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This is a repository for the workshop *Online Data and Open Source Tools: Analyzing Educational Internet Data Using R* at AECT's Annual International Convention on 2019/10/23
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README.md

AECT-workshop-2019

This is a repository for:

Online Data and Open Source Tools: Analyzing Educational Internet Data Using R
at AECT's Annual International Convention in Las Vegas, NV
Wednesday, 10/23, 9:00am - 3:50pm

Optional Pre- and Post-Survey

We are trying to better understand how educational researchers learn to use R to carry out educational research (and instructional design- and learning, design, and technology-related work). Please consider completing the following pre- and post-surveys (to receive up to $15.00 in compensation if you complete both parts and upload an R Markdown document you worked on).

Description

In this workshop, we help participants to learn how to use the R statistical software to analyze Internet data that is relevant to educational research. In particular, we on learning how to get started with R, how to analyze social media data from an already-completed project and beginning one’s own analysis. This workshop promises to support participants to become more confident in their ability to engage in analyzing complex data sources collected from digital sources.

Who This Workshop is For

This workshop is for beginning and experienced scholars interested in using new statistical and computational research methods in their work. More specifically, the level of instruction will be suitable for researchers—from a wide variety of scholarly and professional backgrounds—looking for an introduction to R. There are no suggested prerequisites for attending, but we do require that participants bring a computer (Mac, Windows, or Linux are all suitable for working in R) to the workshop. To get the most from the workshop, install R and R Studio ahead of time (instructions below).

Background

Educational and instructional technology scholars at AECT are at the leading-edge of innovative research on teaching and learning, and remaining there requires ongoing, inspired learning. That is, just as technologies have changed the way teaching and learning happen, they also change the ways that educational research is carried out (Mishra, Koehler, & Greenhow, 2016). For example, advancements in technology have created new sources of data, such as those freely available on the Internet (Munzert, Rubba, Meißner, & Nyhuis, 2015), as well as newer methods and practices for analyzing those data (cite). Thus, even as we engage in research on how technology changes the field of education, scholars at AECT benefit from inspired professional learning on how technology can change that research.

In this workshop, we help participants learn how to use the R programming language and statistical software to analyze Internet data that is relevant to educational research. R is becoming especially widely-used in educational research: At the 2019 American Educational Research Association Annual Meeting, for example, five professional development and training courses include the use of R. R is increasingly prioritized over other statistical software not only because it provides researchers with access to a wide range of powerful statistical techniques and tools at no cost and with considerable rigor but also because R is also useful for collecting research data, publishing results, and inviting reproducibility. As members of the AECT community increasingly engage in analyzing complex data sources collected from digital sources (Kimmons, Carpenter, Veletsianos, & Krutka, 2018; Romero-Hall, Kimmons, & Veletsianos, 2018; Rosenberg, Greenhalgh, Koehler, Hamilton, & Akcaolgu, 2016; Greehalgh, Staudt Willet, & Rosenberg, 2018; Veletsianos, Kimmons, Larsen, Dousay, & Lowenthal, 2018; Xing & Gao, 2018), R is especially relevant to those seeking to follow their example. Furthermore, the use of R—an open source software—is especially timely in light of conversations in the AECT community about the value of open scholarship.

Purpose

While R is becoming increasingly widely-used, R has a steep learning curve for beginners, calling for additional opportunities for professional learning for educational researchers. In this session, we provide support and guidance for using R for exploring Internet data—a task that R is particularly well suited for. We focus on the analysis of a dataset that is likely of interest to many AECT participants: social media data collected from educationally-relevant Twitter hashtags.

We will use a project-based learning approach to provide an overview of the use of R for educational research involving Internet data. By doing so, this session provides inspired professional learning related to learning how to use R to analyze the kinds of complex data sources that members of the AECT community increasingly seek to analyze. In doing so, this session will support participants to not only learn about R, how to set it up, and how to use it, but will also help participants to develop the confidence to access and analyze quantitative data.

Objectives

The workshop objectives are as follows:

  • Learn how to get started with R using open-source (and freely-available tools), including the R software and add-on packages.
  • Learn how to use R to analyze research data: first, by running the commands from an already-completed research project, then by carrying out and document one’s own analysis using a dataset provided by the organizers.
  • Learn several advanced uses of R, including: social network analysis, text analysis, and machine learning methods.
  • Begin one’s own analysis of educational Internet data.
  • Become more confident in one’s ability to access and analyze complex, quantitative sources of data.
  • Understand how to learn more with respect to using R for research purposes.

Installations

If you have issues with any of the installations below (and don’t worry, they’re all very small and won’t take up much space on your computer) please contact me (staudtwi@msu.edu) and I can try to work with you to get it resolved before the workshop. If we’re unsuccessful, at least we know from the start of the workshop that we’ll need to work with you to get up to speed.

To download R:

  • Visit this page to download R: https://cran.r-project.org/
  • Find your operating system (Mac, Windows, or Linux)
  • Download the 'latest release' on the page for your operating system and download and install the application

To download R Studio:

  • Visit this page to download R studio: https://www.rstudio.com/products/rstudio/download/
  • Find your operating system (Mac, Windows, or Linux)
  • Download the 'latest release' on the page for your operating system and download and install the application

Slides

The slides are here: https://bretsw.github.io/aect19-workshop/

Interactive R Markdown File

demo-doc.Rmd is an interactive R Markdown file that accompanies the presentation.

R Studio Cloud

An R Studio Cloud workspace/environment for the demo-doc.Rmd document in this repository is availabile here: https://rstudio.cloud/project/597547

This may be especially helpful if you do not yet have R and R Studio installed on your computer. It does require you to create an account or to use a Google (or GitHub) account to sign-in.


Acknowledgments

Thank you to Joshua Rosenberg and Emily Bovee for developing the workshops this workshop is adapted from: https://github.com/jrosen48/MTSU-workshop and https://github.com/jrosen48/MSU-workshop-2019

Parts of the content for this workshop are also adapted from:

Finally, parts of the content for this workshop are inspired from content associated with the Data Science Specialization for UO COE (led by Daniel Anderson)

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