Metacognitive strategies in secondary science education
Notice bibliographique
Résumé
Students often struggle to meaningfully reflect on their conceptual understandings, establish well-defined learning goals, and employ strategies that effectively bridge learning gaps. The benefits of metacognitive strategies in the science curriculum to enhance student self-awareness is well-documented in the research literature. Metacognition refers to one's considerations for their own thinking and learning. Metacognitive strategies can be subdivided into three categories: planning, monitoring, and evaluation. Planning strategies are utilized prior to a task or unit to encourage goal setting, establish prior knowledge, and identify learning objectives. Monitoring strategies aid students in actively gauging their learning progress. Evaluation strategies nurture student reflection on learning success and assessment preparation techniques. The effectiveness of planning, monitoring, and evaluation metacognitive strategies on assessment performance and perceived learning was investigated within an Alberta Biology 20 class of 19 students. The project time frame was subdivided into five, approximately two-week sessions, and the first session represented a non-treatment stage. Students implemented planning, monitoring, evaluation, and combined strategies for the subsequent four treatment sessions. At the conclusion of each session, students were summatively assessed on their recent content knowledge. Box and Whisker Plots were generated for a visual comparison of the assessment score distributions. A Friedman Two-Way Analysis of Variance by Ranks and a Post-hoc test examined significance between assessment scores for the five sessions. Assessment score ranks sums were statistically significant between the no treatment sample and treatments 2, 3, and 4 respectively, suggesting that metacognitive strategies may contribute to an increase in assessment performance. Likert-style surveys with accompanying open-ended questions were provided to participants at the conclusion of each treatment. The anonymous surveys required students to compare strategy effectiveness between and within treatments, to consider how likely they were to independently use metacognitive strategies in future classes, and to express their interest in learning additional strategies for a particular type. Survey data supported the claim that the incorporation of metacognitive strategies within the curriculum improved the perception of learning. Most students retained a favorable opinion of metacognition strategies throughout the study, and believed the strategies were effective at fostering the development of conceptual understandings.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,195 | 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 ».