Strategies for Creating Engagement in Civil Engineering Students in Lecture Scenarios
Notice bibliographique
Résumé
Abstract Strategies for Creating Engagement in Civil Engineering Students in LectureScenariosTeaching a required engineering communication course to sophomore civil engineers, especially in alarge classroom lecture setting, presents some significant challenges. Students in general face anumber of roadblocks to engagement in lecture settings, including lecture/PowerPoint fatigue,physical fatigue from their demanding workloads, and the distraction of other often more pressingcourse commitments (such as upcoming exams or assignments). These challenges are exacerbatedwhen the subject being taught is not particularly conducive to lecture-style teaching or perceived asrelevant to their disciplinary knowledge base, such as engineering communication. In such scenarios,strategies for creating engagement at the beginning of lectures are crucial to gaining and maintainingstudent attention, and creating the student buy-in that is key to their learning.The discipline of civil engineering, however, is unique from other engineering disciplines inpresenting numerous opportunities for engagement with cultural touchstones relevant to students ofall levels. The general population engages daily with the products of civil engineering by usinginfrastructure, such as roads, buildings, and water systems. Our connection to these artifacts of civilengineering are reflected in products such as popular music, film, and other media which holdcultural currency with students. This presentation explores strategies that take advantage of thisstrong connection between civil engineering and culture to create engagement for civil engineeringstudents in lecture settingsWe examine three strategies developed and piloted during a single semester course on EngineeringCommunication in Civil Engineering. In this presentation, we will first play “Civil EngineeringThemed Musical Trivia,” in which students compete within the lecture classroom to identify the titleand artist for songs with either a titular or lyrical connection to civil engineering. Songs range fromthe highly contemporary - such as Miley Cyrus’ Wrecking Ball and Demi Levato’s Skyscraper - to olderclassics - such as Simon and Garfunkel’s Bridge Over Troubled Water or Joni Mitchell’s Big Yellow Taxi.Second, we examine how both new and old multimedia, such as A Short History of the High-rise — acollaboration between the New York Times and the National Film Board of Canada — or films byEdward Burtynsky, such as Manufactured Landscapes and Watermark, can be introduced prior to lectureto get students thinking about important engineering concepts such as sustainability. Finally, weexplore how local, municipal political issues – such as the highly transportation focused [cityredacted] mayoral race - can be used (in a non-partisan way) to demonstrate the significance of theirchosen discipline to their daily lives.All of these strategies, which take 2-5 minutes at the beginning of the lecture, encourage students tofocus their attention and engage with the material being presented, with the hope that this attentionwill be carried over to the lecture material. During the presentation, these strategies will bedemonstrated to the audience, and their impact on student engagement over the course of a classdiscussed, using data from student evaluations, student-instructor interactions, and lectureexperience.
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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 | 0,006 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,004 | 0,010 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,005 |
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 ».