TY - CHAP
T1 - Incorporating a commercial biology cloud lab into online education
AU - Riedel-Kruse, Ingmar H.
N1 - Publisher Copyright:
© Springer International Publishing AG 2018.
PY - 2018
Y1 - 2018
N2 - Traditional biology classes include lab experiments, which are missing from online education. Key challenges include the development of online tools to interface with laboratory resources, back-end logistics, cost, and scale-up. The recent emergence of biology cloud lab companies offers a promising, unexplored opportunity to integrate such labs into online education. We partnered with a cloud lab company to develop a customized prototype platform for graduate biology education based on bacterial growth measurements under antibiotic stress. We evaluated the platform in terms of (i) reliability, cost, and throughput; (ii) its ease of integration into general course content; and (iii) the flexibility and appeal of available experiment types. We were successful in delivering the lab; students designed and ran their own experiments, and analyzed their own data. However, the biological variability and reproducibility of these online experiments posed some challenges. Overall, this approach is very promising, but not yet ready for large-scale deployment in its present form; general advancements in relevant technologies should change this situation soon. We also deduce general lessons for the deployment of other (biology and non-biology) cloud labs.
AB - Traditional biology classes include lab experiments, which are missing from online education. Key challenges include the development of online tools to interface with laboratory resources, back-end logistics, cost, and scale-up. The recent emergence of biology cloud lab companies offers a promising, unexplored opportunity to integrate such labs into online education. We partnered with a cloud lab company to develop a customized prototype platform for graduate biology education based on bacterial growth measurements under antibiotic stress. We evaluated the platform in terms of (i) reliability, cost, and throughput; (ii) its ease of integration into general course content; and (iii) the flexibility and appeal of available experiment types. We were successful in delivering the lab; students designed and ran their own experiments, and analyzed their own data. However, the biological variability and reproducibility of these online experiments posed some challenges. Overall, this approach is very promising, but not yet ready for large-scale deployment in its present form; general advancements in relevant technologies should change this situation soon. We also deduce general lessons for the deployment of other (biology and non-biology) cloud labs.
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U2 - 10.1007/978-3-319-64352-6_32
DO - 10.1007/978-3-319-64352-6_32
M3 - Chapter
AN - SCOPUS:85063448902
T3 - Lecture Notes in Networks and Systems
SP - 331
EP - 343
BT - Lecture Notes in Networks and Systems
PB - Springer
ER -