering empathy. Practitioner Notes What is already known about this topic Evidence that mobile apps are effective learning tools. Evidence that mobile apps are emotionally engaging. Evidence that education can help dispel ignorance, known to contribute to homophobia and transphobia and promote empathy. Empathy has an emotional component. Empathy can be measured as a general trait or toward specific groups. Queer history is excluded from many formal educational curriculums. What this paper adds Preliminary evidence that a self‐report tool can be used to measure empathy toward both sexual orientation (SO) and gender identity (GI) minorities. Preliminary evidence that undergraduate students’ empathy toward SO and GI minorities increased after interacting with the Edmonton Queer History (EQH) app. Preliminary evidence that students’ empathy toward SO was statistically significantly higher than it was toward GI minorities at both pre and post tests. Preliminary evidence that female students had statistically significantly higher self‐reported empathy toward SO and GI minorities than males. Preliminary evidence that male students had statistically significantly higher skin conductance levels (SCL) than females. Preliminary evidence of a statistically significant interaction between SCL grouping and questionnaire administration on GI minority empathy. Implications for practice and/or policy Mobile apps can be used to teach students about queer history and these interactions may lead to increases in empathy. Educators can supplement their curriculum with educational technologies, such as mobile apps, to fill important gaps. Educators should consider gender differences in teaching topics that may or are intended to inspire empathy. Educators should not assume that empathy toward SO and GI minorities are the same.
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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 | 0,001 | 0,004 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».