Inquiry-Based Learning in Experimental Sessions: Strategies towards conducting more effective Experimental Laboratory Sessions with Engineering Undergraduate Students
Notice bibliographique
Résumé
Experimental sessions in the Laboratory are usually preceded by instructional sessions where student participants are taught about the activities they will be doing in the laboratory. Despite this activity, many times students approach the actual experimentation in the laboratory as mere routine with an expected result. Hence, they are not mentally engaged rather expecting to follow strict procedures as written in the book (manual) and deliver as expected by the book. This is a hindrance to actual learning. This seminar considers an inquiry-based learning approach as a teaching technique for pre-laboratory sessions by Graduate Teaching Assistants which will help engage the undergraduate students more in laboratory activities for productive learning.\nThis presentation is aimed at the Graduate Teaching Assistant (herein referred to as GTA) whose duty usually include preparing students for experimental sessions in the laboratory such as is obtained in MME 2285 (Experimental Methods), a course in Westernâs Department of Mechanical and Materials Engineering.\nFor a GTA in this course and similar courses in Engineering, the Professor expects the GTA to hold instructional (taught) sessions with the students ahead of the Laboratory session where he teaches them rudiments of the laboratory experiment and issues pertaining to the laboratory which the students might not grasp in the lecture room typically taught by the Professor. Usually, the lecture room by the professor follow the traditional teaching methods and some students when not able to understand what was taught assume they will understand once they undertake the experiment in the laboratory. However, this is not always the case, so it is important they understand it before actual experimentation commenced. For the GTA through whom students have a second chance at learning from the experimentation, it is usually better to adopt a different teaching method from that which the student earlier encountered in the lecture room. The proposed teaching method is Inquiry-Based learning (herein referred to as IBL) which deviates from the traditional method and engage the student more thereby helping them to understand while complementing what they had been taught as it engages their reasoning. Where students already understood the pre-laboratory sessions in the lecture room with the professor, further teaching through IBL by the GTA will help to engage the student more and help students to mentally adjudge the work they do in the laboratory during the actual experimentation. Ditto, in cases where student erroneously think they understood the first lecture, the IBL session with the GTA can help correct misconceptions and thus avoid/understand potential pitfalls during actual experimentations in the laboratory.\nSince IBL is question driven (Queen University Centre for Teaching and Learning), the GTA will be able to assess the level of understanding of students based on the teachings they have had with the professor. This enables the GTA to understand the specific needs of students as he undertakes the teaching session. The GTA could potentially benefit immensely from this teaching method in his capacity as a Graduate experimentalist as ideas deduced from doing IBL with undergraduate students could be a valuable input in the GTA graduate studies and research.
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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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».