Inclusive Learning Through Equity-Driven Approaches to Design in Engineering Education
Notice bibliographique
Résumé
Despite it being widely acknowledged that integrating principles of equity, diversity, inclusion, and accessibility (EDIA) in engineering has numerous benefits such as more innovative and inclusive design outcomes, there have been ongoing challenges in addressing equity, promoting diversity, and fostering inclusive teaching and learning strategies in higher education. If EDIA is taught separately from coursework in engineering, students are unlikely to engage with or incorporate EDIA principles in their work. Moreover, the pedagogical approaches for EDIA concepts, which include exploratory discussion and reflection, can be a barrier for student learning if they are not valued in the same way as traditional engineering epistemology and ideologies that prioritize a technical space and objective data. Lastly, evidence demonstrates that a lack of sense of belonging for underrepresented students can impact their learning experience. It is important to address how teaching approaches impact the shift of student mindsets in their design work and their engagement with the learning environment. In this exploratory project, we seek to understand the ways in which learning equity-driven approaches to design, such as design thinking, may impact engineering students’ perceptions of inclusivity in their learning environment and the quality of inclusivity in the work that they design and engineer. We focus on the rationale and development of the methodology in this paper since the work is still in progress. We are working with a diverse team of educators and researchers to review and revise course goals, student learning outcomes and related course content for two design thinking courses in a master’s level engineering program. Changes to the course material include further integrating EDIA principles and the “Liberatory Design framework” described by the Hasso Plattner Institute of Design as “a process and practice to liberate designers from habits that perpetuate inequity.” The impact of such revision is examined through qualitative analysis of students’ written reflections with prompts that focus on EDIA themes. A post-course survey is also used to assess students’ perceptions of EDIA in relation to their academic, professional, and personal learning experiences throughout the program and, more specifically, the design thinking course learning outcomes. Preliminary findings suggest that students connect design thinking approaches with an awareness of the value of diversity in their design teams and with more inclusive design outcomes for the end-user. This exploratory work can inspire research to further examine the role of design thinking and related pedagogical approaches in supporting the integration of EDIA principles in teaching engineering design.
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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 | 0,037 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,019 |
| Communication savante | 0,014 | 0,010 |
| Science ouverte | 0,002 | 0,023 |
| Intégrité de la recherche | 0,002 | 0,005 |
| 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 ».