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Enregistrement W3196611878 · doi:10.18260/1-2--38095

WIP: Short Online Films to Help First-Year Students Write Reports as Engineers

2024· article· en· W3196611878 sur OpenAlex
Michael Alley, Kaitlyn Pigeon, Stephanie Cutler

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Notice bibliographique

Revue2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Curriculum Development
Établissements canadiensnon disponible
Organismes subventionnairesNational Science Foundation
Mots-clésComputer scienceMultimediaMathematics educationPsychology

Résumé

récupéré en direct d'OpenAlex

Abstract Because many engineering students do not take a technical writing course until their junior or senior year [1], a gap exists between the essays that students have learned to write in first-year composition and the reports that those students are expected to produce in many undergraduate design courses and laboratory courses. This paper introduces a series of ten online films (3 – 7 minutes each) to help undergraduates write engineering reports [2]. Since the release of this series at the beginning of 2020, these films have received a combined 8500 film views. Created using the NSF approach of I-Corps™ Learning [3], the films have derived their content from one-on-one interviews with more than 100 engineering students and more than 25 engineering faculty. The focus of these interviews was to understand the gap between what undergraduates already knew about writing from first-year composition and what is needed to write an engineering report. Over three semesters, we piloted the films to hundreds of students in first-year seminars and at the beginning of engineering writing courses. From these pilot tests, we gathered information about the film series which we incorporated into the 2020 version. Although a technical writing course in the junior or senior year should bridge the discussed gap, not understanding the differences between general writing and engineering writing poses problems for engineering undergraduates. For instance, not recognizing what first-year design instructors expect in a summary can pull down a report's grade and lead students to assume that they are inherently not good at engineering writing. As Ambrose and others [4] have found, initial failure in performing a skill can lead many students to assume that they are inherently weak at that skill. Another problem is that engineering students who have not bridged the gap between general writing and engineering writing are at a disadvantage when writing reports during a summer internship. This film series on writing reports as an engineer is part of a larger collection on communicating as engineers and scientists. All series are available online to any student or faculty member and readily found through web searches of the terms "engineering writing" or "engineering presentations." Because the series on engineering presentations, which has been available for two years, receives substantially more views (28,000 film views in 2020), we anticipate that the series on writing reports will receive more views as engineering faculty learn about it. References 1. L. Reave, "Technical Communication Instruction in Engineering Schools: A Survey of Top-Ranked U.S. and Canadian Programs," Journal of Business and Technical Communication, 18 (4), 452 – 490. 2. "Tutorial on Writing Technical Reports," https://xxxxx.xxx.edu/scientificwriting/tutorial-reports/ (_____________________: _________________________ University, 2020). 3. K. A. Smith, A. F. McKenna, R. C. Chavela Guerra, R. Korte, and C. Swan, "Innovation Corps for Learning (I-Corps™ L): Assessing the Potential for Sustainable Scalability of Educational Innovations," 2016 ASEE Annual Conference & Exposition (New Orleans, Louisiana: ASEE, June 2016), 10.18260/p.25702. 4. S. A. Ambrose, M. W. Bridges, M. DiPietro, M. C. Lovett, and M. K. Norman, How Learning Works: Seven Research-Based Principles for Smart Teaching (San Francisco: Josey-Bass, 2010), pp. 76 – 79.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,130
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,029
Tête enseignante GPT0,289
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle