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Using computational modeling to teach experimental design

Using computational modeling to teach experimental design
Using computational modeling to teach experimental design
In many laboratories during an undergraduate science education, students are given a set of procedures to follow to obtain a pre-determined outcome. Often students give little thought to the underlying scientific principles and lack a true understanding of the experimental protocol. Not only does this laboratory format not represent ‘real’ science, it leaves students unprepared for the often unpredictable and intimidating nature of experimental design. Here we have chosen classic biochemical experiments paired with computational modeling approaches to help students navigate the process of designing an experiment, from initial planning to hypothesis development to data analysis. Students can use the modeling mechanisms to help predict experimental outcomes and gain a better understanding of scientific concepts.
0892-6638
559.34
Wright, Amanda
d54fa418-5d37-403d-9d34-23b73e50e595
Gammack, David
65b60f25-7546-4132-99da-e140f4727f8d
Wright, Amanda
d54fa418-5d37-403d-9d34-23b73e50e595
Gammack, David
65b60f25-7546-4132-99da-e140f4727f8d

Wright, Amanda and Gammack, David (2015) Using computational modeling to teach experimental design. FASEB Journal, 29 (S1), 559.34. (doi:10.1096/fasebj.29.1_supplement.559.34).

Record type: Meeting abstract

Abstract

In many laboratories during an undergraduate science education, students are given a set of procedures to follow to obtain a pre-determined outcome. Often students give little thought to the underlying scientific principles and lack a true understanding of the experimental protocol. Not only does this laboratory format not represent ‘real’ science, it leaves students unprepared for the often unpredictable and intimidating nature of experimental design. Here we have chosen classic biochemical experiments paired with computational modeling approaches to help students navigate the process of designing an experiment, from initial planning to hypothesis development to data analysis. Students can use the modeling mechanisms to help predict experimental outcomes and gain a better understanding of scientific concepts.

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Published date: 1 April 2015

Identifiers

Local EPrints ID: 479292
URI: http://eprints.soton.ac.uk/id/eprint/479292
ISSN: 0892-6638
PURE UUID: a812fe13-3dda-41a6-b34d-450f8f3119dc
ORCID for David Gammack: ORCID iD orcid.org/0000-0003-1214-1057

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Date deposited: 20 Jul 2023 16:53
Last modified: 17 Mar 2024 03:33

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Contributors

Author: Amanda Wright
Author: David Gammack ORCID iD

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