Cloud-based science labs allow science classrooms to engage in authentic science inquiry without the logistical and procedural complexities of real hands-on laboratories. A major challenge is to understand the variation of teaching contexts and needs and the implication for technology design. Utilizing an Biology Cloud Lab (BCL) for real-time experimentation that had been deployed as Massive Open Online Course (MOOC) previously, we now execute three in-depth case studies of how K-12 teachers (with ~200 students) adapt and deploy this BCL and MOOC material for their own class-room needs. We uncovered that teachers differed in their diverse range of learning objectives (e.g., large-scale data analysis vs. computational modeling based on real data), how the teachers were able to adapt the BCL and MOOC material differently to meet their respective curricular needs, and how logistically complex and time intensive processes can be automated to allow teachers and students to focus on key practices. This work reveals the need and design rules for well-standardized and modularized cloud-based science laboratories and accompanying learning materials to then enable rich inquiry based learning activities that work at scale while also being highly customizable to the local classroom contexts.
Large-Scale and Versatile Deployment of Biology Cloud Labs in Schools through Teacher Driven Curricula Design
Tahrina Ahmed,Engin Bumbacher,Paulo Blikstein,I. Riedel-Kruse
Published 2024 in ACM Conference on Learning @ Scale
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- Publication year
2024
- Venue
ACM Conference on Learning @ Scale
- Publication date
2024-07-09
- Fields of study
Biology, Computer Science, Education
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Semantic Scholar
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