The Effect of Teaching Methodology and Course Duration on Student Performance at Different Assessment Types across Different Cognitive Levels as defined by Bloom’s Taxonomy
Notice bibliographique
Résumé
The University of Western Ontario currently offers a third year systemic human anatomy course (ANATCELL 3319) in face to face (F2F) and online sections during the fall/winter intake (F/W). While F/W sections share the same lecture and assessment materials, F2F students attend weekly one‐hour cadaveric labs while online students attend weekly interactive video conference labs. During the summer intake, the course is offered in the online section only, with labs given twice a week. The assessments consist of multichoice (MCQ) and short answer questions. Our previous publication showed that F/W F2F scored higher in their MCQ assessments than F/W online students at different Bloom’s Taxonomy levels. In addition, F/W online students scored higher than summer online students in the shared MCQ. In the current study, we further compared the performance of students in MCQ against their performance in short answer questions, in total and at different Bloom’s Taxonomy levels within/against the assessment type(s). For F/W sections (F2F students n=142; online students n=172), there were 300 MCQ (knowledge (n= 149), comprehension (n= 120), application (n= 21), and analysis (n= 10)) and 118 short answer questions (knowledge (n= 88), comprehension (n= 18.5), application (n= 10.5), and analysis (n= 1)). Both groups scored higher in their MCQ than short answer questions, in total and at most cognitive levels (p ≤ 0.05). F/W F2F students scored higher than F/W online in both assessment types and at most levels. The variance across levels differed based on the assessment type. For example, All F/W students scored the highest in comprehension MCQ but the lowest in short answer comprehension questions. This indicates that a change of assessment type influences the way in which students answer. With summer online students (n=44), we compared 169 MCQ (knowledge (n=79), comprehension (n=74), application (n=9) and analysis (n=7)) with 59 short answer questions (knowledge (n= 34), comprehension (n=12), application (10) and analysis (n=3)). Students scored higher (p ≤ 0.05) in their MCQ total, comprehension MCQ, and application MCQ than the adjacent levels of the short answers. Unlike their F/W counterparts, students scored lowest in their MCQ comprehension (p<0.001) in relation to the other levels. Our findings indicate that teaching F2F is likely to improve student performance in terms of both overall grades and cognitive ability. In addition, students are likely to score higher in MCQ than short answer questions which is indicative of a reliance on cues within MCQ (especially comprehension) to help them overcome their lack of information. Finally, the performance of summer students, particularly in relation to comprehension‐type questions which rely on memorisation, indicates that the spacing of course material may help in achieving higher grades. Support or Funding Information Dr. Kem Roger
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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 | 0,008 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».