A Study of Lower-order and Higher-order Questions at Secondary Level
Notice bibliographique
Résumé
In classrooms, questioning is one of the most regularly employed teaching strategies. Questioning is considered by many to be the most important tool that teachers have for helping students build understanding and to encourage students to think about and act upon the material that have structured. Questions are asked to individual pupils, to the whole class, to small groups to arouse curiosity, focus attention, develop an active approach, stimulate pupils, structure the task, diagnose difficulties, communicate expectation, help children reflect, develop thinking skills, help group reflection, provoke discussion and show interest in pupils’ ideas. Perhaps few studies have been carried out regarding the levels of classroom questions in Pakistan on this vital aspect of teaching learning process. The main objective of the study was to explore the levels of questions teachers asked during teaching at secondary level using bloom’s taxonomy. It was focused to observe the ratio of lower and higher- order questions. It was an observational study of the descriptive method. The target population comprised all the teachers of Working Folks Grammar School & College Peshawar. Twenty teachers of different subjects teaching at secondary level were randomly selected as sample of the study. Teachers were observed using an observational guide and audio recording were conducted. The researcher focused only the asked questions of the teachers. This study is significant because its findings and conclusions may stimulate teachers to improve their questioning behavior in order to develop and promote higher order thinking abilities. The result of the study showed that so much time was spent with teachers questioning the students. Most of the questions were low- level cognitive questions. Higher- order questions were also observed however, the ratio of these questions was very low. Total percentage of questions during 445 minutes was 60 percent. The whole number of questions was good but in most of the classes the number of questions was low. Among 267 questions 67 percent were knowledge based, 23 percent were comprehension based, 7 percent were application based, 2 percent were analysis based and 1 percent was synthesis based. However the ratio of evaluation based questions was zero.
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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 | 0,009 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».