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  • David Curtis
Automation and Make
Unrestricted Use
CC BY
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A Software Carpentry lesson to learn how to use Make Make is a tool which can run commands to read files, process these files in some way, and write out the processed files. For example, in software development, Make is used to compile source code into executable programs or libraries, but Make can also be used to: run analysis scripts on raw data files to get data files that summarize the raw data; run visualization scripts on data files to produce plots; and to parse and combine text files and plots to create papers. Make is called a build tool - it builds data files, plots, papers, programs or libraries. It can also update existing files if desired. Make tracks the dependencies between the files it creates and the files used to create these. If one of the original files (e.g. a data file) is changed, then Make knows to recreate, or update, the files that depend upon this file (e.g. a plot). There are now many build tools available, all of which are based on the same concepts as Make.

Subject:
Computer Science
Information Science
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Richie-Halford
Ana Costa Conrado
Andrew Boughton
Andrew Fraser
Andy Kleinhesselink
Andy Teucher
Anna Krystalli
Bill Mills
Brandon Curtis
David E. Bernholdt
Deborah Gertrude Digges
François Michonneau
Gerard Capes
Greg Wilson
Jake Lever
Jason Sherman
John Blischak
Jonah Duckles
Juan F Fung
Kate Hertweck
Lex Nederbragt
Luiz Irber
Matthew Thomas
Michael Culshaw-Maurer
Mike Jackson
Pete Bachant
Piotr Banaszkiewicz
Radovan Bast
Raniere Silva
Rémi Emonet
Samuel Lelièvre
Satya Mishra
Trevor Bekolay
Date Added:
03/20/2017
Teaching with research data: report to the Australian National Data Service (ANDS)
Unrestricted Use
CC BY
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Teaching with Research Data by the Australian National Data Service (ANDS) provides nine case studies of courses that incorporate data usage in teaching. These case studies cover various subject areas. Two examples activities are:

History at the University of Melbourne: data creation and text analysis in the humanities
The course includes an introduction to big data. The creation of vast textural databases means that it is possible not just to find information but to analyse and interpret in ways not previously available for teaching or for the general public. Students are encouraged to use databases of text such as Google Books (using NGram) or the NLA’s Trove newspapers (using QueryPic) to generate graphs of word use or phrase use frequency to see whether their findings accord with other evidence or to otherwise add depth to their assignments. Students are required to open a Zotero account, and use it to collect and present information they have collected. Use of Omeka is currently under investigation: this is an open source web publishing platform to display online exhibitions of scholarly materials and has been one of those resources publicised by the University of Melbourne Research Bazaar.

Approaches to Research in Education at Flinders University: learning social science methodology using real data
David Curtis is Associate Professor, Educational Research at Flinders University where he also teaches a number of subjects to do with statistical methods and research techniques as part of masters degree courses in education. One subject in particular, Approaches to Research (EDUC9761) has a focus on using authentic data, most often PISA data from the OECD19 and LSAY data collected by ACER20. The primary object of the course is to introduce both qualitative and quantitative approaches to research, including the identification of problems, literature review, developing questions and hypotheses, collecting and analysing data and reporting and evaluating research. In this context, use of authentic data provides an opportunity to explore real issues within the field and to integrate the students’ studies with their own research interest. Using real world data means that students confront issues such as incompleteness, measures which are ‘not quite as good as you might wish they were’ and other problems usually not encountered with manufactured data sets.

Subject:
Arts and Humanities
Social Science
Material Type:
Lesson
Author:
David Curtis
David Goodman
Margaret Henty
Date Added:
12/12/2018