Contested Subjectivities: Loving, Hating, and Learning Mathematics
Notice bibliographique
Résumé
This dissertation is a currere study of how five students and their teacher understand their mathematical learning inside a Grade 10 classroom in Quebec. More closely, this research examines how recollections of past, present, and future mathematizing are tied to one’s sense of identity. Through analysing the entries in a teacher journal and the autobiographical stories of former students, identifications with and against common tropes of what it means to be “good” at mathematics were examined. This dissertation thus asks, how do participants in mathematics teaching and learning read their experiences, and why does a study like this matter to the future of the subject or to education overall? Using the autobiographical Curriculum Studies method of currere, a psychoanalytic stylistic analysis, and a cultural studies component whereby participants were encouraged to respond to the characters in the popular sitcom The Big Bang Theory, responses were gathered through individual interviews. Insights were derived from psychoanalytic readings of both transference and countertransference taking place in the learning space and beyond. The researcher’s and participants’ responses were understood through the ways in which the teacher’s emotional world is transferred onto the act of teaching and how, reciprocally, the teacher is addressed through feelings, phantasies, defences, and anxieties. The former students were interviewed with the stages of currere in mind in order to elicit free associative responses that lent insight to the regressive, progressive, and analytic stages. The final, synthetical, stage of currere took place to unpack my identificatory work as a researcher and teacher in the mathematics classroom. The methodological considerations in this dissertation included outlining the significance of repetitions of language in interviewees’ responses, both individually and collectively. Participants’ responses began to indicate a complex emotional world whereby their categorization in a “lower” mathematics course in high school nevertheless did not trap their identities into common tropes of of negativity, difficulty, and anxiety. Rather, the types of language and frequency of word use signal how the emotional landscape of students’ mathematical lives is shaped by how students perceive teachers to see them as mathematical or not. This research reveals how mathematics concepts, but more often, pedagogical dynamics, lead to complicated psychological terrain traversed by both teachers and students. I argue that using currere as a methodology readily employable with high school students helps to uncover the complex worlds of mathematical identity formation including the role of societal stereotypes. Furthermore, if educators understand their own dynamics of love and hate in relation to mathematical competence, performance, and pedagogy, they might better foster mutuality between students and teachers overall.
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Comment cette classification a été obtenuedéplier
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 | 0,004 | 0,002 |
| 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 | 0,003 | 0,001 |
| Communication savante | 0,000 | 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) | 0,001 | 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 tête enseignante, 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 ».