Engineering or Physical Sciences: How to Choose? An Exploration of How First-Year University Students Choose between Studying the Physical Sciences and Engineering
Notice bibliographique
Résumé
Abstract Engineering and the physical sciences share many common foundations in both knowledge and required skills. Yet working scientists and professional engineers may be more inclined to express the differences between their professions and domains of practice, rather than their similarities. The differences between the natural sciences and engineering – in their goals, activities, fields of study, level of materials studied, methodologies, and cultures – have been discussed by scholars in the philosophy and sociology of science as well as by scholars of the practice of engineering and in the emerging field of the philosophy of engineering. Given the actual and perceived disciplinary and career differences between the physical sciences and engineering, how do undergraduate students choose between them for university study? This paper seeks to answer this question by analyzing and examining the results from an ethically-approved online research questionnaire directed at first-year undergraduate university students conducted in September 2022 at a mid-sized comprehensive university. The questionnaire consists of 29 items that ask respondents about the influence of personal, familial, educational, societal/cultural factors on their interest in or decision to study engineering or one of the physical sciences, as well as about their perceptions of engineering versus the physical sciences. Demographic information is also collected from the respondents. The outcomes reported in this paper consist of statistical correlations, as assessed by significance levels, from analysis of the questionnaire data. The theoretical framework for our inquiry is primarily situated within the scientific perspective of critical realism that conceives of knowledge as resulting from the correct understanding of the data of experience, and in which adult students are viewed as operating within horizons of their knowledge and values; within this framework, education can be viewed as constructivist. Within that framework and the context of this study we also explore the dynamics of common models of decision making, including those of rational choice theory, value-focused decision making, and others. Other theoretical influences include Friere's liberation pedagogy, cognitive and affective interactions in attraction to and identification with professional careers, and new literacies for engineering and science. The paper will also discuss how the statistical results from the survey may inform outreach and pedagogy for science and engineering, and thus help to foster greater attraction and retention of undergraduate students in STEM fields, and greater career sustainability and life satisfaction for STEM graduates.
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.
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 | 0,010 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,011 | 0,005 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».