Discovery: Transition of an Inquiry-focused Learning Program to a Virtual Platform During the COVID-19 Pandemic (Evaluation)
Notice bibliographique
Résumé
Abstract The shift to distance learning in response to the COVID-19 pandemic has presented teachers and students with several challenges. Teachers have found themselves quickly creating distance learning materials to provide equal or greater educational opportunity and engagement as in-person instruction. This shift is met with parallel increased demand on students to independently manage their learning and coursework with the absence of in-person supervision, support, and peer interaction. In this work, we describe our approach and observations in transitioning Discovery, a secondary student science, technology, engineering, and mathematics (STEM) education program, to a virtual platform. Developed by graduate students in 2016, Discovery was designed to engage secondary students in semester-long inquiry-based projects within the context of biomedical engineering. Projects are designed to foster and reinforce critical thinking skills required for post-secondary study. Throughout the semester, students design and execute experiments within post-secondary laboratories with instructional support from both their teachers and graduate student volunteers. In response to university teaching space closures in early 2020, we developed and delivered a virtual offering of Discovery. In contrast to in-person delivery, this initial virtual offering placed greater emphasis upon quantitative analysis rather than experimental design and execution. Access to virtual laboratory simulations was provided as a substitute for in-laboratory skill development. While overall assessment of student (survey instrument) and teacher (interviews) experiences revealed a highly positive perception of the program experience, areas for improvement were also highlighted. Many students reported struggling with motivation to keep up with course materials and soft deadlines (60%) as well as the lack of guidance provided by in-person mentor and teacher interactions (50%). Teacher interviews echoed quantified student perceptions, but further identified lamentation at the loss of student-driven, open-ended, and iterative problem-solving opportunities typically afforded by Discovery. Consequently, we developed an adjusted virtual program for the Fall 2020 term. The redesigned program reintroduced the open-ended aspect of previous in-person projects, and rather than including access to commercially available virtual laboratory simulation, greater focus was placed on design of experimental procedures that were evaluated and simulated by graduate students. Additionally, greater care was taken to discretize project components and deliverable deadlines to provide enhanced structure and guidance for students. We observed this updated program structure to similar outcomes of in-person offerings. A slight majority (51.4%) of Fall 2020 students achieved higher grades for Discovery deliverables than other class assessments. In post-program surveys, ~49% of students indicated they are more likely to pursue STEM courses, ~89% would participate in the program again, and ~78% responded that the experience made them more comfortable with completing university or college level laboratory work. While these results were encouraging, comparisons to previous in-person outcomes and analysis of teacher experiences (interviews) highlighted persistent gaps in student experience while completing the program virtually.
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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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,003 | 0,006 |
| Science ouverte | 0,002 | 0,001 |
| 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 ».