Module Orientation

Instructional materials for the LASER Orientation and other modules are linked below and come in three main flavors:

  1. GitHub and associated repositories are where the all the raw materials for each module are saved and accessible to the public. Instructors are welcome to fork or clone this repository and adapt for their own purposes.

  2. Posit Cloud and accompanying workspaces are where students complete interactive coding assignments including Code-Alongs, Case Studies, Badges and Microcredentials. There is also an instructor workspace free of much of the cruft included in the GitHub repository.

  3. Github Pages is used to create HTML versions of each activity (or previews of activities like Case Studies and Badges) and are linked under each module description below.

Github
Repository for Instructors
Posit Cloud Workspace for Students | Instructors

Orientation Module: The LASER Toolkit

The Orientation Module is designed to get learners up and running with the concepts, tools, and processes that guide the LASER curriculum. The orientation begins with a Conceptual Overview focused on the benefits of reproducible research (Gandrud 2013) and tools used by LASER to for this purpose. The Code-Along is a gentle introduction to R/Python and the data-intensive research workflow introduced by Krumm, Means, and Bienkowski (2018) and covered in greater depth by . The coding Case Study expands upon the code-along and introduces working with Quarto, an open-source scientific and technical publishing system. Finally, learners earn their first LASER Badge by publishing their work to the web.

Conceptual
Overview
Reproducible Research & Tools
Code Along The Data-Intensive Research Workflow
Readings &
Reflection
Learning Analytics Goes to School
Case Study A Coding Case Study with Quarto
Badge LASER Orientation Badge

References

Gandrud, Christopher. 2013. Reproducible Research with r and r Studio (3rd Edition). CRC Press. http://github.com/christophergandrud/Rep-Res-Book.
Krumm, Andrew, Barbara Means, and Marie Bienkowski. 2018. Learning Analytics Goes to School. Routledge. https://doi.org/10.4324/9781315650722.