Incorporating Computer Programming & Data Science into a Guided Inquiry-Based Undergraduate Ecology Lab

The biological sciences are becoming increasingly reliant on computer science and associated technologies to quickly and efficiently analyze and interpret complex data sets. Introducing students to data analysis techniques is a critical part of their development as well-rounded, scientifically liter...

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Veröffentlicht in:The American biology teacher Jg. 81; H. 9; S. 649 - 657
Hauptverfasser: Rahn, Jennifer, Willner, Dana, Deverick, James, Kemper, Peter, Saha, Margaret
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Reston University of California Press 01.11.2019
University of California Press Books Division
Schlagworte:
Biodiversity
biological diversity
Computer programming
Computer science
Data analysis
Data science
Ecological effects
Ecological monitoring
INQUIRY & INVESTIGATION
Inquiry method
Inquiry-based lab exercise
Jupyter Notebook
Laboratories
Programming languages
Scientific Research
Students
ISSN:0002-7685, 1938-4211
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Abstract The biological sciences are becoming increasingly reliant on computer science and associated technologies to quickly and efficiently analyze and interpret complex data sets. Introducing students to data analysis techniques is a critical part of their development as well-rounded, scientifically literate citizens. As part of a collaborative effort between the Biology and Computer Science departments at William & Mary, we sought to develop laboratory exercises that would introduce basic ideas of data analysis while also exposing students to Python, a commonly used computer programming language. We accomplished this by developing exercises within the interactive Jupyter Notebook platform, an open-source application that allows Python code to be written and executed as discrete blocks in real time. Students used the developed Jupyter Notebook to analyze data collected as part of a multiweek ecology field experiment aimed at determining the effect of white-tailed deer on aspects of biological diversity. These inquiry-based laboratory exercises generated scientifically relevant data and gave students a chance to experience and participate in ongoing scientific research while demonstrating the utility of computer science in the scientific process.
AbstractList The biological sciences are becoming increasingly reliant on computer science and associated technologies to quickly and efficiently analyze and interpret complex data sets. Introducing students to data analysis techniques is a critical part of their development as well-rounded, scientifically literate citizens. As part of a collaborative effort between the Biology and Computer Science departments at William & Mary, we sought to develop laboratory exercises that would introduce basic ideas of data analysis while also exposing students to Python, a commonly used computer programming language. We accomplished this by developing exercises within the interactive Jupyter Notebook platform, an open-source application that allows Python code to be written and executed as discrete blocks in real time. Students used the developed Jupyter Notebook to analyze data collected as part of a multiweek ecology field experiment aimed at determining the effect of white-tailed deer on aspects of biological diversity. These inquiry-based laboratory exercises generated scientifically relevant data and gave students a chance to experience and participate in ongoing scientific research while demonstrating the utility of computer science in the scientific process.
\The biological sciences are becoming increasingly reliant on computer science and associated technologies to quickly and efficiently analyze and interpret complex data sets. Introducing students to data analysis techniques is a critical part of their development as well-rounded, scientifically literate citizens. As part of a collaborative effort between the Biology and Computer Science departments at William & Mary, we sought to develop laboratory exercises that would introduce basic ideas of data analysis while also exposing students to Python, a commonly used computer programming language. We accomplished this by developing exercises within the interactive Jupyter Notebook platform, an open-source application that allows Python code to be written and executed as discrete blocks in real time. Students used the developed Jupyter Notebook to analyze data collected as part of a multiweek ecology field experiment aimed at determining the effect of white-tailed deer on aspects of biological diversity. These inquiry-based laboratory exercises generated scientifically relevant data and gave students a chance to experience and participate in ongoing scientific research while demonstrating the utility of computer science in the scientific process.
Author Rahn, Jennifer
Saha, Margaret
Kemper, Peter
Deverick, James
Willner, Dana
Author_xml – sequence: 1
  givenname: Jennifer
  surname: Rahn
  fullname: Rahn, Jennifer
  email: jjrahn@wm.edu
  organization: ) is Laboratory Coordinator in the Department of Biology
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  givenname: Dana
  surname: Willner
  fullname: Willner, Dana
  email: dlwillner@wm.edu
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  givenname: James
  surname: Deverick
  fullname: Deverick, James
  email: jwdeve@wm.edu
  organization: ) are Lecturers in the Department of Computer Science
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  givenname: Peter
  surname: Kemper
  fullname: Kemper, Peter
  email: pxkemp@wm.edu
  organization: ) is an Associate Professor in the Department of Computer Science
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  givenname: Margaret
  surname: Saha
  fullname: Saha, Margaret
  email: mssaha@wm.edu
  organization: ) is Chancellor Professor in the Department of Biology, all at William & Mary, Williamsburg, VA 23187-8795
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CitedBy_id crossref_primary_10_1002_ece3_6607
crossref_primary_10_1016_j_ecolmodel_2024_110926
crossref_primary_10_1371_journal_pcbi_1010372
Cites_doi 10.1098/rspb.2014.0261
10.1016/j.biocon.2005.10.027
10.3389/fmicb.2015.00678
10.1016/j.acra.2017.11.024
10.1111/j.1523-1739.2004.00515.x
10.1152/jn.00137.2016
ContentType Journal Article
Copyright 2019 National Association of Biology Teachers. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, https://www.ucpress.edu/journals/reprints-permissions.
2019 National Association of Biology Teachers
Copyright University of California Press Books Division Nov/Dec 2019
Copyright_xml – notice: 2019 National Association of Biology Teachers. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, https://www.ucpress.edu/journals/reprints-permissions.
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– notice: Copyright University of California Press Books Division Nov/Dec 2019
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SubjectTerms Biodiversity
biological diversity
Computer programming
Computer science
Data analysis
Data science
Ecological effects
Ecological monitoring
INQUIRY & INVESTIGATION
Inquiry method
Inquiry-based lab exercise
Jupyter Notebook
Laboratories
Programming languages
Scientific Research
Students
Title Incorporating Computer Programming & Data Science into a Guided Inquiry-Based Undergraduate Ecology Lab
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